Digitalization of Visual Management System (mieruka)

Digitalization of Visual Management System (mieruka)

Muhammad Dzulkarnain bin Shahidan

Department of Transport and Innovation Centre

Faculty of Engineering, Computing, and Science

Swinburne University of Technology

Sarawak, Malaysia

A thesis submitted in partial fulfilment of the requirement for the degree of Master of

Engineering (Research)

October 2020

ii

Dedicated to

To The One I Love, My Family

iii

Abstract

Visualization has widely used in the manufacturing industry, which has played the most

significant role in spreading information. It allows the ease of communication towards different

environments of the organization. In the same time, the transparency of the industry has been

promoted as the main features of having good visualization. As the revolutionary of the

industry goes by, the transparency of industry has been decreased day by day. This lack has

made the researcher in evolving the visualization techniques in line with the current industrial

revolution era. Efficient visualization will prompt the employees with the following action

whenever they have seen it. In making visualization effective, the visualized visual elements

must contain beneficial information that is attractive to the employee. In adaption to the rapid

development of Industry 4.0, this research was implemented the Digital Visual Management

System (DVMS) towards Autokeen Sdn. Bhd., an automotive stamping manufacturing

industry. This implementation was to improve visual management (VM) tools in Autokeen by

using DVMS to manage and monitor their production activity visually. The proposed research

based on the studied conventional visual management system and the operators behavioural

towards it, then form an interactive visualization interface. This interface is the formation by

merging the conventional towards the smart system for the operator to get a good understanding

of the new smart system. The new visual management system, with the capability of

autonomously exchanging information, triggering actions, and self-controlled, will be formed

by the end of this research. It aims to get the highest interaction towards the employee, thus

increase the production performance.

iv

Acknowledgements

First and foremost, thanks to our Almighty GOD, Allah S.W.T, for the wisdom and blessing

he bestowed upon me throughout this journey.

Deepest gratitude and appreciation to my principal coordinating supervisor, Dr Valliapan

Raman, for his guidance, encouragement, and supports he has given me throughout this

research.

Besides that, I would like to give thanks to my associate supervisor, Dr Weidong Huang, the

board of directors of Transport Innovation Centre (TIC), Dr Suresh Palanisamy & Dr Almon

Chai for their advice and guidance throughout my study.

Deepest gratitude to my families as well, especially to my parents. Thank you for your endless

support, encouragement, and believe me that I can do my best in anything when I put my mind

and determination to it.

Big thanks to MARII, allowing me to handle this industrial based research. Giving me a great

experience going through all these challenges paths and even for the sponsorship. Instead of

that, I also would like to give thanks to Autokeen Sdn. Bhd., who gives me trustworthy to do

this research.

Other than that, I also want to thanks to all Transport Innovation Centre (TIC) members for

sharing their knowledge of different fields and advice during the sharing sessions.

The simple phrase "thank you" could not present how thankful I am to everyone. Without any

of you, this research study and dissertation would not be possible.

v

Declaration

I, Muhammad Dzulkarnain bin Shahidan hereby declare that this research study entitled

"Digital Visual Management System (mieruka)" is original and does not contain any material

which has accepted for the award of any other degree or diploma, except where due reference

has made in the text of the examinable outcome. To the best of my knowledge, this thesis does

not contain any material previously published or written by another person except where due

reference has made in the text of the examinable outcome; and where the work has based on

joint research or publications, disclosed relative contributions of the respective workers or

authors.

________________________________

(Muhammad Dzulkarnain bin Shahidan)

vi

Contents

Chapter 1 .................................................................................................................................... 1

1.1. Company background ................................................................................................. 3

1.2. Research problem ........................................................................................................ 8

1.3. Research question ........................................................................................................ 9

1.4. Research objectives ..................................................................................................... 9

1.5. Research delimitation ................................................................................................ 11

1.6. Research process ....................................................................................................... 12

1.7. Research contribution ................................................................................................ 13

1.8. Thesis structure ......................................................................................................... 13

Chapter 2 .................................................................................................................................. 14

2.1. Mieruka ..................................................................................................................... 14

2.1.1. Visualization one of Lean Production technique ............................................... 16

2.1.2. Transparency of Visualization ........................................................................... 19

2.1.3. Visual Management (VM) tools ........................................................................ 20

2.2 Significance of Visualization in Industry .................................................................. 25

2.2.1. Application of VM in current manufacturing sectors ........................................ 26

2.2.2. The uses of VM in other sectors ........................................................................ 27

2.3. The innovation of VM tools ...................................................................................... 28

2.3.1. Industry Internet of Things (IIoT) with Visualization ....................................... 30

CONTENTS

2.3.2. Internet of Things devices .................................................................................. 31

2.4. VM system evaluation tools ...................................................................................... 36

2.4.1. User-centered design (UCD) .............................................................................. 36

2.4.2. Usability evaluation ........................................................................................... 41

2.5. Discussion on Literature Review .............................................................................. 44

2.6. Summary ................................................................................................................... 45

Chapter 3 .................................................................................................................................. 46

3.1 The iterative process of DVMS development ........................................................... 46

3.2 Data collection........................................................................................................... 48

3.2.1 Observation ........................................................................................................ 48

3.2.2 Interviews ........................................................................................................... 48

3.3 Proposed DVMS architecture.................................................................................... 49

3.3.1 Initial phase ........................................................................................................ 49

3.3.2 Prototyping phase............................................................................................... 51

3.3.3 Implementation phase ........................................................................................ 52

3.4 Concept of DVMS ..................................................................................................... 54

3.5 DVMS overview ....................................................................................................... 55

3.6 DVMS requirements ................................................................................................. 56

3.7 DVMS architecture ................................................................................................... 57

3.8 Design process........................................................................................................... 60

3.9 Summary ................................................................................................................... 61

Chapter 4 .................................................................................................................................. 63

4.1 Data Collection .......................................................... Error! Bookmark not defined.

4.2 Problems in the current operation ............................. Error! Bookmark not defined.

4.3 The objective of the current solution......................... Error! Bookmark not defined.

4.4 Visualization Dashboard for proposed DVMS ......................................................... 63

CONTENTS

4.4.1 The first phase of DVMS ................................................................................... 65

4.4.2 The second phase of DVMS .............................................................................. 66

4.4.3 The third phase of DVMS .................................................................................. 69

4.5 Summary ................................................................................................................... 75

Chapter 5 .................................................................................................................................. 76

5.1 Evaluation study framework ..................................................................................... 76

5.2 Evaluation study goals .............................................................................................. 77

5.3 Methods, techniques and participants ....................................................................... 77

5.4 Environment and equipment ..................................................................................... 80

5.5 Study tasks and scenarios .......................................................................................... 82

5.6 Evaluation processes ................................................................................................. 88

5.7 Summary ................................................................................................................... 89

Chapter 6 .................................................................................................................................. 90

6.1 Visual Management (VM) practise in site ................................................................ 90

6.2 Summary of DVMS Implementation ........................................................................ 91

6.3 Heuristic evaluations ................................................................................................. 92

6.4 Results analysis ......................................................................................................... 96

6.5 Standardized questionnaire results & summary ........................................................ 99

6.6 Summary of findings ............................................................................................... 103

6.7 Summary ................................................................................................................. 105

Chapter 7 ................................................................................................................................ 107

7.1 Summary of contributions to Visual Management (VM) in Autokeen ................... 109

7.2 Future works ............................................................................................................ 110

ix

List of Figures

No.

Figure

Title

Page

1.1 Body parts that Autokeen was producing 3

1.2 Hinges that Autokeen was producing 4

1.3 Autokeen WSS Line or Line D. 5

1.4 Standard operation procedure (SOP) and machine datasheet 6

1.5 Cell status chart 6

1.6 Section-Line D safety guidelines 7

1.7 Nut or bolt feeder system controller 7

1.8 Autokeen visual control board 8

1.9 Cross-functional flowchart of research process 13

2.1 Toyota Production System (TPS) House Diagram 19

2.2 The main four characteristics of Industrial Internet of Things

(IIoT)

32

2.3 The human-centered design process, ISO-13407 39

LIST OF FIGURES

3.1 Proposed Digital Visual Management System (DVMS)

architecture

51

3.2 Camera counting system 52

3.3 Prototyping phase DVMS architecture 54

3.4 Implementation phase DVMS architecture 54

3.5 Digital Visual Management System (DVMS) overview 55

3.6 Digital Visual Management System (DVMS) architecture 58

3.7 Overview of Python application working with database 59

3.8 Counting system schematic diagram 60

4.1 The first phase dashboard of the Digital Visual Management

System (DVMS)

66

4.2 Second phase dashboard of DVMS prototype design (a), (b) 67

4.3 Third phase dashboard of the management interface of

DVMS

70

4.4 Third phase dashboard of the production interface of DVMS 73-74

4.5 The emojis for the productivity rate 76

5.1 Evaluation of a workplace environment (a), (b) 82

6.1 The post-improvement after second heuristic evaluation (a),

(b), (c), (d)

96

List of Tables

No.

Figure

Title

Page

2.1 Conventional visual management tools 23-25

2.2 Comparison of Raspberry Pi's performance with a similar

prototype platform

35

2.3 Integrated VM Tools with IoT. 36-37

2.4 UCD methods and application area 40-43

5.1 Sort of usability test method with different type of

techniques and participants.

80-81

6.1 Task completion rates of DVMS management interface

second evaluation study

98

6.2 Task completion rates of DVMS operation interface second

evaluation study

99

6.3 Results referring to SysUse metric, for items 1 – 6 on the

PSSUQ

100

6.4 Results referring to InfoQual metric, for items 7 – 12 on the

PSSUQ

101

LIST OF TABLES

6.5 Results referring to IntQual metric, for items 13 – 12 on the

PSSUQ

102

6.6 Results referring to overall user satisfaction on the PSSUQ 103

6.7 Issues of concern and recommendations for future

development of Digital Visual Management System

(DVMS) at Autokeen.

104-

105

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Commonly Used Acronym

DVMS - Digital Visual Management System

VM - Visual management

TIC - Transport Innovation Center

MARII - Malaysia Automotive Robotic Internet of Things Institute

IIoT - Industry Internet of Things

UCD - User-centered design

WSS - Welding Stationary Station

TPS - Toyota Production System

ISO - International Organization for Standardization

PSSUQ - Post-Study Standardize Usability Questionnaire

SysQual - System quality

InfoQual - Information quality

IntQual - Interface quality

KVA - Kilo-volt-ampere

SOP - Standard operation procedure

COMMONLY USED ACRONYM

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PPE - Personal protective equipment

UI - User interface

IoT - Internet of Things

IR - Industry revolution

LED - Light emitting diode

PDCA - Plan, Do, Check, Act

OPL - One-point lesson

KPI - Key performance indicator

ERP - Enterprise resource planning

OEE - Operational equipment effectiveness

SME - Small medium enterprise

AMM - Aircraft Maintenance Manual

UK - United Kingdom

ID - Identification

STC-

LAM

- Stellenbosch Technology Centre's Laboratory for Advanced

Manufacturing

3D - Three dimensional

ODBC - Open database connectivity

CPS - Cyber Physical System

GHz - Gigahertz

COMMONLY USED ACRONYM

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ARM - Advance RISC machines

CPU - Central processing unit

GUI - Graphical user interface

GPIO - General purpose input/output

RESTful - Representational state transfer technology

GSM - Global system for mobile communication

GPRS - General packet radio services

SQL - Structured query language

USB - Universal serial bus

OpenCV - Open source computer vision

MES - Manufacturing Execution System

PMS - Production Monitoring System

IBM - International Business Machines Corporation

HCI - Human-computer interaction

MySQL - relational database management system

RPi - Raspberry Pi

V - Voltage

DC - Direct current

NPN - Negative-Positive-Negative

1

CHAPTER 1

Introduction

Mieruka (visualization) has become one of the management tools for the manufacturing

industry that attempts to improve industry performance. The presence of this tool was helping

to smooth the manufacturing process, such as managing the order from customers, managing

the manufacturing resources, managing the production activity, controlling the safety around

the workplace, controlling the quality of the product, etc. However, as time goes by, the

globalization of the manufacturing industry has always evolved. This evolution needs great

technology for it to cope with the demands of the customer that still wants perfections. As the

manufacturing of the future, the customer's needs have become the foremost priority by the

manufacturers. Therefore, conventional ways of using the visualization need to be taking into

account. Otherwise, industry performance will decline.

Furthermore, mieruka also has been called Visual Management (VM), which gives the

meaning of connecting and aligning the organizational information with the process

environment and stakeholders, employing stimuli that directly address one or more human

senses. These stimuli transported the quality information to helps people understand the

organizational context at a glance by merely looking around (Tezel, Koskela and

Tzortzopoulos, 2009). VM also can be defined as a communication device used in the work

environment that tells the target worker at a glance how is work has done and whether it is

deviating from the standard (Liker, 2007).

The analogy of the traffic light in the middle of the junction quickly describes the

concept of VM, thus make vital people understand the idea easily. Traffic light used three

different colors to tells the people who were using the road, either red to stop, green to go, or

CHAPTER 1: INTRODUCTION

2

yellow to beware. When the traffic lights turning red to green, the driver immediately starts to

move their car to pass through the junction or any stop line, and when the traffic light starts

turning green to yellow and then to red, people start slowing their car and stand still when

traffic light has completely turned red. These rules have been known by vital people when they

see it. The implementation of this traffic light system was to manage the traffic on the road,

prevent the accident, etc. This concept was explicitly describing what VM functioning in the

road management system.

In the VM, transparency has become the main factor for the organization to have a

successful interaction. With the highest transparency in the manufacturing industry, it will

increase the ease of communication between different levels of manufacturing. The

information disseminated in a glance creates a smaller gap across the industry organizations.

Meanwhile, industry globalization has introduced the fourth industrial revolution (IR 4.0)

where smart linkage of machines, products, and workers were actively engaging with

information computers technologies (ICT) (Mrugalska and Wyrwicka, 2017). This factor has

allowed most of the manufacturing industries take this as an excellent opportunity for VM to

grow. This step has approached because the IR 4.0 offers some new technologies that will help

them take over the globalization and growth of global competition between industries that have

racing to fulfill the customer needs that wanting something with quality with lower investment

(Bauer, Ganschar and Gerlach, 2014). The technologies that have highlighted in the IR 4.0 was

as the Internet of Things (IoT), big data analytics, cloud computing and cybersecurity that

brings a bunch of innovative ways to enhance the visibility and insight of the global markets

(Alasdair Gilchrist, 2016).

This thesis discovers the suitable VM tools for the testing industry, Autokeen Sdn. Bhd.

and implemented an interactive Digital Visual Management System (DVMS) with the

adaptation of the IR 4.0 technologies. The system will contain two different interfaces that are

working as the VM tools that will help Autokeen manage, communicate, control, monitor, and

record the production activity. This innovation helps vital people that separated from a concrete

wall in Autokeen communicating to perform better work or make a decision with more robust

criteria (Segura et al., 2018). Some practical visual aspects were tested in Autokeen to make

sure the theory of visualization has worked well. The implementation used was to make the

operator in the production floor is interconnecting with the management floor through a digital

interactive screen.


3

The prototype of Digital Visual Management System (DVMS) has equipped with a

practical visual aspect that has constructed in the form of a Python application that has been

developed with user-centered design (UCD) method approach to avoid the waste visual design.

The prototype has two different interfaces for different levels which connected over the SQL

database. This database role is to store as much data gain from both interfaces and visualized

back towards both interfaces. It resulting both levels received the correct information and avoid

miscommunication. Lastly, the usability of the DVMS prototype needs to examine to reach up

the highest level of usability and user satisfaction.

1.1. Company background

Autokeen Sdn. Bhd. had established in March 1988. The main activities in Autokeen were

stamping and sub-assembly of metal components, mainly for the automotive industry.

Autokeen is also working for the Malaysian gigantic automotive industry, which is Perodua,

Proton, and Honda for the development of the new car. This partnership is in recognition of

Autokeen's quality and capabilities as one of Malaysia's leading manufacturer of automotive

metal stamping parts (Autokeen Sdn Bhd, no date). Figure 1.1 and Figure 1.2 shows the metal

components (automotive body panel and hinges) has processed in Autokeen.

Figure 1.1: Body parts that Autokeen was producing.


4

Figure 1.2: Hinges that Autokeen was producing.

In this thesis, the researcher asked to focus on sub-assembly activity. The sub-assembly

processes are where the welding process has occurred. It contains a different type of operation,

where standard nut or bold weld, manual spot weld, and fully robotic arm spot weld. The

research concern for this thesis is on the VM tools around the standard nut or bolt weld, WSS

Line, or Line D, where three cells (35 KVA, 50 KVA 6, and 50 KVA 5) has chosen to improve

Autokeen's VM with the integration of IR 4.0 features. Figure 1.3 depicted the condition of the

selected cell.

Along this line, visualization tools that have equipped in every cell were safety

guidelines, standard operation procedure (SOP), sample part, machine datasheet, cell status

chart, and nut or bolt feeder system controller. The SOP and machine datasheet, as shown in

Figure 1.4, shows the placement of these VM tools placed at the top front-left of the operator

in each cell. This SOP used to guide the operator while handling the production processes.

Other than that, Figure 1.5 shows the cell status where it described the status of the cell in a

glance when management is monitoring the cell activities. As an example, when the operator

is going to the toilet for an emergency case, they have to select the option on the cell status

chart. This action used to visualize to anyone who is monitoring the cell. In prioritizing the

safety across the production floor, Autokeen places the banner as shown in Figure 1.6, where


5

it was visualizing the minimum requirements of safety procedure. This safety procedure was

showing the personal protective equipment (PPE) for the operator while operating the machine.

Whoever in this area see the incomplete PPE from the operator. They can ask the operator to

follow the safety guidelines.

Other than that, Figure 1.7 shows the nut or bolt feeder system controller where the

feeding system of nut or bolt controlled through this system. It contains a digital screen where

shows the number of produced item, amount of nut or bolt has consumed in one panel, etc.

This system also equipped with an andon system to make the operator alert regarding the error

happen when conducting the assembly process. At the end of the task, the operator record down

the produced item recorded in this system towards A4 paper.

Last but not least, the end of this line located an information board visualizing the

information regarding the production activities resembles this line. Figure 1.8 shows one of the

Autokeen visual control boards where the machine monitoring data has depicted in a sort of

table. This data was showing the machine performance of the WSS machine along the WSS

line or Line D. The other visual control board in this area also using the same material and

displaying the non-interactive data as the showing visualization tools.

Figure 1.3: Autokeen WSS Line or Line D.


6

`

Figure 1.4: Standard operation procedure (SOP) and machine datasheet.

Figure 1.5: Cell status chart.


7

Figure 1.6: Section-Line D safety guidelines.

Figure 1.7: Nut or bolt feeder system controller.


8

Figure 1.8: Autokeen visual control board.

1.2. Research problem

Industry in Malaysia has been rather slow on the uptake of Industry 4.0. It showed that many

of them are still holding on th eir 2.0, 2.5, and 3.0. These revolutions result that they would

rather keep their foreign workers to cut down the cost and gaining mass production and also

computer and automation from investing in digital technology (Ooi et al., 2018). A site visit to

the Autokeen proven that Autokeen was taking on the same step as other industry that Ooi

described. The production floor has a very minimal digital device, especially on the

visualization system, and they still stick with the foreign workers as their workforce. The

existing visualization system that Autokeen used in disseminating the information is visual

control boards. It appeared in a piece of A3 paper that was paste onto the visual control boards,

and some of it was hanging around the working station. Information regarding the production

activities, safety, operators and machines required many processes to be interactively updated when

using the conventional way of the visualization system. It takes much time to collect and update

the information as it is done manually by the employees and makes this conventional way as

inefficient and labour intensive.


9

With the improvised internet and computers technology (ICT) in Industry 4.0, it shows

Autokeen has been far behind in making full use of visualization tools. Industry 4.0 promoted

an easier method to help the dissemination process of information by using smart technologies

such as smart sensors, smart computers, and smart networks. This feature has allowed the

process of formation of an efficient visualization system that can digitally gather production

information and displayed in a real-time production situation. The efficient visualization

system is very much needed to alert the employees and managers in Autokeen. A cheaper

customized system has developed specifically for use in a production environment of an

Autokeen and other automotive industry.

1.3. Research question

In this section, three research questions have defined to fulfill the research objectives. This first

research question provides the foundation for the other issue.

I. In the development of the lean production system, visualization has been striving

by making the production more efficient. With the existence of the visualization

system in Autokeen, did the conventional visualization functionality has been fully

addressed by the employees? If not, what kind of improvement can be made

through the system?

II. What are the best visualization aspects that will give the highest interaction

between employees and managers towards the digitalized visualization system?

III. How can the conventional visualization system transform into the innovated

visualization system that aligns with Industry 4.0 elements?

IV. How does the digitalized visualization system affect the employees and managers

in Autokeen who are never taking visualization as a necessity in daily production

activities?

1.4. Research objectives

The main objective of this research was to implement an innovative visual management system

that allows the highest interaction between the floor in Autokeen industry. The first objective

that needs to achieve in this research is the concept of the visualization itself, how the


10

visualization helps the industry in managing the production activity in a real-time situation. A

preliminary study of mieruka or visualization is the essential step in this research before taking

into account on innovating it. Otherwise, the current development of the visualization system

in Autokeen also was identified to make sure that Autokeen employees realize the visualization

existence.

From the preliminary study, it results in some requirements that are going to be taken,

including in the implementation of the visual management system by making it beneficial

towards Autokeen. The requirements were to helps the employee in the higher floor review,

manage, and monitor the production activity of the production operator. Meanwhile, the

operator is to understand the task given and making sure the production activities are following

the rules and methods that prompt by the system. These activities will be controlled by two

different interfaces that were going to develop and called as Digital Visual Management

System (DVMS). This implemented device will allow the communication visually on a

different floor, thus increasing the transparency of the organization. In doing so, the perfect

tools for running the system also need to figure out. Industry 4.0 has promoted various of tools

for processing the system. A literature study on the Internet of Things features will discuss

more on the method have taken in developing the DVMS with the interactive elements.

Then, the evaluation process of DVMS will be doing by having a usability test to see

how effective the system was. Furthermore, the usability test also will result in how Autokeen

members are satisfied with the implementation of DVMS, which can lead this towards

increasing their productivity.

Otherwise, this project is not only focusing on the Autokeen production floor only. This

customized system is expecting to develop in a cheaper way that is explicitly used widely in

the production environment of the automotive industry.

The objectives are as follows:

I. To investigate the visualization applications in Autokeen.

II. To identify the most suitable visual elements for Autokeen and apply it towards

Autokeen visual management (VM) system.

III. To develop an interactive user interface (UI) for the improvement in the Autokeen

visualization system.

IV. To test the effectiveness of the DVMS in Autokeen.


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1.5. Research delimitation

This section will explain some of the researcher's limitations while developing the Digital

Visual Management System (DVMS) towards Autokeen Sdn. Bhd. For the development of this

research, Autokeen has assigned only the first three cells of the WSS machine or Line D for

the implementation process of DVMS. The data exploration of this cell was allowed by

Autokeen to be collected by the researcher for research purposes.

The first delimitation made for this research is data limitations. As mentioned earlier,

the process of assembling the nut or bolt to the panel has controlled by the nut or bolt feeder

system. This system manages the production activity by limiting the feeding number of nut or

bolt into a specific panel. A precise number of nut or bolt was feed into the particular panel.

No extra or short number of nut or bolt is being used; otherwise, this system will also count the

number of panels that have finished assembled. However, the researcher does not have

permission to get information from the current system. A new counting method needs to

construct as the counting is the primary input for the developed system. This research will also

not examine how the counting process by the sensor or how to access other potential data from

sensors. It will also limit the scope of using the data collected and stored in the SQL database

of DVMS. The data will due to secrecy in Autokeen data come from free open data sources.

The data gained from the sensors will represent the production data of particular processes and

products in the DVMS.

In this research's evaluation process, another delimitation made for this study is the

number of participants and the information on the real-time production plan. As this research

has been conducted remotely from the Autokeen, some of the data could not be precise.

However, these were not obstacles for this research process to be successful. The gathered

information from the evaluation study will describe how satisfied they are with the system.


12

1.6. Research process

Cross-Functional Flowchart

Prot

otyp

ing

Initi

alIm

plem

entat

ion

Start

UCD

User Requirements

2nd phase of DVMS UI

Interactive DVMS UI

Yes

End

No

1st phase of DVMS UI

Literature Study

1st Evaluation

study

3rd phase of DVMS UI

No

Yes

2nd Evaluation

studyYes

No

Figure 1.9: Cross-functional flowchart of the research process.

Figure 1.9 depicted the cross-functional flowchart of the research process describing the

iterative study taken by the researcher to form an interactive Digital Visual Management

System (DVMS) user interface (UI) for Autokeen Sdn. Bhd. It shows that the iterative study

contains three stages. The first stage researcher starts with the literature study on the VM, IoT,

and the suitable methods in developing the UI for integrated VM tools. After that, the user

requirements have been gained as the initial step for developing the first phase of the DVMS

UI. This first phase of DVMS UI was developed with the user-centered design (UCD) approach

before it goes further in the prototyping stage. A UCD method was actively used to get the

right model with effective VM tools for the second phase of DVMS UI. Then, after the

involvement of the UCD approach in the designed process of the second phase of DVMS UI,

it undergoes the first evaluation study to get the user feedback on the usability of the second

phase of DVMS UI. Before the evaluation process began, the researcher planned to get as much

data on the first evaluation study from the second phase of DVMS UI. These processes have

also been done in the third phase of DVMS UI undergoing the second evaluation study.

Nevertheless, in the second evaluation study, much more data were gained to get user

satisfaction from the usability test. Finally, an interactive DVMS UI has formed after all the

cycle processes have already been done, and usability results have been gained.


13

1.7. Research contribution

Previous research has developed a smart visual management system for a resource management

system for the Stellenbosch Technology Centre's Laboratory for Advanced Manufacturing

(STC-LAM) (Steenkamp, Hagedorn-Hansen and Oosthuizen, 2017). The STC-LAM is an

institution that provides excellent quality products in small quantities with high precision

machinery. The present research is developing the smart visualization system for managing the

operator's production performance towards a conventional manufacturing processes company:

where the development of a smart visual management system was developed as an introduction

towards the conventional manufacturing industry that has a minimal number of the digital

approach, unclear plan of the daily task in the production system and lack of communication

skill among operator. This development was done by comparing multiple user interfaces (UI)

to control the operator's production activities in the smart visualization system. This UI was

controlled the operator, where the operator has to interact with any of the visual images that

appear on the screen. The operator's interaction towards the manufacturing activities with the

new smart visual management system was recorded and analyzed to differentiate from the

conventional manufacturing production system. The UI has followed the mieruka concept to

gets the interaction from the operator. Therefore, the present research is intended to contribute

to manufacturing activities, improve operator skill, and develop a cheaper smart visualization

system for use in a production environment of the conventional manufacturing process of other

automotive industries.

1.8. Thesis structure

This section gives a brief overview of the chapter organization in this thesis. Chapter 2 will

investigate the related literature and studies relevant to the development of the Digital Visual

Management System (DVMS). In Chapter 3, overviews of methods that have been constructed

and explained for the research processes. After that, the development processes of DVMS have

presented in Chapter 4. Chapter 5 presents the evaluation processes and results obtained for

related studies and the DVMS. Finally, Chapter 6 summarizes the proposed methods and results

obtained in previous chapters, along with some limitations, putting forward some possible

directions for future research.

14

CHAPTER 2

Literature Review

This chapter will briefly describe and define the visualization, history of visualization, where

it came from, how it functions, when it started to develop, etc. A literature study of visualization

in lean manufacturing also will be described. The entire section of this chapter will let the

readers know about the visualization in the manufacturing industry. Other than that, some

section in this chapter also explaining the visualization application construction industry and

medical sector. Besides, this chapter also introduces the development of visualization with

Industry 4.0. The in-depth studies of the new era's visualization development will give the path

towards developing this research. This chapter is also explaining the innovative tools that have

implemented for IR 4.0 development era. Besides the visualization's advancement, the story

behind successful visualization will also thoroughly explain the right tools and methods for

implementing successful VM tools. The last part of this chapter will elaborate on the literature

of chosen tools and evaluation tools to assess the effectiveness of the visualization's innovation

2.1. Mieruka

Nowadays, Japanese terms have been widely used in this world. Japan has become an example

of most countries in this world (Hamilton and Sanders, 1983). Not only terms but their culture

at any angle has also been spread all around the world. Most of the famous terms used in the

manufacturing side are Kaizen, Kanban, Jidoka, and even the 5S meaning itself has translated

into an English term. Mieruka (見える化) is one Japanese term that has the meaning of

visualization or in-depth visual control. It came from the word mieru (見える) will give the

mean of being able to see and ka (化) for the action of making something (Syed, 2014).

CHAPTER 2: LITERATURE REVIEW

15

Therefore, mieruka gives the meaning of a visual device's capability that can interpret our

actions in any situation. It will evaluate it as fast as possible, whether in standard or deviated

from a visual state. Then, it will prompt any action if it deviates from the standard. Besides,

the word of visual control itself came from the meaning that it can control how it is want to be

through visual.

In the past few decades, mieruka or visualization has been introduced in the Japanese

automotive manufacturing industry by Toyota since they invented the Toyota Production

System (TPS), creating a lean production industry. Lean concept by Taiichi Ohno is to reduce

muda or waste which the things that customer does not pay for it. Thus, Taiichi Ohno creates

a 14 Principles embodied in Part 2 of the book "The Toyota Way" by Jeffrey Liker to explain

how Toyota runs their business. The mieruka concept has been mentioned in the 7th Principe

of the book, "Use Visual Control So No Problem Hidden" (Liker, 2007). Further explanation

of mieruka for lean production has been included in the next sub-section. This section only

paraphrased about the definition of mieruka, where it comes from, when it can use, who the

one in-charge, why mieruka has not spread widely, and how it can innovate.

In this industrial business modernization era, productivity and competitiveness among

industries will increase day by day. At the same time, the reduction of the waste still ongoing

to make it zero. This globalization has highlighted the formation of waste that has never settled.

So, if the waste has not been reduced or removed from the process, the industry's income could

not increase. From that, it results in a static development where the improvement cannot take

place. Story of Hori and the team from the System Development Industry of Hitachi, Ltd,

Kanagawa, Japan, they have used the mieruka to overcome industrial growth. The concept of

mieruka has been used in their plant-floor system that visualizes the total cost ownership

reduction includes the development, maintenance, and management of Hitachi Industrial

Equipment System Co., Ltd., Chiba, Japan. They used mieruka to share and utilize information

by making it visible and understandable to the employee in their industry. They also used the

concept of mieruka by building an architecture system that allows the communication in

between computers and machines in plant-floor systems for the system to run (Hori et al.,

2009). From that, they applied the mieruka concept widely in their industry. Mieruka not only

can be used towards humans but also machines and computers. Machine and computers can

also become the visual device of mieruka that will visualize the information to a human, thus

doing what the visual device information delivers.


16

Mieruka concept has proliferated in most manufacturing industries aligned with Kaizen or

Continuous Improvement to follow and practice the lean concept. Research from Systems

Development Laboratory, Hitachi, Ltd., Japan also by Katsumi Kawano and the team has also

used the mieruka concept to recursively the manufacturing information to make visible at the

factory, thus results in a rapid decision making among stakeholders in the business process

(Kawano, Sameshima and Kato, 2010).

2.1.1. Visualization one of Lean Production technique

Lean production was risen by the young Japanese engineer when Eiji Toyota went on

a three-month pilgrimage to Ford's Rouge plant in Detroit in 1950. Before that, his uncle

Kiichiro had a first visit to Ford in 1929, but many worst things had happened to the Toyoda

family and Toyota Motor Company since they were founded in 1937 until Kiichiro resigned

from the company to accept the responsibility for management failures. From that, Eiji Toyoda

carefully studied Rouge by merely copying and improving it to Toyota Motor Company. Eiji

Toyoda and Taiichi Ohno, the production genius, concludes that the mass production that used

by Rouge could never work in Japan. They were about to implement the Toyota Production

System (TPS), called "lean production". Toyota's first successful example is the textile

machinery business by developing superior technical features on its looms. After that, Toyota's

chief production engineer Taiichi Ohno investigating Detroit's method to be applied towards

Toyota Motor Company, thus improving the TPS (James P. Womack, Daniel Roos, 1990).

The TPS is used interchangeably with lean production because both of them have the

same definition, which is a comprehensive set of techniques that, when combined and matured,

will allow researchers to reduce and then eliminate the wastes (muda). TPS was also the best-

documented lean management system documented by many lean researchers proven itself over

a very long time. This system will make the company leaner and help it become more flexible

and more responsive by reducing waste (Wilson, 2009). Taiichi Ohno, the founder of TPS, said

it even more succinctly:

"All we are doing is looking at the timeline from the moment the customer gives us an order to

the point when we collect the cash. And we are reducing that time line by removing the non-

value-added wastes." (Ohno, 1988)


17

Toyota Takaoka is one of the first lean plants that shows all the visual information such

as daily production targets, numbers of cars produced, equipment breakdown, personnel

shortages, overtime arose, and others (James P. Womack, Daniel Roos, 1990). These were the

example of mieruka tools that shows the production activity in standard or deviated. TPS was

documented and applied it towards their plant, thus shows that the visualization technique

includes in the TPS. One of the visualization techniques used in the Takaoka plant is the andon

boards. These visualization tools are lighted in red, yellow, and green that indicates the machine

or line status. Otherwise, some andon was showing the interactive LED panel that was showing

vital information about the production. This technique will prompt immediate information

about the status of the machine or line of the production. Anyone who visible to the andon

lights will immediately know the machine's current status; it is either in progress, danger, or

trouble. Thus follows with any action required that related to the light shows.

After that, James P. Womack comes with another book named Lean Thinking that tells

what Toyota and other car manufacturing companies do with their factory that makes them

more significant than Europe (James P. Womack, 1996). This book tells about the expansion

of lean production to lean enterprise that allows managers to use lean techniques and maintain

a steady course. Five lean principles allow the manager to do that which is the precisely

specified value by specific product, identify value stream for each product, make value flow

without interruptions, let the customer pull value from the producer, and pursue perfection have

highlighted. These five principles help the company get a zero-waste, which was the goal for

the TPS. In implementing the visualization towards the manufacturing system, all these five

principles have to follow to ensure that the system focuses on reaching zero waste, thus making

the company leaner.

Moreover, the TPS house diagram has become one of the most recognizable symbols

in modern manufacturing (Liker, 2007). It can be seen down below in Figure 2.1. A visual

management system, which is one of the visualization techniques, has become the house's

foundation to support the two pillars, which is just-in-time and jidoka. It gives visualization

meaning of support system for all the listed system above the foundation level. It can visualize

anything related to the production as fast as possible, whether in standard or deviated, thus

prompting any action that will maintain or revert to standard form. Through a visual, a whole

system in manufacturing can manage to reduce waste to zero.


18

Figure 2.1: Toyota Production System (TPS) House Diagram. (Liker, 2007)

Other than that, the book of Toyota Way stated that the author already understands what

TPS and Toyota Way did to their manufacturing industry. They designed a system to provide

the tools for people to improve their work continually. Toyota Way is an ideology brings by

Toyota that gives a meaning of dependency on people, not less. All the manufacturing systems

depend on the people to maintain and have continuous improvement in each work they are

doing. In the Toyota Way, 14 principles have constituted; one of them is "use visual control,

so no problems are hidden." Taiichi Ohno has quoted that "you must clean up everything so

you can see problems" (Liker, 2007). When looking in-depth, this quote's meaning also gives

the meaning of the use of visual control must be clear, where the location is, who is the target

person, what tools need to take to make it back to standard, etc.

From that, it describes the visualization is not just an image or picture. It always

contains at least a single meaning or any managing or controlling elements to be delivered from

any visual device, resulting in any action from delivered information. This visualization


19

technique has much application in manufacturing organizations to make the company lean. It

also can become one of the continuous improvement techniques because it can be innovating

by following the industry trends. Visualization application in Toyota has been discussed and

results in a significant impact on lean. In the sub-section 2.1.3, the most significant

visualization tools that have improved the lean production of manufacturing were highlighted.

All the visualization tools that have success in the lean production were sorted out, and each

tool's brief details were explained. Then the following section will elaborate more of the

application of the significant visualization tools of the manufacturing industry and other

sectors.

2.1.2. Transparency of Visualization

Transparency is one of the vital functions that was offered by visualization. It means

separating the network information and the hierarchical structure of order giving (Greif and

Hamilton, 1991). Process transparency can be defined as the ability of a production process (or

its parts) to communicate with people (Powell, 2002). Traditionally, the work environment,

control system, and knowledge tend to be centralized since managers are expected to know

more than the operators about the process (Powell, 2002). Transparency facilitates

management-by-sight, which requires an understanding of the workplace at a glance by the

superior (Tezel, Koskela and Tzortzopoulos, 2009). It serves both manager and worker with

the same information as nothing is being hidden in a transparent organization. If process

transparency is successfully implemented, most problems, abnormalities, and types of waste

that exist can be easily recognized. As the most significant example in the manufacturing

industry, Toyota company has implemented the Toyota Production System (TPS) or Lean

Production, where the production style has been changed totally from the mass production era.

In TPS, Taiichi Ohno has mentioned in the seventh Principe, "Use visual control, no problems

are hidden" (Liker, 2007). This statement showing the TPS visualization tools has reduced the

transparency in the Toyota industry's production activity. All the information was recorded into

readable information that can be seen by everyone in the industry.

The organizations that improve their transparency in the industry will radiate the

information and ease access to the desired information. For example, the transparency helps

the decision-making process of the difference level of authority and increment the accessibility

of data for people at lower hierarchical levels, harmonizing well with the central necessities of


20

the hierarchical strengthening practice. Otherwise, the transparency characteristic equipped

with the information-orientated tool, the adaptability, and lean characters helps the modern

organization that has separated with thick walls to communicate.

Transparency has created perfections towards the working environment of the

organization. It simplified the decision-making process for the employees as the information is

ready to access at the fingertip. Transparency has helped the workplace in the improvement

and more prominent decision-making process, the incitement of casual contacts all through

various progressive levels, the commitment towards the presentation of decentralization

arrangements, the help to expand representatives cooperation and the independence in the

executives, progressively successful (covering) circulation of obligations, an expansion in

worker resolve, more adequacy of creation planning, the disentanglement of creation control

frameworks, quick appreciation (by making issues obvious) and reaction to issues (a controlled

speed in dynamic and responsiveness), increment in the inspiration of laborers for development

and permeability of mistakes (Moser and Santos, 2003). In accordance with Grief and

Hamilton, flexibility, versatility, and mobility were also included in work teams when

transparency was into the visualization (Greif and Hamilton, 1991). Precise information will

increase the visibility that assists individuals with building mental models and criticizes their

activities are the fundamentals of UCD (Norman, 1998).

In the book of (Koskela, 2000) summarizes the methods for improving the transparency

in organizations: setting up essential housekeeping to make the working area visible (the

strategy for 5S); making the procedure legitimately noticeable through proper design and

signage; making everything into their standard; rendering imperceptible characteristics of the

procedure obvious through estimation; epitomizing process data in work zones, apparatuses,

holders, materials and data frameworks; using visual controls to empower any individual to

perceive measures and deviations from them quickly; lessening the reliance of creation units.

2.1.3. Visual Management (VM) tools

In the manufacturing industry, there are many types of visualization tools that have

been used. The previous sub-section already mentioned the Toyota Takaoka in Japan that has

been the first company that applied andon boards. Andon boards is an electronic board that

visualizes any data related to the production status. In Toyota Takaoka, andon board was used

to display the target for daily production, the number of cars has been produced for the day,


21

equipment breakdowns, etc. It mentioned that this andon board was visible from every work

station in the plant (James P. Womack, Daniel Roos, 1990). That is the one example of

visualization tools that are used to disseminate information along the visible area.

The visualization tools' main goals were allowing communication, improving safety,

becoming a security device, recognizing law enforcement, human interface, and advertising

(Ortiz and Park, 2011). All these goals have different functionality, but it has the same target:

wanting feedback from a person who interacts with it. Many organizations have indirectly used

the function of visualization to deliver information. All they wanted from a visual device is to

disseminate the information to all of the employees. This sub-section is about to explain in-

depth tools of visualization in the manufacturing industry. It is slightly different from other

organizations because, in the manufacturing industry, visualization tools used to start from the

raw material until the finished products delivered to the customer can cover up the

manufacturing industry's supply chain.

Tezel, Koskela, and Tzortzopoulos already figured out the most functioning visual

management tools from the late 1940s until 2015 and summarized the strategy to implement

the VM tools industry. Table 2.1 listed the conventional VM tools that were reliable to work

with IR 4.0. It also describes the functions with it all characteristic: process transparency,

discipline, continuous improvement, on-the-job training, creating shared ownership, and the

desired image management-by-facts, simplifications, and unification and creating a

boundaryless organization. These conventional VM tools can be an excellent guideline to

innovate new VM tools integrated with current industry technology. It will bring high impacts

to the industry when approaching significant visual tools. It can be saying that most

visualization tools can relate all of the lean production implementations. The innovations can

be easily applied towards developed visual tools. Otherwise, the listed VM tools in the Table

2.1, the emergence of Industry 4.0 technologies has done towards the tools (Tezel and Aziz,

2017). The conclusion can be made towards the visualization where the tools can easily adapt

to the current technology as it promotes continuous improvements.


22

Table 2.1: Conventional visual management tools (Tezel and Aziz, 2017)

VM tools/systems

Brief descriptions Working mechanisms General remarks

Andon system

Audio-visual signalling boards used to take supervisors' attention to a possible or actual disruption (i.e., quality, safety, information need, etc.) in production activity. Those disruptions are often the subjects of continuous improvement efforts.

The location and status of production disruptions (i.e., about to happen or already happened) are generally communicated.

Andon examples in construction are mostly from high-rise building construction sites.

Project production control systems

Production plans and actual production status are visually communicated. There are also state-of-the-art construction production control and coordination boards used to visually link the Last Planner plans to work teams.

Generally, planned and actual production tasks, durations, times, locations, production work units, and production rates, required production flow elements like information, material, and workforce.

In the construction industry, there are both conventional Gantt charts, location-based control systems (i.e., Line of Balance charts), and state of the art visual control systems that link the Last Planner System plans with site tasks.

Internal marketing tools (Posters, slogans etc.)

Visual elements are used to underline desired behaviors, convey a message, affect perceptions, support change initiatives, best practices, etc., similar to a marketing campaign.

Visually rich and attractive slogans, posters, mascots etc.

They were generally used for safety purposes in construction.

Standard operating procedures (SOP)

Instructions are describing the optimum steps to accomplish a work task.

Visualizing standard operating procedures containing information like work sequences, production rates and work-in-progress levels.


23

Visual performance boards

Key performance indicators (KPIs) of work teams and workplace, in general, are shared in special areas that are sometimes called obeya rooms or performance areas for greater coverage

Target versus actual performance figures is shown together. Deviations are highlighted clearly. Ways to mitigate those deviations are discussed and shown to set a base for continuous improvement efforts.

Team meetings are held around those performance boards (or in obeya rooms) to focus and trigger discussions.

5S

A systematic workplace structuring and housekeeping methodology, which refers to an acronym for the "sorting", "setting-in-order", "sweeping", "standardizing" and "sustaining" steps

Visual information of workplace elements (space, machinery, equipment, tools. gadgets, materials, personnel) on "what", "where", "when", "who" and "how many". Visual cleaning instructions, basic health and safety checks and preventive equipment/machinery maintenance checks.

The conventional 5S is hard to sustain due to the highly mobile and dynamic nature of construction sites.


24

Furthermore, Bateman, Phlip, and Warrender have conducted a study about the

development, implementation, and use of visual management tools to improve communication.

The study has proved that using the visual management tools called communication boards has

enabled the engagement between the teams and first-line managers in an attractive way to

discuss and solve a problem (Bateman, Philp and Warrender, 2016). To create an attractive

way of constructing communication boards, they have summarized how to approach visual

management tools, which are a must because it is the characteristics of the visual tools itself

that any visualization system or device must-have. First is from (Greif and Hamilton, 1991),

which has said that when using visual tools provides a shared concept of where the factory is

now, it should be, thus leading to team-based participatory problem-solving and

implementation achieve goals. Otherwise, Grief also reminds of implementing visual tools that

are not overloading, bold and colourful, and use standardized approaches across a site but not

be uniform, thus reflecting differences between areas.

Furthermore, (Jaca et al., 2014) has become one of the famous technical paper for

visualization. This paper provides researchers with 20 visual management elements from 52

companies. Most of the companies have only focused on the "marking on the floor" which is

signage, photos, etc. that was 80% on most companies. The advanced visualization tools such

as "maintenance schedule" or "statistical process control" on average have collected less than

50% of the most company. From this, it can be concluded that visualization application has not

been majoring in most companies. Many innovations can make towards the most of visual

tools. Otherwise, most of the visual tools themselves are adaptable to any changes that we can

see early. It can fit kanban, poka-yoke, andon, etc.

From the in-depth study of VM tools of the previous research, some of the tools have

been found out to solve the visualization problems. The listed tools in Table 2.1 were showing

the significant VM tools from the conventional study, where it got the element that can help

the problem-solving process in this research. There were two tools that most likely to be applied

in the digital user interface, the production control system and visual performance board. These

two were chosen due to its characteristics that visualized the essential data of the production. This

production control system will visualize the informative production data, such as tasks in the

production. Then the visual performance board will give the KPIs of the production activity.

So these two were essential VM tools that need to be in the production cell. It will help the

worker keep track of their works and also their performance. An advanced VM can be formed

towards the management level.


25

2.2 Significance of Visualization in Industry

Visualization tools have brought much easiness towards various types of industries.

The visual devices can indicate something that will make people or anything response towards

the visual device by taking any action from the information disseminated through the visual

device. The visualization technique has been used to reduce muda (waste) in lean production.

In the meantime, the implementation of visualization also an impact on increasing

performance. This improvement led to the high-performance industry because when waste was

eliminated or reduced, proportionally will increase the organization's performance. This section

will show and discuss successful visualization implementation, which will significantly impact

that will lead to the lean industry.

The industry's visual approach has not only focused on performance measurement,

KPIs indicator, production monitoring, etc. Otherwise, it can be more than that. Three case

studies for several aerospace companies have been conducted. These studies were to test and

evaluate the application visual management system that can simplify performance management

and allow communication from a different level (Parry and Turner, 2006). The first case study

was at Rolls Royce. The study wants to improve Enterprise Resource Planning (ERP) by using

visualization techniques. The visualization technique was used to communicate the required

output from the ERP system to the shop floor. This development was given benefits in cost

reduction and increased production rate, thus eliminating waste in shipment to the customer.

After that, the second case study was to manage the complex knowledge-based in the Aircraft

Maintenance Manual (AMM) in Airbus UK. AMM is the system that allowing connection

supply chain, people, and also knowledge-based. In this case study, the visual control boards

have been used to increase the transparency in AMM. Visual control boards enable interaction

for the AMM system and make it more interactive due to the operator's feelings. From that,

they get used to it and interact with the system. The last one is in Weston Aerospace, using the

visualization tools to run the report on work packages, resources, and processes for their

organization. From the successful visualization study, Parry and Turner have been admitted

that the visualization system was a robust system that can become tools in controlling

manufacturing.

The powerful visualization has brought interest in most industry organizations in this

world to compete in the global market. With that, it results in the uncontrolled development of

visual management cases. Performance evaluation of visual management then has been created,


26

which also brought an idea of initiating the strategic development of visual management in

case transfer (Murata and Katayama, 2016). Visual development should be focused on

providing valuable benefits to users. Otherwise, it will be categorized under uncontrolled

development, thus creating more waste in the manufacturing industry.

2.2.1. Application of VM in current manufacturing sectors

In previous sections, the VM application that has been explained was mostly used by

the manufacturing industry to manage and control their daily activities. The functionality for

each application also has been briefly explained throughout the sections. In this sub-section,

the application of VM tools in the current manufacturing sector will be briefly explained. The

steps that have been taken to make it efficient also will be explained in detail.

The first case study that this sub-section up to is the communications boards in a British

lock manufacturing company. The graphic design and cognitive psychology elements have

been explored to bring the design principles into the company's previous informal processes.

Thus with the available design principles, an improved VM tool was developed, enabling team

leaders to better engage in problem-solving and continuous improvement (Bateman, Philp and

Warrender, 2016). With this development, improved and precision communication can be

made in a manufacturing company, thus remove the waste produces when the undelivered

information occurred.

Other than that, the current application of visualization has also been further using the

Internet of Things (IoT) features to improve the visual control system's implementation

process. The visual innovation towards IoT features will be discussed more in the following

section. The IoT is the main element that needs to focus on in this study. As an introduction to

IoT, a case study made at Stellenbosch Technology Centre's Laboratory for Advanced

Manufacturing (STC-LAM) in developing the visual management system for resource

management will briefly be explained. This IoT-based visualization system was used to gather

shop floor data and display it in a dashboard for decision-making processes based on the

information stored in the VM tools. Thus comparison can be made towards the historical trend

(Steenkamp, Hagedorn-Hansen and Oosthuizen, 2017). This approach of visual improvement

towards the manufacturing industry has improved the transparency of the industry. Every

information has easy access from the managers. Continuous improvement can be made towards


27

the industry, thus helping the manufacturing sector industry increase their production

efficiency.

Nevertheless, a three-dimensional (3D) monitoring system has formed with the

advancement of visualization technology. This approach has given production management a

piece of creative information on their production line as the 3D data provides effective data

support. The combination of OpenGL modelling and open database connectivity (ODBC) has

been created in the Microsoft Visual C++ V6.0 platform to create the 3D production monitoring

system. The developed system has improved the production system. This development creates

a client-server model where allows the user to read the processed information of machining

processes for each workpiece in 3D. This 3D monitoring system also provides the simulation

on production capacity to maximize the production activity, thus automatically helping the

industry optimize their production activity (Hu and Li, 2018). A better visual of manufacturing

activities can be achieved. All problems or any opportunities in the production activities are

visualized. Thus, trust can build between the manufacturing and the client, helping the

manufacturing industry's business activities.

2.2.2. The uses of VM in other sectors

This section aims to prove that the VM tools' application was just not focused only on

the manufacturing industry sector. These VM tools were also applied in other organizations as

the definition of the VM itself, showing the managing features that include in the VM tools

itself. In the historical background of VM and correspondingly. VM was written in the

encyclopedia of the history of technology by A.K. Corry around 2500 BC. Corry. It describes

the VM was used in construction projects and other related areas by Egyptian Royal Cubit as

the visual measuring standard. Other than, history of evolution management that written by

Daniel A. Wren in his book "The Evolution of Management Thought" around 600 BC also

mentioning the Chinese General Sun Tzu used gongs, flags, and signal fires for communication

and management of his army (Tezel, Koskela and Tzortzopoulos, 2009).

In the modernization era, VM tools in other sectors have already improved with the

uses of information and communication technologies (ICT) in the management system. The

construction site has used the VM tool to manage the activities in about 62 blocks of apartments

spread over 55 hectares by developing a computerized heijunka system. Forklift work has been

distributed and levelled through tablets to inform operators about supply and clean-up activities


28

that need to be performed at the job site. Implementing the advanced VM tools in the

construction industry results in a reduction of idle machines and work stoppage due to the lack

of material and distance travelled. This computerized system has also improved construction

sites' organization and workers' productivity (Barbosa et al., 2013).

Moreover, the VM tools in the construction sector enable the employees in construction

design to comprehend the design efficiently and commit to both their hierarchical qualities and

client needs. Otherwise, the construction sector designers have also used visual scheduling to

meet the projects and deliverables' schedule. The designers quickly make the decision-making

process with visual scheduling to visualize everything (Tjell and Bosch-sijtsema, 2015).

Last but not least, the VM tools have also been gone further in the healthcare sector.

The VM was used to visualize the health and wellness data holistically. This approach helped

the individual enhance all the client's wellness zone by using the visual interface to record and

communicate on the client's wellness. Beyond that, the relationship between coach and client

is closer with the visual interface uses as it maximizes the communication between them. Along

with that, ease of communication of this visual interface helps the full engagement of the coach

towards the client, as the client wellness data will actively provide to the coach. The

implemented VM system helped the coaches to screen the wellness status of the client and to

distinguish issues that need special consideration and further inspiration to improve client

health. The client also was able to monitor their wellness status through the system (Al-

Musawi, 2015).

2.3. The innovation of VM tools

The visual management system is one of the lean techniques that are easy to evolve as

the trend changes. Bunch of innovation has been made towards the visualization system to

eliminate waste and increase the productivity of workers or systems. Innovation in

manufacturing is the one of strategy for growth in a supply chain by producing a good service

or (Innovation Strategy | Product Innovation Strategy | Strategyn, 1999). To create an effective

visual innovation, the needs of the users must be the main reason for the innovation. Users

always want something that, according to the globalization era because they wanted something

that new and trending.


29

Nevertheless, in most companies, managers usually disagree with what the users need

towards the visualization system (Tezel & Aziz 2017). The manager was usually not able to

see what the users were facing on the shop floor. The manager should give the user's voice out

to know what kind of innovation can be implemented to reduce the gap between user and

manager. The limitation of innovation will stop the continuous improvement of the

visualization system. The use of visualization will be limited due to inefficient productivity

techniques.

Visual management system in lean management initially started by the implementation

of andon lights at Toyota Takaoka, Japan, which using of lights with a different colour to

indicates the processing activity (James P. Womack, Daniel Roos 1990). After that, the

development of visualization has been increasing, and the implementation has been broad.

(Tezel & Aziz 2017) has emerging technology such Internet of Things, Augmented Reality,

context-aware and mobile computing, drones and quadcopters, auto-identification (AutoID)

and laser scanning towards conventional visual management that is for the production and

construction such poka-yokes, kanban, heijunka, andon, etc. (Tezel & Aziz 2017). It has

brought much innovation that is connecting visual management with a digital device. In the era

of industry 4.0 that will be discussed in the next sub-section, visual management already

achieved half of the industrial trend. The communication through visual management becomes

easier, even though it was complex due to emerging many techniques.

Nowadays, people always use their smartphones to view email, read the current issue,

save important things, create an event, etc. All the works mostly rely on the phone. Besides,

people nowadays also love their smartphone because it was powerful enough to do works and

also mobile. Some of the company already start emerging the visual management system to

manage or monitor their production into user's smartphones (Kiritsis, 2016). This kind of

innovation increases the awareness of users because people nowadays use smartphones in

negative ways. For example, users tend to play a game while doing work or something that will

reduce the visual attraction. Through this innovation, it creates more awareness of the

production activity or helps users out of works. Other than that, innovation in the visual

management system looks like no end. It always emerges with many technologies in every

industrial revolution.


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2.3.1. Industry Internet of Things (IIoT) with Visualization

Recently the industrial revolution era has introduced the new Industry 4.0 or better

known as Industry Internet of Things (IIoT). This new term for new modern information

technology where the uses of the internet have enhanced. This fourth industrial revolution

agenda is to emerge the real and virtual worlds into one system called a cyber-physical

production system (Deloitte, 2015). This system will create an online system which easies for

the user to access the real production system through another virtual system using the visual

device. All of the information was on the finger, and communication between concrete walls

become easy with this virtual system. In other words, this new revolution brings better visibility

and insight towards organization operation and assets in the use of modern sensors,

middleware, software, and backend cloud compute and storage system (Alasdair Gilchrist

2016). Visualization easily adapts to the new industry because it has the concept of visibility

and communication that Industry Internet of Things has.

Figure 2.2: The main four characteristics of Industrial Internet of Things (IIoT) (Deloitte 2015)

Figure 2.2 shows the four main characteristics of this new internet industry. The IIoT must

have vertical networking of a smart production system that will be stored and process all the

data of production. Then it followed by horizontal integration via a new generation of global

value chain networks. The global value chain networks depend on the sector that the

organization applied. After that, it through-engineering across the entire value chain, which

means it communicates across the sector applied and then got a response from them. Thus,


31

interaction happened among them and created an exponential technology. This characteristic

then circulates to make the IIoT alive.

The development of Industry Internet of Things to the current manufacturing industry

must be linked to lean production implementation to make the lean more advanced and

implemented system efficient. Mrugalska & Wyrwicka conducted case studies on linking lean

production with IIoT. The case studies were to develop a smart product, smart machine, and

augmented operator. In the case studies, most of the lean techniques that have linked to IIoT

were a visualization technique. It can be said that the visualization system was very adaptive

and match well with the IIoT.

2.3.2. Internet of Things devices

Industry Internet of Things (IIoT) has brought a new system called Cyber-Physical System

(CPS) due to rapid advancement in digital computers and boundless communication among

organizations (Alasdair Gilchrist, 2016). After that, it has made expertise to produce a small

and compact device embedded with a powerful microprocessor to run a system such as a

smartphone, Raspberry Pi, ZigBee, etc. These devices only a single processor and have been

called a single-board processor that can run faster than an old big computer.

A comparison among IoT devices have made towards Raspberry Pi, Arduino,

BeagleBone Black, Phidgets and Udoo in terms of size and cost, power and memory,

flexibility, communication and operating system and programming languages (Maksimović et

al., 2014). This comparison has listed in Table 2.2 below. Otherwise, Raspberry Pi has

admitted for a better prototyping project (Maksimovic and Vujovic, 2015). This suggestion

was allowed researchers to develop IoT system using it. From that, it will make the process of

development easier and more convenient for new researchers.

Smart technologies were many developed in the era of IoT. IIoT allows developers to

create anything in the use of the internet, making an environmentally smart by using the IoT

devices for the prototyping, thus lead towards more significant development. Table 2.3 shows

the research that has used the Raspberry Pi to make a smart production system. It has proven

that Raspberry Pi has a significant function. Most of the implemented system that is focusing

on IoT platform has been a success and only has a little limitation on it. It is not just to work

only with the manufacturing sector, but with other sectors also. In developing the prototyping


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or implementing the smart system with integration of IoT, Raspberry Pi can be used for

controlling, processing, collecting information, data storage, etc. This innovation helps IoT

practitioners to implement a better smart manufacturing system.

Many researchers also using the Raspberry Pi to adapt the IIoT. In visualizing the

beneficial data towards end-user by creating multiple digital visualization GUI with a different

characteristic for a different level (Snatkin et al., 2015). This implementation helped the

dissemination of information towards the correct employer. In this case, if the data for ERP or

OEE towards the production operator that has low knowledge in production, this will create

waste. For Malaysia, most of the production operator still operated by a foreign worker that

has a limited understanding of certain language. This language barrier creates a waste where

vital people cannot use the system. Other than that, to improve the developed GUI has

evaluated the GUI to find out how to improve the GUI (Ragnarsson et al., 2017). The end-user

has tested the GUI the, giving on response about it. From that, a friendly GUI that is informative

and beneficial will be formed to support the visualization in IoT.


33

Table 2.2: Comparison of Raspberry Pi's performance with a similar prototype platform (Maksimovic and Vujovic, 2015)


34

Table 2.3: Integrated VM Tools with IoT.

Integrated System IoT involvement (Raspberry Pi) Outcomes Limitation Author Future work

Production monitoring system - Visual module development in monitoring production:

• Manufacturing Execution System (MES)

Raspberry Pi and Arduino

• Arduino controller as the data collector

• Uses of SQL server for cloud computing

They are developing three different views of GUI according to a different type of end-user to deliver complex data most simply.

Since prognostic accuracy is subject to a stochastic process that has not yet occurred, it is difficult to formulate a clear systematic methodology for an effective prognostic methodology for industrial applications

(Snatkin et al., 2015)

Advanced data analysis and prognostics methods should be researched, implemented, and tested to enhance

proposed PMS for SMEs.

Smart Environmental Monitoring - Visualize surrounding environment by using sensors and uploads it directly to the internet, where it can be accessed anytime and anywhere through internet.

Raspberry Pi with GPIO pins connected towards IoT sensors

• Xively - enable businesses to connect products and operations to the Internet and visualized quickly.

It provides weather monitoring services for remote areas and able to automatically upload to the internet. It can be used to predict the onset of bad weather using signs such as changing temperature and humidity.

Sensor failure and also it just an ad hoc applications that are usually not available for larger monitoring area.

(Mohannad Ibrahim, Abdelghafor Elgamri, Sharief Babiker, 2015)

For a larger monitoring area, it has to deal with governments and big agencies that can allow the system to broadly operate


35

Home Automation – monitoring and determining the confidence of fire in the building.

• Individual control devices, • Distributed-control

systems and • Centrally controlled

systems.

Raspberry Pi

• Sensor connected to GPIO

• Driver for sensor • RESTful service

• Home alarm system project,

• Temperature sensor project,

• Webcam Surveillance project,

• Siren project.

Only can monitor small area which is the area located near to sensor.

(Maksimovic and Vujovic, 2015)

• usage to outdoor • expanded with

GSM/GPRS module • independent • power supply


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2.4. VM system evaluation tools

In order to allow ease of use of visualization tools, the user-centered design (UCD) method has

been introduced. The UCD credibility was studied in this section for innovating this research

new visualization system and followed by usability evaluation to see how satisfied users with

the developed system. The following sub-sections will be explained in detail on the literature

study of UCD method and the usability test that has done by other researchers.

2.4.1. User-centered design (UCD)

User-centered design (UCD) is a process of designing with the end-user. There is no such way

to specifically defined UCD because numerous points of view can characterize it. However, all

the definitions are characterized by focusing on the user’s perspective in developing something

(Devi, Sen and Hemachandran, 2012). Based on Donald Norman, it describes UCD as “a

philosophy based on the user's needs and interests, with an emphasis on making products usable

and understandable” (Norman, 2013). However, users' involvement in the User-Centered

Design process is a common way of ensuring that their needs and interests are being met (Devi,

Sen and Hemachandran, 2012).

Somehow, even though there are many UCD definitions, a specific guideline needs to

be focused on applying the UCD methods towards their study. ISO 13407 standard has outlined

four critical human-centered design activities: requirements gathering, requirements

specification, design, and evaluation. The UCD process has also been formalized in ISO-

standard 13407 Human-centered design processes for an interactive system (ISO

13407:1999(en), Human-centred design processes for interactive systems, 1999). Figure 3.1

visualizes the iterative process of UCD. In applying the standard, some fundamental principles

need to follow:

1. The active involvement of users and a clear understanding of user and task

requirements

2. An appropriate allocation of function between user and system,

3. Iteration of design solutions, and

4. Multi-disciplinary design teams.


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Understand and specify the context of use

Plan the human-centered process

Produce design solutions

Evaluate design against requirements

Specify the user and organization requirements

System meets requirements?

Figure 2.3. The human-centered design process, ISO-13407

The four activities in Figure 2.3 can be elaborated as follows:

• Understanding and specify the context of use: This activity includes the first place of

this cycle as it helps the study understand the users' knowledge and the environment of

the proposed system.

• Specify the user and organization requirements: With the users and organization

requirements, it clarifies the needs of the users and organization towards the system and

makes users satisfied with the system.

• Produce design solutions: Create or sketches a rough design of the proposed system

based on the information given by users and organizations to visualize how the system

will interact with them. This step could be done by providing a prototype of the system

or actual implementation.

• Evaluate design against requirements: This final step was to test the system. Whether

it has already followed the user spec or still need to do a cycle human-centered for the

system to meet the user requirements. In this step also is where the assessment or

usability test takes place.

In order to make the users active part of each step in this process. There are a variety of methods

that are being used in the UCD approach. Each step has different tools. The methods chosen

depended on the information that needs to be collected by the researcher. There are twelve

methods of UCD that have been recorded. Table 2.3 explains the description and guidance of


38

the researcher's selection method to decide the best method for their study. In the functional

dependency, if there are tools needed for the selected method, it will explain the tools. If it

requires designer skills or experts, it will describe the correct way of assessing the methods.

Table 2.4: UCD methods and application area (Devi, Sen and Hemachandran, 2012)

UCD

Methods

No. of

stakeholders

involved

Functional Dependency Application area

Card Sorting 10-20 users

Tool Support: The tool support is

available based on the method.

Stakeholder efforts are combined and

analysed statistically through IBM’S

EZ, which is used as a tool that helps

analyse the stakeholder activity. This

tool comprises two packages that are U-

sort and EZ Calc. U-Sort is used by card

sorting Participants to sort virtual cards,

or the designer can input after the

physical card activity has been done.

designing a new

site designing a

new area of a site

redesigning a site

Contextual

method.

Contextual

Enquiry

Varies (few-

many)

Designer/Expert skill: No primary tool

support is available based on the

method. Context-based enquiries are

framed, and qualitative analysis is of the

collected data is done by the designer. It

is carried out mostly at the user’s

workplace.

Qualitative data-

gathering and data

analysis (adapted

in the fields of

Psychology,

Anthropology, and

Sociology)

Focus Group

6-12

users/groups

Designer Skill: Targeted stakeholder is

invited to a session of discussion. The

designers/facilitators manage the

discussion skilfully to stay in topic.

Academic

research, Product

marketing,

Evaluation


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research, Quality

improvement

Interview Varies (few-

many)

Designer/Expert skill: Interviewer asks

semi-structured questions either face-to-

face or by telephone. Those interviewed

may include stakeholders, content

experts, support staff, and users

themselves. Both parties may choose to

view a system online during part of the

interview.

In-depth data

about a particular

role or set of tasks

were obtained.

They were finding

out what users

want.

Log File

Analysis

None

Tool Support: User’s actions with a

system are collected from server logs

and examined later for usage patterns

and potential problem areas.

To track site usage

(it allows a web

administrator to

track file use and

server traffic)

Paper

Prototyping

5-7

users/groups

Tool Support: The tool support is

available based on the method. More

recently, digital paper prototyping has

been advocated by companies like

Pidoco due to advantages in terms of

collaboration, flexibility and cost. It is

throwaway prototyping and involves

creating rough, even-hand sketched,

drawings of an interface to use as

prototypes, or models, of a design.

Communication in

the Team,

Usability Testing,

Design Testing,

Information

Architecture Rapid

Prototyping,

Survey

Varies Designer/Expert skill: Users are asked

a standard set of questions on paper, in

person, by telephone, or by electronic

mail.

To obtain

quantitative data

from users about

existing tasks or

the current system.


40

Task

Analysis

At least 5

users/groups

Designer/Expert skill: It is to learn

about an existing website to analyse the

essential rationale. The analysis will

involve the purpose of what people are

doing, what they are trying to archive,

why they are trying to archive it and

how they are going about it. The data

abstracted helps to build new

requirements or to design new tasks.

It is suitable and

recommended for

most situations

Usability

Test

5-12 users Designer/Expert skill: Testing is

usually carried out on a one-to-one basis

to allow the facilitator to observe the

user's behaviour closely. A second

facilitator may be useful for recording

purposes. The key to interpreting the

results of testing is to look for general

trends and behaviour patterns that

indicate problems with the usability of

the site.

Provides

recommendations

for how a design

can be improved.

Eye-tracking,

teaching method,

coaching method,

self-reporting

Logs

Expert

review

3-5 Designer/Expert skill: After

examining the system, Design experts

give a comment in detail on its

adherence to principles of good design

based on their expertise. Multiple

experts are recommended to increase

the probability that they will identify the

main problems.

To identify

usability

problems in a

product or service

Guided

Walkthrough

1-4 users Designer/Expert skill: Facilitator leads

a user through a representation of the

system asking questions either during or

after the walkthrough to gauge the

user’s understanding of the system.

Checks structure

and flow against

user goals


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2.4.2. Usability evaluation

A usability test is a systematical process of collecting the usability data of an interface for

improvement purposes. Same as the User-centered design, there is a lot of points of view about

the definition of usability. The earliest definitions of formative usability came from Chapanis

and his student. They describe usability as follows:

“Although it is not easy to measure ‘ease of use,’ it is easy to measure the difficulties that

people have in using something. Difficulties and errors can be identified, classified, counted,

and measured. So my premise is that ease of use is inversely proportional to the number and

severity of difficulties people have in using the software. There are, of course, other measures

that have been used to assess ease of use, but I think the weight of the evidence will support the

conclusion that these other dependent measures are correlated with the number and severity

of difficulties”. (Lewis, 2014)

It clearly describes that usability is used to measure the difficulties (error) in a product to make

it useful to the user.

Heuristic

Evaluation

3-5 users

Designer/Expert skill: A group of

evaluators (HCI experience)

systematically apply a set of user-

centered heuristics in order to evaluate

the system. Multiple experts are

recommended to increase the

probability that they will identify the

main problems.

Websites, e-

learning system,

groupware,

notification

system, and

games.

The method will

provide

recommendations

for design

improvements.


42

Usability has an international standard definition in ISO 9241 part 11. It defines

usability as the extent to which specified users can use a product. It used to achieve specified

goals with effectiveness, efficiency, and satisfaction in a specified context of use (ISO 9241-

11:2018(en), Ergonomics of human-system interaction — Part 11: Usability: Definitions and

concepts, 2018). Definitions provided can be derived from the usability concept. It used to

understanding and measuring the product's boundaries against a lot of predefined objectives

based on the user perspective, the context of use and purposes. From that, the researcher can

minimize the gap between the parameters and apply ease of use towards the products.

In measuring the parameters to close the gap, there is some specific method of usability

testing that has been specializing for a different type of approach. This section has selected

several usability testing methods suited to the delimitation of this research. The usability

method that was going to be explored are as follow:

• Heuristic evaluation: An inspection will be done towards the user interface (UI) to

identify the usability problems in a glance, which are not necessarily found in user

testing. Experts and non-experts can do this. The more experts take place, and more

problems can be found. Normally, around 3 to 5 of usability experts are required to

undergo this method on their knowledge of human cognition and interface design rules

of thumb or heuristics (Ghasemifard et al., 2015).

• User-based testing method: this method allows the user to explore and use the system

with several tasks. While exploring and operating the system, the user will be observed

by the investigator to record any issues arising from the test. Beyond that, the required

time on task completion or task completion rates or some errors will be recorded by the

investigator for data analysis. When system imperfections have been recognized,

suggestions on improvement are proposed to make the ergonomic nature of the item

become better. In operating the user-based testing method, there is a suggested step in-

order to conduct the test (Bastien, 2008):

• The meaning of the test objectives,

• The capability and enlistment of tests members,

• The determination of undertakings members should figure it out,

• The creation and depiction of the undertaking situations,

• The decision of the measures that will be made just as how the information will

be recorded,


43

• The planning of the test materials and the test condition (the convenience

research facility),

• The decision of the analyser, and the structure of the test convention essentially

(directions, plan convention, and so on.),

• The structure or potentially the determination of fulfilment surveys, the

information examinations strategies,

• The introduction and correspondence of the test outcomes.

The researcher must fulfil the steps listed above to do this method. If the

requirement does not acquire by the researcher, it will not help the advancement process

of the system could not be achieved. The subjects that will be tended to were the number

of members one needs to select for: leading a client test, the test technique, directing

client test remotely, the devices accessible and expected to lead ease of use tests, and

the assessment of versatile applications.

• Standardized usability questionnaire: A questionnaire is a form designed to obtain

information from respondents. The items in a questionnaire can be open-ended

questions but are more typically multiple-choice, with respondents selecting from a set

of alternatives. A self-reported data will be gathers on identified tasks for this method.

The questionnaires measure the user experience and help identify the usability problems

on the created system which need to be improved. These standardize questionnaires

normally measure parameters such as user satisfaction, effectiveness, usefulness, ease

of use, and interface quality. For this research, the chosen standardize questionnaire is

Post-Study System Usability Questionnaire (PSSUQ). This questionnaire designed

to assess the user’s satisfaction with the computer system. The origin of PSSUQ was

an internal IBM project called System Usability MetricS (SUMS). As for now, PSSUQ

has three versions of the standardized questionnaire. This research was using the latest

version of PSSUQ, which PSSUQ Version 3 that has a total of 16 questions. PSSUQ

items produce four scores – one overall, and three subscales (Sauro and Lewis, 2012).

o Overall: Average the response for items 1 through 16 (all the items)

o System Quality (SysQual): Average items 1 through 6

o Information Quality (InfoQual): Average items 7 through 12

o Interface Quality (IntQual): Average items 13 through 15


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The overall PSSUQ coefficient alpha is reflecting the reliability of the system was 0.94.

Furthermore, for the SysQual, InfoQual, and IntQual is 0.9, 0.91, and 0.83, respectively.

2.5. Discussion on Literature Review

Visual Management (VM) system have been advancing in past decades. Different approaches

are made not only to improve the transparency of the system itself but also to improve the

production performance as the demands in the global customers were indefinitely increased. In

this section, the challenges of implementing the perfect visualization tools with the emergence

of IR 4.0 technologies into Autokeen production activities will be discussed.

Initially, the literature study has been done towards the mieruka (visualization) as it one

of the technique in Lean Production system that promoting transparency into an organization.

Then, it followed with the Visual Management (VM) tools that have been shortlisted as the

most significant visualization in this era. From that, the picture of improving the visualization

tools in Autokeen to promote transparency has been depicted. The VM tools in the literature

study have been promoting much transparency to make the organization managed well. The

literature study of visualization has been compared with the conventional visualization tools in

Autokeen to generate something that was going to useful for the Autokeen production activity.

After that, a literature study went through the significance of VM in the current

manufacturing industry and other sectors. This focus was conduct to understand how the

application of VM can help the organization figuring the problem that they are facing before

the implementation of VM. With the brief explanation of other sectors that uses VM, this

literature study provides a clear purpose for the implementation of the new VM tools in

Autokeen. The new implemented VM system need to plan their production activity with the

VM system visually, where the main focus was to works as the production control system for

Autokeen. In this situation, the VM implementation also needed to follow the new trend of IR

4.0, where distinction process of system implementation needs to be carried out by the

researcher. With that, it results in the researcher was chosen the devices generated in the IoT

era with the concept of IR 4.0, where sensors were used to collect data. The user interface (UI)

will represent the collected data as it processed the visual image of the VM system.

In completing the implementation process, the literature study of the system evaluation

processes has done to figure out the best way of system development. The suggested evaluation


45

process of previous research has compared to distinguish what is the most suitable evaluation

process for the developed VM tools. Thus, a reliable evaluation process can be conducted to

get the feedbacks user from Autokeen to fulfil the criteria of this research.

2.6. Summary

In this chapter, the researcher has done the literature study on the mieruka or visualization,

where it briefly explained the definition of mieruka. This word comes from a Japanese word

that gives the meaning of visualization or in-depth visual control that can see. The other

definition of the visualization also was explained. Where it shows the visualization promoting

the capability of the visual device to interpret any action with robust circumstances, this action

then followed with the evaluation processes of the deviated state. Then, further actions will

appear to correct the mistakes in the process until they perfect.

Furthermore, the historical study of visualization has conducted towards the lean

production system. This study shows where the uses of visualization start to developed in the

Japan manufacturing industry. Then the study followed to elaborate more on the transparency

of visualization. The transparency has helped much organization by promoting the ease of

communication. After that, a literature study towards the various significance of visualization

in a different type of industry. The application of current visualization system in manufacturing

and other sectors such as healthcare and construction in managing and controlling the

businesses. In the meantime, the researcher also figures out the reliable visual management

(VM) tools after the modernization era to distinguish the non-functional VM tools from the

study. Besides, the literature study has gone through towards the innovated VM tools, where it

shows the engagement of VM with IR 4.0 as this study was focusing on the IR 4.0 approach.

Later by this chapter, the literature study was conducted in how accessing the evaluation study

towards developed visualization tools that consist of Internet of Things (IoT) features. A UCD

method was introduced towards this study by explaining the steps have done by the researcher

to get a UCD approach done. Last but not least, the usability test has also described the methods

on how to access the user satisfaction and system usefulness when implementing the

visualization system.

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CHAPTER 3

Research Method

This chapter will briefly explain the development process of the Digital Visual Management

System (DVMS). In chapter 1, the researcher has mentioned the DVMS as the smart

visualization system that is going to manage and control the production processes. In the

creation of the DVMS, few processes need to be taken iteratively on designing and

implementing the system. The iterative process of the development will be explained stage-by-

stage. The details of the methods taken for each process were going to describe in this chapter.

Otherwise, the DVMS architecture described in details, from scratch into the final product,

including all stages. Every stage of constructions the DVMS was followed by an evaluation

study. The evaluation processes were going to specify in this chapter, where the data collection

processes were introduced into stages.

3.1 The iterative process of DVMS development

The main study objective is to implement an interactive VM system with the emergence of IoT

features called DVMS. In the development process of DVMS, multiple processes need to be

taken, which lead to different objectives. With that, a bunch of different steps has taken to

achieve those objectives. In order to do so, the researcher has decided to divide the process into

several phases. All the processes have classified with the different objectives that need to be

achieved in a different phase. In chapter 1, the cross-functional flowchart has depicted the

phases that his study had as the following: an initial phase, prototyping phase and an

implementation phase that every phase. Each phase has explained the tests taken to make sure

it is suited to the study.

CHAPTER 3: RESEARCH METHOD

47

The initial phase was to get to know the concept of mieruka or VM as a part of the lean

production system. With the first approach, it strengthened the knowledge of mieruka towards

the researcher, thus allowing the researcher to distinguish the useful VM tools for the Autokeen

industry. The investigation process was to figure out the digitization of VM on the proposed of

DVMS. The proposed DVMS was used to deliver a bunch of information interactively, which

aimed to reduce the transparency of the Autokeen organization. The theories of the

visualization also have been highlighted throughout the initial phase. As this research also is

an industrial-based problem research, the initial phase contained interviews with the industry

partner. This visit was to collect user requirements from the industry and proceed with the user-

centered design (UCD) approach for designing the DVMS. From that, the initial draft of DVMS

has formed. The draft then used to develop the mockup user interface (UI) from the scratch and

counting device that are going to based on the Raspberry Pi. After the development process has

completed, it has shown towards the stakeholders to judge the rough idea of the researcher

before going to prototype the UI. With that, it results in the changes the ideas of the UI and

counting device. These changes have brought the DVMS into the next UCD cycle that will be

in the second phase of this research study.

In the prototyping phase, the development of DVMS has continued with the second

UCD cycle attempt. The judgment of stakeholders has become the requirements in the UCD

process. The researcher has enhanced the counting process and the UI of the DVMS. The

DVMS was running over the Raspberry Pi 3 (RPi-3) and tested in the lab before it the

evaluation process takes place. After several testing has done towards the second phase of

DVMS development, it has brought over the Autokeen. At this moment, the DVMS is ready to

be evaluated by the users in Autokeen. The reliability of the RPi-3 was tested and feedbacks

from the users have gained. From the evaluation processes, the DVMS UI found out was still

lack of information. It has not met up some requirements from Autokeen. Third UCD cycle

needs to done to satisfy Autokeen.

Finally, the implemented evaluation study has resulted in this implementation phase.

The unsolved requirements have led to the third UCD cycle, where the DVMS need two

different UI for managing and controlling the production activity. The functional features in

the previous DVMS UI need to be separated. All the other features were polished before it

being prepared for the next evaluation processes. The RPi-3 was replaced with RPi-4 for more

performance. All the apparatus of the DVMS was prepared and run multiple times to make it

ready for the second evaluation study. After all, the prototype phase appeared to match up all


48

the things to meet the real-time production situation in the Autokeen. The real situation on

production processes of Autokeen was visualized through the DVMS as the evaluation

processes were in analysing.

3.2 Data collection

The process of data collection done in Autokeen was used to support the design method of

UCD and the process of evaluation. The collected data was divided into two types:

• Primary data: The primary data has collected, all by ourselves, through observations

and interviews. Primary data has been collected specifically for this thesis. Thus these

data are niche targeting and useful.

• Secondary data: The secondary data has already been collected by others before. In

this thesis, literature and company information were belonging to secondary data. In

order to have a clear understanding of the theory, the relevant literature has studied.

3.2.1 Observation

Observation can be done in either a direct or indirect way. The direct observation means the

researcher collects data by themselves, through their visit and observations in the real

environment of studied phenomena. Indirect observation means using the secondary data which

are collected by others, either open or hidden (Designing an Observation Study, no date).

During the visit to the Autokeen, direct observation was used to observe their production

process. The researcher visited the production line of the Autokeen, collected all information

regarding the production activities and the visualization tools that were applied towards

Autokeen. Those data helped this research to depict the process flow of Autokeen and generate

then generated a DVMS where it promotes the visual planning for the Autokeen to manage

their production activities.

3.2.2 Interviews

Before doing formal interviews, the researchers need to prepare adequately in order to obtain

enough information which is wanted to get from questions. It is necessary to understand the

background and present situation of the selected company. This method mostly was done to


49

get the requirements of the users towards the DVMS. The interview data is very precious

towards this research as the developed system was based on the user's needs. The interview

process was done from the beginning of the study until the final evaluation process towards the

developed DVMS. Those data help the researcher to improve the system every time after the

interview has done.

3.3 Proposed DVMS architecture

Production levelManagement level

DVMS

Figure 3.1: Proposed Digital Visual Management System (DVMS) architecture.

Figure 3.1 shows the proposed DVMS architecture, where the implementation of DVMS

begun. In this section, the researcher will explain all the concepts that being approach and used

in developing the DVMS. All the concepts and design related to DVMS were explained stage

by stage in the following sub-sections. The study had the following phases: an initial phase,

prototyping phase and an implementation phase which every phase. Each phase will come out

with several tests to make sure its suite with the study.

3.3.1 Initial phase

The initial phase involves distinguishing process of visualization in Autokeen and current

manufacturing industry and also other sectors. This process is where Autokeen’s VM tools

were compared with IR 4.0 innovated VM. A rough idea was formed and followed by

collecting the user requirements to start approaching the UCD method. This approach will help

the researcher gain the understanding of the interaction of the user with the designed UI. With

that, it results with a rough idea which to provide the focused cell with a digital visual device.


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This device used to keep updating the operator on the production performance while visualizing

back the production data to management. The database for the system also will be using an

open-source data relational database management that will allow the system to communicate

with data.

From that, a decision to prototyping IoT devices such as Raspberry Pi has made. The

decision then followed by the specific test to check the device reliability. As this study relates

to counting productivity, video recording counting technique has been chosen. This technique

will be working using a computer vision technology which is OpenCV. The video recording

approach on counting device was proposed because it will not affect any process in the

production line while doing the counting. Thus, this counted data then need to be transferred

to a database name MySQL. This database was a SQL database that is an open-source and

many IoT researcher has used this MySQL to create the integrated VM tools. This database

then will communicate with the user interface (UI) system that was going to be developed in

the prototyping phase.

Figure 3.2: Camera counting system

An object counter system was programmed using Python language that integrates with

computer vision technology (OpenCV). Figure 3.2 shows the working principle of the counting

system. The blue line represents the "enter-line", and the red line represents the "exit-line".

When the object recorded in the camera frame, it will form a centroid. After that, if the object

centroid passes through the red or blue line, it will be intersected then the system will count

every each intersected they have made. From that, this research use the blue line is for goods


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to enter, and the red is for scraps to enter. Then this counted data will transfer to the MySQL

database.

Next process is to visualize the data that have been collected. Then, the mockup user

interface (UI) need to be produced to become the tools for visualization. In Chapter 2, this

research has discussed more the visual performance boards and also a production control

system. In designing the mockup UI, Snatkin ideas have become this research example on how

to create a GUI. They have created three types of UI for a different level (Snatkin et al., 2015).

A guideline was given on how to create a UI with reference of theory from Fitts and Hick law.

(Fitts, 1992)(Hick, 2008). Other than that, high user involvement also has become one of the

factors in developing this UI as the researcher used the user-centered design (UCD) approach

to creates this design. The UI for this initial phase was to show how the product counting and

also visualized the individual performance regarding their production. From that, it will

visualize an emoji that will motivate the operator to work hard on the progress. The image of

the first design concept will be shown later in the section” Visualization Dashboard for

proposed DVMS”. The processed was then go through actively in UCD where in the cycle

which users have to evaluate the design system as the given requirements. Survey then done to

this fourth step of UCD and results was bringing forward to the prototyping phase.

3.3.2 Prototyping phase

Next is the prototype part. This prototyping phase is to continue the first UCD cycle results

from the initial phase. It started with analysing the evaluation data of the first UCD cycle, where

it includes the judgement from stakeholders. The first thing that researcher did at the beginning

of this phase was researching the most suitable counting system for DVMS. The second attempt

of the UCD cycle has carried out by doing the first two step of the UCD. The environment in

Autokeen was studied by look through the production processes at the studied area. The studied

area, which is Line D or WSS Line, was using the proximity sensors to count the product. This

counter system is to control the nut feeding system, as mentioned in Chapter 1. Then, it seems

the knowledge of the operator has matured in using the proximity sensor. After that, from the

given requirements from the first UCD cycle, the researcher has produced a new idea of

counting method by using a proximity sensor that connected towards Raspberry Pi. This

method will be elaborated further in the DVMS architecture section, where the details on how

the process will explain in details.


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Other than that, two different user interface (UI) has developed for practical visual

management (VM) tools as the different interface can allow the separation of visual

information, where it does not waste the area in the UI for unbeneficial information of the

different environment. This system architecture depicted in Figure 3.3, where each

environment was provided with different DVMS UI. The DVMS Management UI was used to

manage and revised the production activity. In contrast, the DVMS Operation UI used to

control the production activity on the production floor. The management floor was visualized

the Management UI using a pc or laptop to display. At the same time, Raspberry Pi (RPi) was

provided with its touchscreen display to visualize the DVMS Operation UI was equipped with

Raspberry Pi (RPi) that has the own display to display the UI to the production operator. This

RPi then was connected to a proximity sensor where it functions as the data collector for this

DVMS system. Then, both environments were connected through the same wireless network

where the database was located in the RPi, allowing both UI to communicate. The designed UI

for this phase will be explained in details, where every functionality of the DVMS will be

described and depicted.

C

VVisual Screen

Counter sensor

System Controller

Management PC/Laptop

Wireless Router

Figure 3.3: Prototyping phase DVMS architecture.

3.3.3 Implementation phase

In this implementation phase, the system architecture has slightly different from the

prototyping phase. It covered up to three different cells in Autokeen to allow the managing

element from the DVMS to be more effective. This system architecture depicted in Figure 3.4

has similarity as Figure 3.3. The architecture also contains another environment called

"database environment", where it stores most of the data that belong to the management and


53

production environment. The designed UI for this phase was altered according to the results

from evaluation processes that researcher has undergone. The functionality of the newly

designed UI for this phase will be explained later in this chapter.

Management PC/Laptop

Wireless RouterServer

Counter sensor

System Controller

C

VVisual Screen

Counter sensor

System Controller

C

VVisual Screen

Counter sensor

System Controller

C

VVisual Screen

Cell 2 Cell 3Cell 1

Figure 3.4: Implementation phase DVMS architecture.

3.4 Problems faced

The problems used to appear in every phase of the research process. The list below describes

the problems that researcher facing while constructing the DVMS in the iterative study:

• Initial phase:

o The counting method uses the OpenCV, where the video recording will capture

an image entering the specified region. After that, the centroid of the object will

be defined. Then, the system will count the centroid of the object entering the

specified region. This method was not relevant as the camera counting process

will consume much time in developing it. Besides, the Autokeen production

environment was not suitable for camera counting technology since the light

intensity has not enough to capture precision data.

o The designed user interface (UI) should not be combined in both environments

(production and management) as both environments have different niches.


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o The designed UI seems not interested and will not affect the user sensory. Thus,

the implementation created more waste.

• Prototyping phase:

o The features that are promoted in the management interface do not have much

to manage the production activities in Autokeen. Also, the OEE displayed over

the management UI does not match the Autokeen production system, causing

unsuccessful implementations.

o The MySQL database location was located in the Raspberry Pi (RPi) where it

used to display the operation UI of DVMS. This approach will affect the

performance of RPi and crash the systems.

o The application of the DVMS towards only one cell in Autokeen will affect the

evaluation process. Only a single user only was assigned to the single cell,

according to real-time production activity.

• Implementation phase:

o The real-time interaction of both DVMS UI causes a lot of memory usage

towards both UI. DVMS UI will crash, and the system controller will hang

when the UI has already uptake all the memory for the system.

In order to encounter the problems facing data collection processes, some objectives have been

figured out. Below are the listed objectives for the current solution:

• To find a suitable counting system that can collaborate with DVMS UI as Autokeen does

not provide any digital data regarding the product counting.

• To figure out the most suitable visual elements for Autokeen as it promotes the ease of

communications.

• To allow the system smoothness as the elements need to fulfill user satisfaction from the

usability test.

3.5 Concept of DVMS

The reasoning behind developing the DVMS is to strategize the production activity to

demonstrate the real-time tasks, progress, and results, or errors, in the production operation of

Autokeen. DVMS gives a platform where different levels can communicate through an


55

interface about the production activities. This feature is meant to help the management team

structure the daily production plan, monitor the production activity, manage operation progress,

reduce cycle time for production, and communicate with the production floor. Simultaneously,

it also helps the operators understand the tasks and monitor their performance to improve or

maintain production performance. DVMS contains two different interfaces. These interfaces

contain different visual images containing information to be delivered to a different level.

3.6 DVMS overview

Production level

Databases

Management level

Operation interface of DVMS

Management interface of DVMS

Figure 3.5: Digital Visual Management System (DVMS) overview.

Figure 3.5 shows the Digital Visual Management System (DVMS) overview that

connects the management level with production level through a different interface where the

data is transmitted through a SQL database. It also illustrated that the user in the management

level has access towards the management interface of DVMS and also direct access towards

SQL database. Meanwhile, the user in the production level is allowed to access the operation

interface of DVMS. The interface for each level has its own functionality based on their

workload. These interfaces were interconnecting through a SQL database to transmit data from

each level. Later the data will be accessible by the user in each level that has been simplified

based on the user needs. As for the management level, the interface will allow the user to

manage the production activity in the area where the DVMS covered. Meanwhile, the DVMS

interface for operation team controlled the user in the production level to maintain the good

production performance in the production floor. This approach helps the information to travel

along the concrete wall, thus allowing the ease of communication in the organization.


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3.7 DVMS requirements

The requirements for the DVMS are the configuration that must have by DVMS before it being

tested. The requirements have been divided into functional and non-functional requirements.

The functional requirements are functions that DVMS will send directly respond to the user.

In contrast, the non-functional requirements are the performance characteristic that has in the

DVMS which the user does not interact with directly, such as usability, efficiency, reliability,

etc.

The functional requirements of DVMS will divide into two, operation interface and

management interface. For the management interface, the functional requirements are:

• DVMS shall store the operator’s identification and parts identifications.

• DVMS shall store the production history and machine monitoring data from the

previous production.

• DVMS shall visualize the real-time production activity data on the assigned production

line. Include the status of the cell, productivity, number of defects, and remaining time

on specific production tasks.

• DVMS shall calculate and visualize the overall efficiency and number of defects item

in the real-time production situation.

• DVMS shall the show the reports coming from operation interface is there is breakdown

happen in any cell.

• DVMS shall automatically transfer all the desire action into the database; thus, the

information delivers to another interface for operation.

Meanwhile, the functional requirements for the operator interface are:

• DVMS shall show the name of the user that has assigned to the specific cell.

• DVMS shall show the list of tasks that need to completed by the user.

• DVMS shall interactively update the task completion rates according to the number of

finished tasks.


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• DVMS shall show the standard operation procedure (SOP) for the selected task.

• DVMS shall allow the user to start production when the user has chosen and studied

the specific task from the list of tasks.

• DVMS shall interactively display the emoji according to the user’s productivity.

• DVMS shall start or pause the countdown whenever the user chooses to start or pause

the production.

• DVMS shall show the desire action taken by the user during the production activity.

(e.g. Break time, operator going to the toilet, etc.)

• DVMS shall update the database according to the number of product produced.

• DVMS shall interactively display the gauge according to the production data.

In respect of the non-functional requirements in the DVMS, the aim was towards the system

usability as it requires the users to work with it. The usability requirement involves measuring

parameters such as the usefulness and likability of DVMS, simplicity and ease of use, and

quality of the information and the interface. These boundaries cannot be executed legitimately

but instead estimated after usage.

3.8 DVMS architecture

MySQL Connector

Management level

Management PC/LaptopSensorRPi-4B

Operator

RPi-3B+

DatabaseMySQL Connector

Management Environment Database EnvironmentProduction Environment

Figure 3.6: Digital Visual Management System (DVMS) architecture.


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Figure 3.6 shows a DVMS architecture that was connected through the same wireless local

area network (WLAN). The DVMS architecture containing three different environments that

are inter-connecting to each other under the same network. Among them are the management

environment, database environment, and production environment. In the management

environment, Figure 3.6 shows the Management UI was based on the PC or laptop. While, in

the production environment, it shows the user was visualized with a touchscreen display. It was

connected to the system controller called Raspberry Pi 4 Model B (RPi-4B) to operate the

interface. The system controller also was connected to the proximity sensor for collecting the

produced data from the operator. The management and production environment display

different DVMS UI. However, both of it was using the Python application called Tkinter to

visualize the information that allowing these two different interfaces communicating with each

other through the use of DVMS. In order to communicate, both interfaces were retrieving

database's data through the MySQL connector. It converts the Python programming language

to database language to allows them communicating with stored data. The data for the DVMS

was stored in another system controller called Raspberry Pi 3 Model B+ to function as a server.

With this approach, it reduces the workload of the system controller that was operating the

DVMS UI for management and operation. It also helps smoothen the data retrieval process

without any disturbance from other processes.

Focusing on the connection for Python application towards database in both

management and production environment, Figure 3.7 shows an overview of the linkage

between Python application (Tkinter) in gathering the data from the database. It starts with

Tkinter send a connection request to the MySQL Connector Python API. Then, the Python API

forward the same request in a suitable language to make the database understand the request

and results in the accepted connection with the connected signal to MySQL Connector Python.

After that, it followed by the Tkinter to send a cursor connection which allows the DVMS

interface to communicate throughout the entire database system. With a granted connection to

the database, it allows all the process of data retrieval through executing a certain SQL

statement or certain SQL query for that back-end database. With that, it results in the DVMS

with requested data and allowing users in the management level to connect to the user in the

production level or vice versa throughout the usage of DVMS.


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Python application (Tkinter)

MySQL Connector

Python

Python DB API

Database

mysql.connector.connect()

Connection.cursor()

Cursor.execute()

Connection request

Connected

Result data

Figure 3.7: Overview of Python application working with the database.

The production environment of DVMS was equipped with a counting system to collect

the production data. At the beginning of this research, the video recording counting system was

proposed to be a production counter as it does not affect any of the production processes.

However, then the implementation of the video recording counting system does not worth

towards this research and it also not the main concern of this research. The proximity sensor

with NPN characteristic was used to replace the counting system of DVMS. This proximity

sensor was connected to the Raspberry Pi GPIO pin, where it allows the signal to be read by

the Python application. Figure 3.8 depicted the circuit for the counting system to be processed.

The proximity sensor is supplied with the 5V of DC that separated from RPi. This sensor works

when the metal has detected on the sensor, and then it passed the signals directly to GPIO pin

on RPi.

Figure 3.8: Counting system schematic diagram

Raspberry Pi 3 or 4 GPIO Pin Header

Grounding3.3v Pin

GPIO Pin


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3.9 Design process of the User Interface (UI)

The design of the Digital Visual Management System (DVMS) user interface (UI) followed

the user-centered design (UCD) approach. In the early development, the users and the specific

task were figured out. With this approach also, the iterative design has been developed by using

the UCD cycles where it includes the designing, testing, measuring and redesigning.

After the requirement analysis takes place, the development of DVMS UI design has

been followed. The analysis has provided information on the proposed features of the system.

In the early development, it started with the low-fidelity prototype, where a sketchy and

incomplete prototype has been roughly designed. This prototyping phase begins in a blank

paper than mock it using Tkinter, a standard Python binding to the Tk GUI toolkit. The low-

fidelity prototype focused on the underlying design and the substance examples of the UI. This

stage involved stakeholders and Autokeen members in order to acquire immediate criticism on

the structure and the arranged usefulness of the framework.

Otherwise, the colours for the UI in DVMS was chosen to accomplish efficient colour

communication in the visualization. The right colour has helped the user to comprehend the

working and the fundamental thought of the framework all the more rapidly. Besides, the

colours were utilized to emphasize and de-emphasize the information. The choice of colours

followed these rules: simplicity, consistency, clarity, and language of the colour (Ortiz and

Park, 2011)(Wright, Mosser-Wooley and Wooley, 1997). Gestalt principles of visual

perception were applied to arrange the data and designs and to give the user valuable

experiences into them, group them, and separate the information, or make the information

increasingly distinguishable from the rest (Wright, Mosser-Wooley and Wooley, 1997).

Furthermore, the increases in the numbers of emojis usage as it simplified the message

in the form of a small digital image or icon. The emojis recently has become the way to express

an idea or emotion has led towards the development of DVMS UI. The ideas of emoji have

been inserted towards the DVMS UI development as it visualized simple messages or emotion

towards the user to takes any action when they see it. A study has been conducted when people

saw an emoji, and it certainly plays a role in enriching users’ emotions (Yuasa, Saito and

Mukawa, 2011). From this, the emojis selection plays a significant step in order to make emojis

control the production rate of the operator.

Last but not least, the research followed by the development of the high-quality

prototype for the DVMS UI. All the proposed functionalities have already executed in the


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DVMS UI to works interactively. Stakeholders were asked to analyse the prototype if there

was a room for modifications to take place. After the modifications have done towards the

identified area in initial testing, the high-quality prototype was formed. Then the DVMS

prototype tested with the real-time production situation to observe awareness of users towards

DVMS and their production performance. The users then observed, and the reaction towards

the UI was recorded and evaluated. These steps were done to improve all the area in DVMS to

make sure the visual elements have satisfied by user. Otherwise, the usability test also was

done towards the users to improve the UI continuously. The testing brought about the

distinguishing proof of new prerequisites that required the upgrade of parts of the framework

and the consideration of extra functionalities.

3.10 Summary

In this chapter, the researcher described the methods that have taken, which observations and

interviews for this research study to overcome the problem facing Autokeen visual

management (VM) system. The process of the development of the new VM system was done

iteratively, where it contains three different stages, namely; initial, prototyping, and

implementing. In the initial phase, the first UCD cycle has been taken place along with the

initial draft of the DVMS UI, where it contains only one UI. Then it further with the prototyping

phase, the counting method has been decided for the DVMS and the DVMS containing two

different UI separating the niche in a different environment. This phase was closed by the first

evaluation study, where the first usability data has recorded. The final iteration process is

implementation. The UCD process still occurs, and this phase also ends with the usability test's

evaluation process. Besides, the problem faced when constructing the study was figured out.

The objective of solving the problem also was described in this chapter. All the system

architecture has been explained in each phase. It also shows the improvement has taken place

in the development process of DVMS.

All the used methods in conducting this iterative study processes have clarified early in

this chapter. It then proceeds by explaining the concept of the DVMS, which questions why

this system needs to be developed. Furthermore, it stated the DVMS containing two different

interfaces that interconnecting to allow the communication processes in the Autokeen. All the

purposes of DVMS also have been briefly explained in the concept of the DVMS section. This


62

chapter then continues by showing the reader on the DVMS overview. It shows how the DVMS

working principle that will undergo to achieve its concept.

Moreover, the researcher has included each interface's functional requirements, namely

the operation interface and management interface. This requirement has become the benchmark

of the DVMS development processes. The architecture of DVMS also described over this

chapter that was elaborating more on the visual processing information over the DVMS UI.

This section mentioned visual DVMS UI for running over the Raspberry Pi 4 and connected to

the proximity sensor for counting purposes. The management DVMS UI was running over the

pc or laptop. This two different interface has described connecting over the WLAN towards

the same database. Raspberry Pi 3 has been used to control the database system and works as

a server for this system. Finally, this chapter ends with the design process of both DVMS UI.

The methodology of developing the DVMS was briefly explained in this chapter.

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CHAPTER 4

Development of DVMS

During the development of the Digital Visual Management System (DVMS) in optimizing the

production activity with the integration visualization tools with the Internet of Things (IoT)

features, a user-centered design (UCD) process was used in creating the design concept of the

DVMS. In order to do so, the necessary process must be included. Therefore, this chapter will

explain the details of collecting data, problems encountered, and ways to solve the problems.

Meanwhile, sort of DVMS dashboards was formed and the development processes were

explained.

4.1 Data collection

The development of DVMS was started with the process of data collection where researcher

attends a site visit towards Autokeen Sdn. Bhd. to construct the study plan for the visualization

study. The site visit was done towards Autokeen to collect as much data regarding the

production activities in Autokeen by process of interview and observation. The interview

process was done towards Autokeen managers and employers. From those processes, the

researcher has known the Autokeen production system on the studied line (Line D or WSS

Line). The production system that Autokeen using namely one-piece flow. The production

areas affected in conducting this research are in the second stage of the production process.

The stage was doing assembly processes of specific nut or bolt towards the different stamped

panel. These processes were done manually by the operator with the help of a nut or bolt control

feeder, as explained in chapter 1. All the related information, such as implemented VM tools

and product information, was collected from Autokeen. The implemented VM tools in

CHAPTER 4: DEVELOPMENT OF DVMS

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Autokeen was described in chapter 1. This data was required to emerge with the new

technology, then helps in DVMS UI development.

Furthermore, the data collection process was then done to collect the user requirement

for the process of DVMS development. This process was done by interviewing the Autokeen

plant manager. He is one of the stakeholders from Autokeen to make sure the Autokeen

production system can be improved after the DVMS development. The DVMS also required

to satisfied all the user requirements from the industry as below:

• Set and measure the daily target of the production.

• Visualize the real-time production performance of the cell and record down the

performance of the operator.

• Alarm or alert the employee based on the production status of the monitored cell.

• Reminder on a production shift timing.

• The motivation for the operator to achieve the target and improve their performance.

All the listed user requirements above have become the guidelines in constructing

DVMS UI. All the UCD cycle was followed the same user requirements in making the

successful DVMS.

4.2 Visualization Dashboard for proposed DVMS

The development process of Digital Visual Management System (DVMS) UI dashboards is

explained in this section. There are three main phases has gone through in developing this UI.

In the first phase of the developed DVMS UI, it was implemented before conducting the

evaluation study. The second phase of developing DVMS UI, it contained the modifications

that were needed by the results of performing the first evaluation study. Finally, the third phase

is the improvements from the second evaluation study of the previous dashboards. These

alterations and enhancements were obtained from criticism from the users and the results of

the evaluation study. The consequences of this evaluation study can be found in chapter 5.


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4.2.1 The first phase of DVMS

Figure 4.1: The first phase dashboard of the Digital Visual Management System (DVMS)

Figure 4.1 shows the first dashboard of the Digital Visual Management System (DVMS)

interface. It contains only one interface where management level and operation level are

sharing the same interface but can access in a different location. It is an exercise taken by a

researcher that intend to test a specific design idea or assumption of the real design. The concept

is to count the real-time production, and the emoji works as an indicator of the performance

measurement in DVMS. This mock-up design of DVMS was constructed based on the user

requirements that have been gathered from the user through the process of User-Centered

Design (UCD).

The management in the first version was allowed to key in the demands towards the

interface. At the same time, the min and max rate has been calculated according to the specific

cycle time that has programmed towards DVMS UI. This interface then will calculate the

number of the produced item by the operator, and this counted item then used to calculate the

productivity rate. The productivity rate was used as the indicator for the emoji that were going

to be displayed. This emoji works as a productivity indicator of the operator’s production. The

operator needs to react towards the emoji that DVMS shows by the increase or maintain the

production speed. The first version of DVMS is the only a mock application where it used to

get the main concept of visual planning.


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4.2.2 The second phase of DVMS

(a) Management interface

(b) Operation interface

Figure 4.2: Second phase dashboard of DVMS prototype design (a), (b)

The second dashboard of the DVMS was executed after the second cycle of the UCD approach.

The new UI contained the alterations that were needed to improve production management.

The separation between management and operation activities was to enhance different niche


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functionality. With that, it also allows more feature implemented to improve their production

activity.

Figure 4.2 shown the second phase developed dashboard of DVMS, which containing

two different UI. These UIs were focused on the specific target user; (a) Management interface

is for the managing and monitoring the production activity, while (b) Operation interface where

a user received the specific task from another user and the interface monitor the productivity

of the user doing the activity in the production cell.

In the management interface shown in Figure 4.2. (a), shows the visual image of

Management Interface for DVMS that has five different features, which also has different

functions as below: -

i. Production History – this section allows the management team to review the

previous production activity based on the type of cell, operator, and part id on

the selected date. From the provided data, management can see the performance

for each operator in doing a different kind of task in a different cell. Then,

continuous improvement can happen when the management team has reviewed

the performance and rearrange their operator based on the results.

ii. Machine Monitoring – in this section, it allows the management team to review

the machine performance. The common condition of the machine will be key in

by the operator in the operation interface before they conduct each task. This

would help the management in the tracking of the bad condition of the machine

and send it for maintenance.

iii. Overall Equipment Effectiveness (OEE) – This section displays the OEE of

production includes the availability, performance, and quality in a real-time. It

also will plot a graph for OEE against time in a real-time. This feature visualized

the management team the trend of production activity on the shop floor.

iv. Communication Box – this feature gives a space where the management

interface and operation interface can communicate. So anything come cross

management team mind, will send the messages to the other interface. It also

shows the messages coming from the operator that is using the operation

interface.


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v. Line Activity – this section is essential; two different functions were to manage

and monitor the production activities. In order to begin the production, the

management team should set up a specific task towards the operator. Then, it

will send the task information towards the operation interface, so that operator

knows what the management wanted. After that, the management interface will

visualize with the production status in the production cell while the production

was running.

For the production interface, the concept is to communicate continuously. The data that

is being visualized to the operator is the reflection from the operator itself. This situation will

become a mirror for the operator to continuously improving themselves. This interface will act

as production speed indicator of the operator by showing different emoji that describe the

operator actions and also gives the motivation to boost up operator emotion. Figure 4.2. (b)

show the user interface for Operation interface that contains five different feature, which also

has different functions as below: -

i. General information – this was located on top of this interface (light blue), it shows the

greeting to the operator, date, time, and temperature.

ii. Operator progression – this shows the progress time of the productions and break time

that has been consumed by the operator.

iii. Production information – the number of demands for the production has been shown in

this section. It also shows the number of finish goods and scraps form during production

in a real-time. Graphs in this section showing the trend of the productivity rate against

time will also be showing in this section.

iv. Activity rate – under this section, two gauges shows the rate of productivity and also

the defects item that has formed during production. It is also showing the emoji with

some wording to make sure the operator is motivated. As the emoji is the main visual

aspect in this user interface, the location for this feature was on the centre of the user

interface.

v. Communication box – to show the message from the management interface and also

the operator allows sending the message too.

vi. Machine monitoring – for the operator to report the machine condition before running

the production.


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4.2.3 The third phase of DVMS

This implementation of the third phase of the UI was due to the results from the evaluation

study that the second phase has not to fulfil the user requirements. The third phase of DVMS

is the results of the evaluation study of DVMS second phase. The improvement was made to

make the DVMS look more attractive and following the lean production theory. The methods

for the evaluation study was decided and described in Chapter 4, and the results of the

evaluation are detailed in Chapter 5.

Figure 4.3: Third phase dashboard of the management interface of DVMS

In the management interface, the concept is to managing the production activity while it can

see the production activity on the production floor. Besides, this interface also can review the

previous production activity for production improvement in the future. From Figure 4.3, it

shows the visual image of Management Interface for DVMS that has six different features,

which also has different functions as below: -

i. Production History – this section allows the management team to review the previous

production activity based on the type of cell, operator, and part id on the selected date.

From the provided data, management can see the performance for each operator in


70

doing a different kind of task in a different cell. Then, continuous improvement can

happen when the management team has reviewed the performance and rearrange their

operator based on the results.

ii. Machine Monitoring – in this section, it allows the management team to review the

machine performance. The common condition of the machine will be key in by the

operator in the operation interface before they conduct each task. This would help the

management in the tracking of the bad condition of the machine and send it for

maintenance.

iii. Overall Efficiency – This section displays productivity rate, defective rate, and overall

efficiency (goods – defects) in a real-time. It also will plot a graph for overall efficiency

against time in a real-time. This feature visualized the management team the trend of

production activity on the shop floor.

iv. Communication Box – this feature gives the manager the ability to announce all cell or

specific cell. Also, if some of the cells are having an issue (breakdown), it will report

to the management team on what issue they faced. So the management team will send

the technician to solve the problem.

v. Line Activity – this section is very important; it has two parts. The upper part is for the

management to give the task towards the cell. Meanwhile, the lower parts are showing

the real-time activity of the cell. In order to begin the production, the management team

should set up the set of tasks towards the operator by using the upper part. Then, while

the production was running, the management team can monitor the productivity of their

operator through the lower part. Every detail of the running production was visualized

in this part.

vi. Variable Management – this function can be access by clicking the icon located on the

left side of line activity, three boxes (button) for managing the variable before

submitting the task towards the production interface. The variable that can be managed

through this option is operator, parts and weightage.


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1st variable – Operator

Management team need to set up their operator that

working in the WSS line by key in the operator

information to this section.

2nd variable – Parts

Management team need to set up all the

parts that need to assemble in WSS line by

key in the parts information to this

section.

3rd variable – Weightage

Weightage is a ratio for the productivity

rate towards demands. Management

team need to set the suitable weightage

for their operator.

Meanwhile, in the third phase of the production interface, the UI contains a different frame as

the screen that was used to display the UI on the 7-inch display. In order to do so, the UI will

contain a different frame to ensure the operator able to see the visual aspect of the interface

while doing their work. Figure 4.3 shows the four frames of the third version of DVMS that

are going to be evaluated in the Autokeen. The evaluation results will be shown in Chapter 6.


72

(a) The third phase of production interface – Frame 1

(b) The third phase of production interface – Frame 2

(c) The third phase of production interface – Frame 3


73

(d) The third phase of production interface – Frame 4

Figure 4.4: Third phase dashboard of the production interface of DVMS

The concept of the third version of the production interface is the same as before. However, it

is more precisely focusing on to visualize the daily task of the production activity. The

improvement that has made towards this interface is on each feature of the interface. Figure

4.4 shows the improvement that has made towards the production interface for DVMS that has

seven different feature, which also has different functions as below: -

i. General information – this was located on top of this interface (light blue), it shows the

greeting to the operator, cell name, date and time. Otherwise, whenever the

announcement was made by Management Interface, a small icon will pop up in this

section to tell there is an announcement.

ii. Safety Requirements – this feature is located in the first frame (Figure 1.3) showing the

minimum safety requirement to perform the upcoming task. The operator has to follow

all these requirements before pressing the “▶” to show the next frame (Figure 1.4). It

acts as the entry point for the operator to operate. Besides, whenever the operator leaves

(pause the production), this section will appear with the status of operation and the time

pass whenever the operation is a pause.

iii. Task Description – In this section, the selected task will fill up the details of the product.

Meanwhile, all the boxes will fill with standard operation procedure (SOP) for the

selected product.


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iv. Task Management – This section shows up all the task given by the manager for the

shift. If the running time is the day, then the production task of the day will show up

and vice versa with night shift. Before starting the production, the operator needs to

select the task and show it up into task description. After that, they are allowed to start

production.

v. Machine Monitoring – In this section, the operator needs to explain the state of the

machine before starting the task. This data will be transferred to the database for

management for later review.

vi. Task Completion Rates – The completion rates of the shift by the operator is shown

under this area. This shows the number of completed task against the number of the

total task given by the manager.

vii. Task Information – this section shows up during operator doing their work. It shows

the process name, the number of task running and the box is for the picture of the

assembled product (guidelines for assembling processes). In the meantime, the operator

also can show the task description of the selected task by pressing the task number box.

Then sort of SOP will show up in another window.

viii. Time Management – this section countdown the time required by the operator to

complete the task. When performing a task, if the operator needs a break, they need to

choose a reason. Besides, this will also be visualized in the management interface.

ix. Activity Rate – this part is the main part of this interface, it will show different emoji

faces with description depending on the performance of the operator as depicted in

Figure 4.5. It will also visualize the status of the machine when no operator is

performing the job. It will convey the status of the cell.

x. Production Status – this section will visualize the amount of product produced, and the

graph will show the operator's real-time productivity. Graphical trends will visualize to

the operator whether the performance is increasing or decreasing for the entire task.

Therefore, they can take action to stabilize productivity.

xi. Emergency Button – this allows the operator to stop the production immediately when

something bad happens to the machine or system. A sort of problem list will come out

under the activity rate area to inform the manager regarding the problem.


75

Figure 4.5: The emojis for the productivity rate.

4.3 Summary

At the beginning of this chapter, the data required for developing the DVMS was briefly

explained. The mentioned data was gained in the initial phase of the iterative study, as stated

in the previous chapter. The first two steps in the first UCD cycle was the important processes

for obtaining the initial data for the research and also the DVMS development. Environmental

around the research area was the first data of this chapter mentioned, including the production

processes, production, and information type of employee in Autokeen. Secondly was the user

requirements from the industry for the DVMS to be developed. Then, after the data was gained,

the process of developing the DVMS dashboards was explained. In satisfying the user

requirements, the process of development was done in three different phases. The three

different phases of developing DVMS is the same process of the iterative study mentioned in

the previous chapter. This step also aims to achieve the third research objective. Furthermore,

this chapter proceeds by the researcher elaborated on all the developed DVMS functionality

with the picture of the dashboard of DVMS. In the following chapter, details of the evaluation

processes were explained in detail; all the steps and methods taken were elaborated.

Very good performance => 80% Good performance => 60%

Low performance => 30% Very low performance < 30%

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CHAPTER 5

Evaluation Study of DVMS

This chapter explains the structured evaluation study that has constructed for the Digital Visual

Management System (DVMS) to achieve the usability results. This usability test was to

evaluate the interaction of users towards DVMS. This evaluation study was introduced in

chapter 1 and explained in chapter 3, where it only tested towards the second and third

visualization dashboard where the VM tools have been revised. In the following sections, this

chapter was starting by stating the framework of having this evaluation study towards DVMS.

Structure of this chapter followed by the explanation on the goals of evaluating the DVMS.

Besides, the method, techniques and scenarios of the evaluation processes were narrated after.

The environment and equipment setup of the evaluation study were depicted and explained in

details for each evaluation event. Also, the evaluation event tasks and scenarios were then

structured and describe to make the data collecting processes smooth. With all the tools before

handling the evaluation process explained, the step of handling the process then explain in the

final section of chapter.

5.1 Evaluation study framework

The evaluation procedure initiates by determining clear goals, appropriate questions and real-

time tasks to meet the research objectives. For that purpose, following steps resembles the main

activities of this method, in order to perform user testing and to obtain a reliable outcome for

the evaluation study:

i. Decide and structure the clear evaluation goals which are connected to the research

objectives;

CHAPTER 5: EVALUATION STUDY OF DVMS

77

ii. Choosing the right evaluation methods and techniques;

iii. Standby for the practical issues;

iv. Plan the evaluation processes;

v. Evaluate, analyse, and present the data.

5.2 Evaluation study goals

The goals of the evaluation study are shaped to accomplish the research objectives. In this section,

the main goals of performing the evaluation study will be highlighted. After developing and

implementing the DVMS for managing the Autokeen production activity, the user evaluation was

carried out to evaluate the DVMS so as to accomplish the main goals as follows:

i. Obtain proposals or choices to refine the UI plan of this part;

ii. Identify any usability issues so they can be tended to as a piece of the iterative structure

process, in particular: System Usefulness, Information Quality, Interface Quality, and

User Satisfaction

iii. Check the user's performance and recognize the errands and capacities which present

difficulties to the user;

iv. Examine diverse option coordinated UI plans to locate the most reasonable UI for

managing Autokeen production activity before beginning of the DVMS integration;

v. Compare the general user fulfilment towards the framework by utilizing self-upheld

measurements strategies, and survey the exhibition of the techniques.

5.3 Methods, techniques and participants

In the user evaluation study, the different usability methods and techniques has been chosen to

obtain the necessary data and to accomplish the evaluation goals. Likewise, various sorts of

participants were included, specifically broad user and expert. Coming up next are the

descriptions of the testing methods and techniques of how they were utilized, with data on the

reasonable kind of participants for every one of them.

i. Heuristic evaluation testing method – this method was applied towards the

individuals that experienced towards the lean management and experts towards

Autokeen production floor. The point was to recognize ease of use issues in the DVMS

UI and to acquire suggestions for remedial activity. The Walk-through procedure and


78

review were utilized as strategies for this technique. In this strategy, the expert 'test-

drove' the DVMS, and through remarks and open-ended information was never really

address any usability issues which probably won't be obvious to an ordinary user later

in Autokeen creation floor. This technique was applied towards the two assessments

with an alternate number of experts.

ii. User-based testing method – this method was applied in evaluating the uses on DVMS

user interface to test the interaction of Autokeen employees (management level &

production level) towards the DVMS user interface. The aim was to measure the

effectiveness of information flow from the management interface to the operation

interface. Before doing the test, the qualification and recruitment of participants need

to be done—first, an interview towards employee to know their knowledge on lean

visualization tools and computer system. Most of the Autokeen production operator

mostly are foreigners. They might not know the English language that was implemented

for the system. An interview needs to be done towards them will be taken. The English

words that have been implemented with the bits of help of some pictures and colours.

iii. Survey method – survey method was utilized with general users. It was utilized to

acquire the users' point of views towards the DVMS UI and to get their criticism on

that. Two techniques were utilized for this method, specifically the interview and

questionnaire. In the first evaluation study, the questionnaire was not distributed

towards users, however the interview was handled. In the second evaluation study, both

the interview and questionnaire method were applied to it. The standardized

questionnaire was distributed after survey has done in the second evaluation study to

gather the information and to quantify the usability factors:

▪ The Post-Study System Usability Questionnaire (PSSUQ) version 3 has been

used in this study to acquire the system quality, information quality, and

interface quality of the DVMS UI. With the acquired data, the user satisfaction

towards the system will achieved also.

Besides that, some additional question also will ask towards the participants to

investigate the participants background for further exploration study.

iv. Observation method – a direct-observation and video recording will be done towards

the experts and general users to see how the interaction of all type of users towards the

system. A note will be taken on direct-observation and the video is for reviews. This


79

method used only one observer called 'moderator'. The 'moderator' is the researcher for

this project.

The number of participants in the first evaluation was 6, where all methods were used.

Meanwhile, in the following evaluation study, 10 participants were asked to take parts in these

methods. Two expert participants in the first evaluation study also participated in the second

evaluation study. The other 8 participants were new to this evaluation processes.

As in the previous chapter, three phase dashboards of DVMS has been explained where

iterative study has been takes place. A brief explanation on each dashboard also has been

explained where the first dashboard only undergoes the UCD cycle processes. Meanwhile the

other two were evaluated with this structured evaluation study processes.

For the first evaluation study, the second dashboard of DVMS UI was tested. Two of

the expert participants with different gender are in middle-aged. For the general users, all of

them were male, one in middle-aged and the other two was in early 20. The participants were

of two different nationalities, namely Malay and Bangladesh.

Meanwhile, the third version of DVMS user interface was evaluated in the second

evaluation study with 10 participants, for the experts’ participants, it was the same participants

in the first evaluation study that are in middle-aged. For the general users, all 8 of them were

male and with age ranging from 19 to 35. Two expert participants had exposed to a DVMS

user interface the second version before, while 8 had not. The participants represented three

nationalities, namely Malay, Bangladesh, and Indonesian.

Table 5.1 shows the sort of usability test method with different type of techniques and

participants that will undergo in both evaluation studies. It shows the connection between the

distinctive methods of usability, type of techniques, and types of participants and numbers of

participants in both evaluation study processes. This table shows a clear sorting of usability

method for the evaluation procedure to take place.

Table 5.1: Sort of usability test method with different type of techniques and participants.

Methods Techniques Type of

Participants

Number of Participants

First evaluation Second

evaluation


80

Heuristic Walkthrough

Experts 3 2 Interview

User-based Direct observe

General

users 1

8

(2 line-leader & 6

operator) Note-taking

Survey Interview

General

users - 6

Questionnaire

Observation

Direct observe Experts &

general

users

6 10 Note-taking

Video recording

5.4 Environment and equipment

In this evaluation study, both studies were conducted on the production floor at Autokeen Sdn.

Bhd. In the first evaluation, only one cell in the Line D or WSS Line was applied the DVMS

user interface. The first evaluation was using the second version of the DVMS user interface

to manage the production activity in Autokeen. At this time, the laptop screen has used as the

visual device to display the interfaces of the DVMS. The laptop has been placed around the

cell for the operator to monitor their production speed. Otherwise, the displayed DVMS also

was used to control the production speed come from the operator.

Meanwhile, for the second evaluation, three cells in the Line D or WSS Line of

Autokeen production floor, the DVMS user interface was mounted in the right spot where the

user can easily see the screen. A digital touch screen was used and connected to the system

controller to visualize the participants the DVMS user interface.

For both the evaluation process, the moderator was located around the machine. It was

to observe the participants without disturbing the production activity that was managed through

DVMS. Besides, the moderator was also taking notes on a note-pad, and video recording was


81

set up for further investigation. Figure 5.1 illustrates the part of the workspace that has the

DVMS setup for the evaluation purposes.

Cell 55 KVA 6 (bolt weld assembly)

Moderator

Op

erto

r 1

Trolley put the nut welded panel

Cel

l 35

KV

A (n

ut w

eld

asse

mbl

y)

Cel

l 55

KV

A 6

(b

olt

we

ld a

ssem

bly

)

Op

erat

or

2

Pal

let

for

un-w

eld

ed p

anel

Pal

let

for

we

lded

pan

el

nut

& b

olt

(a)First evaluation environment setup


82

Op

erto

r 1

Pal

let

for

un-w

eld

ed p

anel

Trolley put the nut welded panel

Cel

l 35

KV

A (

nut

wel

d as

sem

bly)

Op

erat

or

2

Cel

l 55

KV

A 6

(b

olt

we

ld a

ssem

bly

)

Op

erat

or

3

Cel

l 55

KV

A 5

(b

olt

we

ld a

ssem

bly

)

Pal

let

for

we

lded

pan

el

nut

& b

olt

Pal

let

for

we

lded

pan

el

Nut

on

ly

Pal

let

for

un-w

eld

ed p

anel

Cel

l 55

KV

A 6

(b

olt

we

ld a

ssem

bly

)

Moderator

Lin

e Le

ader

(a)Second evaluation environment setup

Figure 5.1: Evaluation of a workplace environment

5.5 Study tasks and scenarios

This evaluation study was applied towards test industry called Autokeen. The production

activity in the WSS machine or Line D will be applied towards the both evaluation study. All

the scenarios were prepared based on the activity of the first three cell in Line D namely 35

KVA, 55 KVA 6, and 55 KVA 5. From these scenarios, a set of tasks were formed to allow the

users to undergo the user-based testing method.

In the first evaluation study, the second version of the DVMS user interfaces was used

to be evaluated in the Autokeen. The evaluation study was constructed in the Autokeen

production line and to be tested by the participants. The scenario has been conducted by the

moderator to see how the DVMS user interface can interact with the participants. During the

evaluation process, most of the functionality in the DVMS user interface will not be useful

towards the participant. This first evaluation study is doing to evaluate more on the design

concept that the user will interact more and to make sure the system controller is reliable

towards the environment. Below is the scenario that has been doing in this first evaluation

study: -


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Scenario:

“Line leader check the amount of product that needs to be done by the operator in cell 35

KVA. Then the line leader asks the operator to do the task by providing the stamped panel on

the un-welded pallet and inform the operator is doing the production operation.”

Below are the set of tasks for this scenario:

i. Identify the demands of the productions.

ii. Key in the number of demands and send the data to the database.

iii. Operator view the number of demands

iv. The operator starts doing the production activity until they meet the demand

For the second evaluation study, the third version of the DVMS user interface was first

undergoing the heuristic evaluation, and some changes have done to it before the user-based

testing method in the real-time production situation. Chapter 5 will show the improved

interface that is going to test towards participants. The improved interface also contains two

different interfaces that were also focused on a different group. The scenarios have been made

toward every group, and each scenario contains different task that going to be perform by a

different group. The first third scenarios were made to the management group, where they will

be using the management interface. Meanwhile, the rest are for the operators where the

production is performed. Below are the scenarios for the second evaluation test: -

First scenario:

“In the management environment, they need to plan for the production activity that will be happening on the production floor. But before that, they need to see which operator that suitable for that particular production activity as they need to have a smooth production process. After that, the planned production has been passed to the line leader and the line leader check the availability of product that and then send it towards the production cell 35 KVA, 50 KVA 6, and 50 KVA 5. Then the line leader asks the operator to do the task by providing the stamped panel on the un-welded pallet and inform the operator is doing the production operation.”

Below are the set of tasks for this scenario where the DVMS management interface was being

used in performing the first scenario:

i. Review the production history and machine condition to plan for the production


84

ii. Insert the variable needed by the DVMS management interface

iii. Set the planned task towards the DVMS management interface

iv. Review all the planned task before asking the operator to start working.

Second scenario:

“In the production floor, the management team need to go down from the office and went to

the shop floor to see the status of the production floor. Otherwise, when the management needs

to make an announcement or to ask the operator to be more productive, they also need to

approach the operator, went down to the shop floor.”


used in performing the second scenario:

i. Monitor real-time production data (Productivity & Efficiency).

ii. Monitor the cell under the line activity

iii. Make an announcement to a specific cell or all cell.

Third scenario:

“When the operator in the production floor has finished their tasks that already plan, if the

manager needs to set another task toward the operator, they need to go down and ask the

operator to do the next task.”


used in performing the third scenario:

i. Monitor the status of the cell under the line activity.

ii. Instantly review all the task under the task description by re-select the shift dropdown

menu for each cell to check the cell availability.

iii. Add the specific task towards the specific cell that is available.

Fourth scenario:

“Before starting the production activity, the line supervisor will be giving a short talk

regarding the previous production activity such as safety equipment, machine condition, etc.


85

In the meantime, all the operators need to make sure the PPE that they are wearing followed

the safety guidelines. After that, the operator then started to assign into a specific line by line

leader and then start doing their work according to the task given and changing the A3 paper

that displaying the SOP into the assigned task. Line supervisor also has taken note of each

machine condition before the machine has passed toward the operators.”

Below are the set of tasks for this scenario where the DVMS production interface was being

used in performing the fourth scenario:

i. Check all the safety guidelines shows by the interface before proceed to the next frame

where the task is showing.

ii. The interface will greet the operator by welcoming the operator towards the cell. If the

interface showing the wrong name, means the operator need to re-check with the line

leader.

iii. Under task management, the task for the entire shift will be showed up towards the

operator, and the operator needs to select the most top task first before running the

process. The interface will show the SOP for the task towards the operator.

iv. Under the same frame, on the centre bottom of the frame contain the machine

monitoring. An operator needs to tick all the stated machine condition before starting

the production.

v. Operator press the start production and start doing the process.

Fifth scenario:

“While doing the production, operators are about to use the toilet, to have break time or

anything. The operator will put the arrow chart displaying the cell status on the trolley to

display the status of the cell to inform anyone who passed by the cell. Moreover, after finishing

the break time or going to the toilet or anything, the operators remove the arrow chart and

start doing the work again.”

Below is the set of task for this scenario where the DVMS operation interface was being used

in performing the fifth scenario:


86

i. Under the third frame of the DVMS operation interface, there is time management, and

the operator needs to select the reason for pausing the production. Then the operator

needs to press pause.

ii. When the operator pressed the pause production, it moves the frame into another frame

displaying the SOP of the production, the status of the cell in term of the picture and

the time elapsed on the paused operations. The operator needs to make sure the time

elapsed time has followed the allocation time of paused production. Then the operator

needs to resume the production to resume on the specific task.

Sixth scenario:

“While operating the job, the operator was making a mistake on the specific part and cause

the part defect. The operator should revise the SOP to make sure the processes are right. The

operator needs to look at back the SOP and make sure everything is right.”

Below are the set of tasks for this scenario where the DVMS operation interface was being

used in performing the sixth scenario:

i. Under the “Task Information”, it displayed the completed product with the chosen

nut/bolt for the specific part. The operator needs to press the “Task No. #” to review

back the SOP.

ii. After that, the new frame will come out containing SOP and Time Management, where

the operator needs to revise the SOP and then continue the production without wasting

time.

Seventh scenario:

“While operating the job, the machine was run into a problem. The operator called the line

leader to reports the problem towards maintenance.”


used in performing the seventh scenario:

i. The operator needs to press the emergency stop button to stop the production first,

where this message also has visualized in the management interface.


87

ii. The operator selects the problem under the dropdown menu on the centre of the frame

and sends the reports to the management interface that will be visualized in reports area.

Eighth scenario:

“When the operator has finished the operation, the operator needs to put the arrow chart on

the trolley to display the cell status. This will make the line leader approach the cell to check

with the operator, and if there is a new task, the line leader will assign to the operator.”


used in performing the eighth scenario:

i. The DVMS operation interface will display the second frame where displaying tasks,

SOP, and task completion rates. If the operator has finished the task, the task

management box will be empty, and the task completion rates will show 100%

completed tasks, if not they will be a remaining task on the box and with a specific

amount of completed tasks. If the box is empty, the operator needs to press a refresh

button to see a new task coming by line leader, and if there is no incoming task, the

start production will turn into exit production. The operator needs to press exit

production.

Ninth scenario:

“The general announcement was made through the loudspeaker, and sometimes the worker

does not hear the details of the announcement. They will ask the other operator who heard the

announcement.”


used in performing the ninth scenario:

i. The operator will notify the announcement icon on the top bar of their interface and

click it to view the announcement.


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5.6 Evaluation processes

In order to conduct evaluation study, the processes were partitioned into three different phases:

preparation, evaluation session, and analysis and result. The process was start with the

preparation where this phase included setting up the participants for the test and planning a test

meeting for every one of them. Additionally, all the important components have been structured

and prepared before undergoing the process. Also, the evaluation study arrangement and

condition had designed in this stage

During each evaluation session, the following steps were implemented, in the following order:

i. The moderator asked both experts to walk-through the DVMS UI and giving their

opinion on the DVMS user interface before it goes to the general users.

ii. The moderator introduces the DVMS UI towards the general user. The working

principle and the application towards the real-time production activity in Autokeen has

been explain and moderator open for a question and answer session before they using

the system;

iii. The moderator asked the participant to investigate the framework and verbally process

during this time.

iv. The test begins with the constructed scenarios which based on real-time production

processes in Autokeen. Involved participants were asked to performed the production

in the user of DVMS UI. The processed was observed and recorded into sort of videos

and notes;

v. Participant answered the ‘Post-Study System Questionnaire’ after all the task has done;

While operating the DVMS UI, the involves participants were freely to ask the moderator about

the system functionality, processes, and etc.

Following phase where all the tasks has been completed by all participants and the PSSUQ has

been answered. All the recorded data were used to analyse in this phase. This was done so as

to locate the necessary outcome, as characterized in the objectives of the assessment study. In

this final phase, the examination occurred after the information were gathered and joined. The

results of both of the assessment examines are introduced in the Chapter 6.


89

5.7 Summary

The entire chapter described the processes of handling the evaluation study, where the usability

test took place to evaluate Autokeen users' interaction with the developed DVMS. Two

different usability evaluation was constructed, as this study was conducted iteratively. The first

usability evaluation was done in the second stage of the iterative study, prototyping. Then, the

second usability evaluation study was followed in the implementation phase. In order to create

these evaluation studies, the evaluation framework has been the first thing created and

describes in the first section of this chapter. This first section has guided this research by

planning sequential steps for conducting the evaluation study. From the given framework, the

structural evaluation study plan was then structured for this entire chapter. The first structure

of this evaluation study framework was the evaluation study goals. These goals have become

the parameter for this research study that needs to be controlled by the researcher. The first

essential goals that the researcher stated in evaluating the study was to refine the DVMS UI.

The gradual refinement process of DVMS UI will show the different results of user engagement

towards the UI. This user interaction is the main focus of developing this system. Otherwise,

the objective could not be achieved by the researcher. Then, the researcher describes the other

goals in identifying usability issues. This approach helps the researcher figure out the

deficiency in the UI. Thus improvement can be made towards the lack. After the goals, this

chapter has described the way in choosing suitable methods and techniques with a certain

number of participants. Table 5.1 has shown a sort of usability test method with different

techniques and participants in both evaluation studies. This chapter also depicts the situation

when the evaluation study takes place in the section of this evaluation study's environment and

equipment. Before that, to conduct the test, the initial study phase has conducted in the

Autokeen production environment, as mentioned in early chapter 4. The environment was

studied, and the real-time scenarios of the production activities were recorded and applied to

the evaluation study. The improvement can be made towards real-time scenarios, such as

improvements in the processing time and production steps needed to observe and analyze. This

improvement will then describe in the next chapter. Finally, the processes that need to be taken

for each evaluation study has clarified. This section presents the procedure of conducting the

evaluation study that has arranged to measure the improvements made by each phase. The

results of the evaluation processes will be described in the next chapter.

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CHAPTER 6

Results

This chapter explains the results for this entire research, including the development and

implementation processes and both evaluation studies for the DVMS. The first section of this

chapter will explain how the DVMS implemented. Then this chapter followed by illustrating

the results which linkage to research question and objectives. With this approach, it gives

clarifications about the regions of positive criticism, and those requiring further consideration,

in view of the input from the participants in the questionnaire.

6.1 Visual Management (VM) practise in site

In Chapter 1, the researcher has described the current visual management (VM) tools that were

implemented in the Autokeen production system. Most of the implemented tools seem not to

affect much in the production performance as the appearance of it does not intend to improve

the employee visually. The distinct VM tools that seemed a bit interacted with the operator was

the bolt or nut feeder management system. It works as controlling the feeding amount of bolt

or nut towards the specified panel. It warns the operator when the operator deviates from the

standard. Otherwise, the visualized information seems does not interact with the operator when

the operator is doing the production operation. Furthermore, the visual control board that was

placed far away from the line seems does not become important towards the operator. The

operator only interacts directly with the other operator and the management team when they

ask for something. Even though Autokeen has implemented VM tools quite a lot, the uses of it

seem to worsen as the attractions towards the operators has faded away by the era globalization.

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6.2 Summary of DVMS Implementation

The implementation of DVMS begun with getting the user requirements from the stakeholders,

including Autokeen members, MARII representative, and also TIC directors. It then followed

with the selection of suitable development processes, where UCD has been chosen as it requires

the involvement of stakeholders in developing the DVMS. This implementation then started

with the sketching and designing process where the most effective VM was chosen to be in the

DVMS. This process has gone through the UCD cycle where it was going to several stages that

reviewing processes by stakeholders to confirm the suitable VM and delivery method of

DVMS. Also, the designing process of DVMS was not just based on UCD. It has also followed

by the literature study of the VM tools where to get the successful VM. The first phase of

developing the DVMS has decided the DVMS to based on the Python GUI application

(Tkinter) where it based on the Python programming language that can be easily used in a

different type of operating system. Then, the counting system was based on the video recording

counting system. When this first version of DVMS being drafting, each step of the UCD cycle

has been gone through until the final step where stakeholders have gone through and giving

feedback on the DVMS concept. Other than that, this version of DVMS has also been reviewed

and commented during the researcher’s confirmation candidature. This review is where the

turning point of the counting system of DVMS. The video recording counting system was

resulted not relevant for this study. Then it was replaced with the used of proximity sensors.

After that, the implementation process of DVMS continued with separation of DVMS

UI, where it specifies the area of work in the production process. The management and

operation processes of DVMS has been separated as the DVMS visual elements are going to

be precise. From that, the implementation of DVMS is spiked, where the design of DVMS UI

has changed. This change was made to follow what has been required by users. A UCD cycle

is still ongoing where every change on design has involving users. When this second phase of

DVMS UI has been partially prototyped, the first usability evaluation has been conducted to

test the UI and the system controller (Raspberry Pi) in the real situation of production. With

the usability evaluation study, various feedbacks from the users has been collected, and

improvements of the DVMS were required. These improvements were created a third

development process of DVMS, where it was the final stage of DVMS.

In the final stage of DVMS development, a high-fidelity prototype of DVMS where all

the functionalities are confirmed and tested. The DVMS then was gone through the second

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usability evaluation, where it started with the heuristic evaluation. With this evaluation, it

resulted in slight changes in the design and functionalities towards the DVMS where it was

recorded in the results of heuristic evaluations. This changes then allowed the researcher to

further going through the next step in the evaluation study where the real scenarios were

conducted with the use of DVMS. During the testing, all the behaviour from both users and

DVMS UI were observed to record and repair to make it more efficient. The DVMS then was

going through all the usability evaluation without having a significant problem. All the

feedbacks were recorded to going through further improvements in the future.

6.3 Heuristic evaluations

The heuristic evaluation mainly for participants who are experts from Autokeen to distinguish

the potential issues in the UI of the framework and to acquire their input. For the first evaluation

study, the mocking user interface for DVMS has demonstrated towards the participants. After

that, the interview was done towards the participants that have been judging the user interface.

From that, the participants provide feedback towards the moderator as below: -

• Participants 1 (Plant Manager)

o The user interface does not have the interaction requirements that were needed

by Autokeen. The improvement of human to computer interaction that helps

communication between human to human very low. The visual planning of the

system seems not clear as it only can let the progress happen once at a time.

Otherwise, he also stated that the operators in Autokeen might have bad

emotions as the pressure coming to their life, and he does not want the interface

burdening his operator. The interface that he desires must be attractive and

giving good vibes towards the operator in the meantime, being a monitoring

device for the operator.

o He suggested to construct the interface based on the lean management theory as

Toyota Way has been done through the lean development:

▪ Machine condition (autonomous maintenance)

▪ Quality

▪ Safety

▪ Productivity

▪ Process condition

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• Participants 2 (Project Management)

o As her first sight in during the walkthrough of the DVMS user interface, the

Overall Equipment Effectiveness that contain in the management interface will

not be useful towards Autokeen production management.

o Be specifically assign the job to the production operator, so the operator will

bear in mind what kind of product they are making. Thus the quality of products

can be controlled by the Autokeen.

o Visualize the operator status under the management interface so that in the

management interface, they will know what is happening downs there.

• Participants 3 (Line Supervisor)

o Instead of highlighting the name part, insert the blueprints of product details

towards the interface. With the blueprints, the operator will know about what

kind of job has assigned to him.

o Put on some safety requirements while handling the job towards the operator

GUI. This approach will keep the accident in a minimal amount.

From the results of the heuristic evaluation of the first evaluation study, the researcher

took the point from the expertise and improved the DVMS user interface to be more useful, as

can be seen in the third version of the DVMS user interface in Chapter 3. When the

improvements of the user interface have made, the researcher attempts the second evaluation

test, where the heuristic evaluation test also will be conducted. In the second evaluation test,

all the functionality of the DVMS user interface was explained towards the participants in

Autokeen management level, where they are experts in managing their production activity. The

DVMS UI walkthrough has been done by them in distinguishing the potential issues in this

system and to acquire their input towards the DVMS UI before it being tested with the real-

time Autokeen production situation. With that, below are the provided feedbacks from the

participants: -

• Participants 1 (Plant Manager)

o The user interface for the management interface of DVMS seems so lag, and

the trend of the graph that formed during the production activity was not

beneficial towards them.

• Participants 2 (Project Management)

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o Her response also the same as the first participants, the user interface seems

very lag, and the graph trend in both user interface would not be beneficial

towards the management either operators.

With that, the DVMS UI has been altered to be tested with the real-time production

environment. Thus helps the interaction between the production environment. The improved

UI depicted in Figure 6.1(b), graph in the management and operation of DVMS UI has been

removed. The most effective visual aspects in DVMS have been highlighted. Other than that,

the period for each production task has been automatically calculated in the management UI.

This improvement was due to the new variable that is shown in Figure 6.1(a), which production

cycle time has been added to the interface. The period of the production will be based on the

production cycle times with the number of demands. Through this improvement, it speeds up

the process of delivering the task as it helps the user to count the specific period of the specific

task. The period of each task will be automatically calculated by the management UI before

sending it to the operation interface.

The DVMS operation UI also has undergone the heuristic evaluation. The first

improvement has made where the variables have inserted towards the interface that can be seen

in Figure 6.1(c). As can be seen, the image of the SOP has been depicted in Figure 6.1(c). Other

than that, Figure 6.1(d) shows the significant visual elements have been highlighted towards

the DVMS operation UI. This significant DVMS VM tool was highlighted because the graph

has been removed from the mainframe. From that, the user in the production floor has

visualized with only the effective VM.

(a) The part list in under the variable management.

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(b) The improved management UI after the heuristic usability evaluation of the second evaluation process.

(c) The second frame of the DVMS operation interface

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(d) The third frame of the DVMS operation interface Figure 6.1: The post-improvement after second heuristic evaluation

6.4 Results analysis

In evaluating the tasks in different scenarios, the first evaluation study was only containing one

scenario with four different tasks, and the second evaluation study was containing nine

scenarios with twenty-three different tasks. In the second evaluation study, the tasks are more

because all of the functionality has been going through the heuristic evaluation method first

before running in the real-time production environment. The task in the first evaluation is more

testing on the reliability of the device and the second evaluation used to cover all the

functionality that contains in DVMS. On the first evaluation, 3 out of 4 tasks were completed

successfully by one participant. Meanwhile, in the second evaluation, two different groups

were evaluated with two different interfaces that each of them contains, three scenarios for

management interface and six scenarios for operation interface. The greater part of the errands

was finished effectively by all participants. The following task were finished effectively by all

participants as indicated by the diverse interface: -

❖ First evaluation study:

- DVMS interface:

▪ T1 (Identify the number to be produced in the cell 35 KVA)

▪ T2 (Key in the number to the system)

▪ T3 (View the number on the operator system)

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▪ T4 (Start the assembly process to meet the number)

❖ Second evaluation study:

- DVMS management interface:

▪ T1 (Review production history & machine condition before start planning)

▪ T2 (Insert the variable needed by the DVMS such: operators’ information & parts’

information)

▪ T3 (Set the planned task into each cell: 35 KVA, 50 KVA 6 & 50 KVA 5)

▪ T4 (Review all the set task in the interface)

▪ T5 (Monitor line activity)

▪ T6 (Monitor the cell activity)

▪ T7 (Make an announcement)

▪ T8 (Monitor the status of the cell)

▪ T9 (Review all the assigned task to check availability)

▪ T10 (Add another task into the specific cell)

- DVMS operation interface:

▪ T1 (Check all safety guidelines and proceed into production)

▪ T2 (Check the greeting)

▪ T3 (Select the most top task & review the SOP)

▪ T4 (Reports machine condition)

▪ T5 (Press start once done the task 2,3 & 4)

▪ T6 (Select the reason for pausing production)

▪ T7 (Pause the production and continue after finish)

▪ T8 (Showing the SOP in another frame)

▪ T9 (Back to the mainframe to continue production)

▪ T10 (Press emergency button to stop production)

▪ T11 (Reports the emergency cases)

▪ T12 (Review the task provided and exit the production if the task has finished)

▪ T13 (View the announcement)

In the first evaluation study, task 1 (Identify the number to be produced in the cell 35

KVA) first task was not completed by the participant. Meanwhile, in the second evaluation

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study, while evaluating the management interface, Task 1 (Review production history &

machine condition before start planning) was not completed successfully by both participants.

The other task was completed successfully by both participants in participating in the task

evaluation in the management interface of DVMS. Furthermore, in the tasks evaluation process

of operation interface, task 3 (Select the most top task & review the SOP) and task 8 (Showing

the SOP in another frame) was finished effectively by 4 out of 6 members with the errand

fruition rates (66.7). Undertaking culmination rates are itemized in Table 6.1 and Table 6.2.

Table 6.1: Task completion rates of DVMS management

interface second evaluation study

Tasks Participants P1 P2

T1 - -

T2 √ √

T3 √ √

T4 √ √

T5 √ √

T6 √ √

T7 √ √

T8 √ √

T9 √ √

T10 √ √

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Table 6.2 Task completion rates of DVMS operation interface second evaluation study

Tasks Participants P1 P2 P3 P4 P5 P6

T1 √ √ √ √ √ √

T2 √ √ √ √ √ √

T3 √ √ - √ √ -

T4 √ √ √ √ √ √

T5 √ √ √ √ √ √

T6 √ √ √ √ √ √

T7 √ √ √ √ √ √

T8 √ √ - √ √ -

T9 √ √ √ √ √ √

T10 √ √ √ √ √ √

T11 √ √ √ √ √ √

T12 √ √ √ √ √ √

T13 √ √ √ √ √ √

6.5 Standardized questionnaire results & summary

In the second evaluation study, the Post-Study System Usability Questionnaire (PSSUQ)

version 3 has been used to assess users' perceived satisfaction with the DVMS user interface.

The results from PSSUQ will provide metrisc namely SysUse, InfoQual, and IntQual that

showing the users' satisfaction. The SysUse metric will get from the first six questions of

PSSUQ from participants score as shown in Table 6.3. The mean of the score for in overall

satisfaction with SysUse was 2.22 (on the 7-point Likert scale, with 1 signifying 'strongly

agree'), with a standard deviation of 1.441. This outcome shows the degree of high fulfilment

from the participants toward the usefulness of the DVMS UI.

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In general, the considerable number of items with respect to the SysUse of the DVMS

is a (+1.00). It resembles the average response for all the items was on the positive end of the

scale. Most by far of participants are satisfied on the ease of use and simplification that DVMS

UI provides. Additionally, all of the participants have agreed on easiness on learning the

DVMS as is has marked 100% of percentage agree. Be that as it may, just 67% participants

can get their job done quickly, comfortable while using this system and believe that they can

become productive when using the system. This issue should be viewed as when arranging

future improvement towards the DVMS UI.

Table 6.3: Results referring to SysUse metric, for items 1 – 6 on the PSSUQ

Questions Percentage

Agree Mean

Standard

Deviation

"Overall I am satisfied with how easy it is to

use this system." 83 2.00 1.673

"It was simple to use this system" 83 2.17 1.169

"I was able to complete the tasks and

scenarios quickly using this system." 67 2.67 1.633

"I felt comfortable using this system." 67 2.50 1.643

"It was easy to learn to use this system." 100 1.67 1.033

"I believe I could become productive quickly

using this system." 67 2.33 1.366

SysUse 2.22 1.441

Next on PSSUQ metric are the InfoQual as it measured the quality of the information provided

by the DVMS UI. The question number 7 – 12 has marked as the InfoQual in the PSSUQ

version 3. Table 6.4 displays the results for InfoQual where the average score was 2.20 (7-point

Likert scale, ‘strongly agree’ for 1), with a standard deviation of 1.218. The results were

generally considerable as the score is (+1.00). Overall, the information provided was

straightforward and helped the participants to finish the given tasks and scenarios.

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"The system gave error messages that clearly how to fix the problem when they encountered

it" has been agreed by all participants. All of them also tell information was well organized on

the screen, and it was easy to find the information needed. A percentage of 83 tells the

information was effective and helps them to complete the tasks. However, only 67% of

participants were approved when they have made a mistake. They could recover it easily, and

quickly also only 67% of the participants the information provided was clean. This focuses to

the need to possibly improve the criticism identified with the nature of the data of the DVMS

UI.

Table 6.4: Results referring to Information Quality metric, for items 7 – 12 on the PSSUQ


Agree Mean

Standard

Deviation

"The system gave error messages that clearly

told me how to fix problems." 100 2.50 0.837

"Whenever I made a mistake using the system,

I could recover easily and quickly." 67 2.33 1.506

"The information (such as online help,

on-screen messages and other documentation)

provided with system was clear."

67 2.50 1.643

"It was easy for me to find the information I

needed." 100 2.00 1.095

"The information was effective in helping me

complete the tasks and scenarios." 83 2.17 1.169

"The organization of information on the

system screens was clear." 100 1.67 0.817

InfoQual 2.20 1.218

The PSSUQ also gives the results on interface quality. Questions number 13-15 were utilized

to evaluate the participants' satisfaction toward IntQual of the DVMS UI. From Table 6.5, it

shows that average response score of IntQual was 2.39, with a standard deviation of 1.252.

Otherwise, only 83% of participants has discovered the interface charming to utilize and

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preferred utilizing it. But then, only 50% of participants noticed that DVMS UI functions and

capabilities fulfilled their expectations. From this result, the researcher has to pay full attention

on this point as it seems this point consist biggest issue on DVMS UI.

Table 6.5: Results referring to Interface Quality metric, for items 13 – 12 on the PSSUQ


Agree Mean

Standard

Deviation

"The interface of this system was pleasant." 83 2.17 1.169

"I liked using the interface of this system." 83 2.17 1.169

"This system has all the functions and

capabilities I expect it to have." 50 2.83 1.472

IntQual 2.39 1.252

Overall, the user satisfaction score toward the DVMS UI was acquired by joining the outcomes

of the three metrics that have listed above of the Post-Study System Usability Questionnaire

(PSSUQ) including an extra question on overall satisfaction. Rundowns are represented in

Table 6.6. It tends to be seen that the normal reaction for every measurement is a profoundly

positive one. Plus, the normal reaction to the last thing of the PSSUQ, 'Overall I am satisfied

with this system', scored well, with mean of 2.17 out of 7 points, with 1 is the 'strongly agree'.

From every one of these outcomes, the total user satisfaction from the PSSUQ is 2.24 out of 7,

which demonstrates that the members discovered utilizing the Digital Visual Management

System (DVMS) to be an acceptable experience.

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Table 6.6: Results of the overall user satisfaction on the PSSUQ

Metrics of the Post-Study System Usability Questionnaire Mean Standard Deviation

System usefulness (SysUse) 2.22 1.441

Information quality (InfoQual) 2.20 1.218

Interface quality (IntQual) 2.39 1.252

Overall, I am satisfied with this system. 2.17 1.169

Overall user satisfaction 2.24 1.314

6.6 Summary of findings

The norm of Autokeen production system in Line D has changed when the DVMS has been

applied and tested towards the real-time production system. This innovation has made the

participants gives most of the positive feedback. These feedbacks are related towards the

implementation that has made through DVMS by providing the Autokeen with the visual

planning tools that allow the management level can review the past production history, review

the performance of the operator, review the operator attitude, real-time watching the production

status in production floor, and communicating with the production floor through a visual

interface, meanwhile, the visual interface that was provided to the user in production floor is

handy and motivating them in terms of safety, time, and their performance.

Otherwise, some negative feedback was given towards moderator on some

functionalities of DVMS UI that might have some issues. As example, the operation interface

of DVMS the task review where the standard operation procedure (SOP) was not clear. Some

parts do not have the SOP, and the productivity rate of the operator seems to decrease whenever

the operator already speeds up the production. Meanwhile, in the management interface of

DVMS, the negative feedback was the complicated results that formed when acquiring the

production history data in the management interface. Otherwise, the smoothness of each

interface needs to increase as it slowing down the interaction process.

Outcomes of this evaluation study also listed out issues that need to be consider for

future work of DVMS in order to improve the DVMS, and the suggestions to address these

issues could be figured. The issues were ranked in priority: high, medium, and low. Table 6.7

listed highly, medium and low ranked issues with recommendations that need to be solve and

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undergo to make the DVMS works smooth and effectively with Autokeen real-time production

activity.

Table 6.7: Issues of concern and recommendations for the future development of Digital

Visual Management System (DVMS) at Autokeen.

No.

Issue

Issue

Priority

Issue Recommendation

1 High

Both management and operation

DVMS UI, the interfaces seem to slow

down when all the tasks have been

gone through. It keeps the management

interface crashing as it loads so many

data from databases.

Memory management of the

Python application need to be

done, so it will not consume

much memory.

2 High

In the operation interface, the value of

productivity rate seems not working

right, as the operator has increased their

performance, the number of

productivity rate did not raise much. As

time goes by, the number of

productivities keep decreasing even the

operator speed up the process.

Re-check the variable used to

calculate the Productivity rate

and improve it.

3 High

In the management interface, the

production history data does not

benefit much towards the user as the

visualized data seems to complex. Data

visualization need to improve to

increase the ease of understanding of

the production results.

From the current visualized

data, make it as a variable for

the complex data. Change the

data into graph or chart format,

so it helps the user to

understand easier.

4 Medium

Cover the DVMS into the inventory

area so that the management interface

can access the inventory data also. As

Broader the coverage of the

DVMS into the stamping area

in the Autokeen. The product

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now, the user needs to check manually

the amount of product left in the

inventory to planned the daily

production.

produced will be counted, thus

stored in the database. Then the

data can be access by DVMS,

and the user can manage the

industry through the one

system.

5 Medium

Currently, in the operation interface,

when the operator placing the panel to

the trolley where it allows them to

access the panel that is going to

assemble quickly, include in the cycle

time of the production.

The use of DVMS can details

up to every operation that the

operator is doing. Add the

button into the operator to

easily pause the system, and the

interface will change the status

of the worker loading the panel

onto the trolley

6 Low

The visibility of the DVMS operation

interface does not cover many people

on the production floor. If the operator

is going to the toilet or taking a break

too long, if the status in the DVMS

operation user interface is displaying

over a big screen where everything is

visualized, the operator will not be

wasting time and focusing 100%

towards the production activity.

A big LED screen where it is

displaying the status of the cell,

where the operator can see from

far that the cell that he is

operating is not operated.

6.7 Summary

In this chapter, the results and evaluation for the development of Digital Visual Management

System (DVMS) have been explained. It starts with the results from the interview and

observations from the early site visit where the aims were to figure out the visual management

practises that has applied to the Autokeen. After that, the development processes of DVMS

was explained. Then, this chapter starts to presenting the usability test results from heuristic

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evaluations, user-based testing method where different scenarios have been set up and the

structured usability questionnaire (PSSUQ) data. Finally, the summary of findings was

elaborating the results from this VM implementations, and some issues were figured out with

different priority. The future improvements will be explained later in chapter 7.

107

CHAPTER 7

Conclusion and Future Works

This thesis focused on improving visualization tools that will open the eyes of Autokeen

employees on how important the visual management (VM) application is towards managing

the production activity. Before the visual enforcement towards Autokeen has happened, the

employees seem not seriously considering how important the VM tools are around them. They

just thought it just works as a little guidance towards the employee and does not seem will

affecting the production activity of Autokeen. To answer the first research question, Autokeen

employee has not used much the visualization device around them. They were operating the

production by following the previous norm of working style. With the early DVMS

implementation, the employee seems stressed when using the system. But whenever they get

used to the DVMS, they seem found the system interested and enjoying using the system. They

can monitor their working activities through a digital device that they found attractive.

In addressing the second research question, the researcher has constructed a study plan

with following the evaluation process that focuses mainly on developing an interactive Digital

Visual Management System (DVMS). The study plan helps the researcher identify the best

visual elements that Autokeen employee use the most instantaneously, as this will allow more

interaction towards the DVMS. Otherwise, in the study plan, the researcher has planned an

iterative study where the UCD approach has become one method in developing the DVMS. A

multi development phase has helped the researcher identified the best visualization aspects

towards Autokeen as it highest engagement of users towards the development. So the

visualization aspects have been identified as the data according to the production operation

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108

performance according to specific information (location, time, operator). It also helps the

Autokeen to have a daily production planning wherein the management interface. It allows the

management team to schedule the tasks towards specific information (location, time, operator,

shift) with the option can edit later, which was very useful to Autokeen. Otherwise, DVMS

also helps Autokeen control the production performance by strengthening the safety element

in the system. Keeping the operator up-to-date with their performance as it used three different

elements to attract the operator (digital screen, sound system, LED light).

With the new Industry 4.0, the features promoted, such as smart sensors, smart

networks, etc. have helped develop DVMS. The operation interface has been processed over

the small device name Raspberry Pi that is used to process the visualization UI in the production

cell. It tends to visualize the production activity, visually managing the daily production

activity and visually controlling the operator's production activity in Autokeen Sdn. Bhd. It

helped track down the production status and allowed the management to monitor the activity

remotely over the network's linkage. This method was ordered to match the third research

question. The employees need to interact with the digitalized VM tools. This improvement has

improved the transparencies at the production of Autokeen. This is because the user interface

(UI) for operator shows the indicator on their current production rate; meanwhile, the UI for

management shows the working cell's real-time situation. Suppose the operator was taking a

break too long. In that case, the manager directly could see it through the DVMS UI for

management as these two UI always interacted and displayed the real-time Autokeen

production floor situation.

In order to make the system easy to use. The UCD processes have been done from early

of designing the DVMS. The iterative study was then followed to match the DVMS with

Autokeen surrounding. Various tasks in different scenarios related to the Autokeen production

activities have been created to help Autokeen employees identified their normal process over

the system. In the same time, the evaluation process including the usability test was handle to

check the user satisfaction over the DVMS. With this, the final research questioned can be

answered, and the objective of this research has been achieved. The Digital Visual Management

System has been designed and thrive.


109

7.1 Summary of contributions to Visual Management (VM) in Autokeen

This research mainly was developing the DVMS for Autokeen that is one of the automotive

stamping industries. The area for this research to be done is a production environment that has

a very lack of digital approach, and the production processes were scattered. It means the flow

of the products has not well constructed. The production processes were mainly done

conventionally. The operator was given a pile of the stamped panel and an empty pallet filled

with a specific amount of assembled panel. From this, the researcher was given user

requirements for developing the DVMS to helps the production activity more aggressive. The

intention of Autokeen in developing the DVMS was to motivate their operator regarding the

production activities. They want their operator to keep the productivity on-track. Otherwise,

production planning also could be improved with the development of the DVMS.

In developing effective DVMS, the researcher has conducted an iterative study where

it allows the user to judge the design for every phase. This iterative study contains three

different phases named initial phase, prototyping phase, and implementing phase. Two

different methods have been conducted over the iterative study. At the beginning of the study,

the UCD cycle was actively done towards the first two phases. The DVMS development used

the UCD technique to actively involve the users in the developing process, while the researcher

was getting feedback on the designed DVMS. With the UCD approach, the stakeholders and

users was allowed to judge the design to make the developed system user-friendly. Otherwise,

this method also helped the researcher gain a conventional visualization system and analyzed

it with the literature study.

The UCD cycle has been conducted multiple times to achieve the desired design for the

next evaluation process. The evaluation process included the usability test where user

satisfaction was obtained whenever the evaluation process was conducted. In the evaluation

study, the desired DVMS was running the usability test. The developed DVMS was brought

over the Autokeen, and the DVMS was mounted over the specified production cell in

Autokeen. After that, the DVMS then was tested towards the real-time production situation in

Autokeen. The users were asked to operate the DVMS and the specified usability test were

handled.

These approaches were to make sure the objectives of the study have been fulfilled the

researcher. The interactions of the user towards DVMS was developed from the evaluation

processes. This evaluation study's usability metrics results were acquired from the standard


110

questionnaire, the PSSUQ version 3 designated of high satisfaction rates. The mean for system

usefulness (SysUse) was 2.22, information quality (InfoQual) was 2.20, and interface quality

(IntQual) was 2.39, where it was using the 7-point Likert scale (where 1 strongly agrees).

Meanwhile, the average score for overall user satisfaction toward the solution varied between

2.24 and 2.80. Based on the PSSUQ version 3 questionnaire, these results show high user

satisfaction and reliable results. Otherwise, from the interview with the users in Autokeen and

stakeholders, they have satisfied with the developed DVMS.

In conclusion, the user demonstrated high satisfaction towards DVMS UI, which

indicates higher usability results. It also indicates that the chosen various methods on

developing and evaluating the DVMS by the UCD cycle and usability testing method were

successful. Also, the various methods delivered comparable outcomes, which recommends that

the instruments perform comparatively. The outcomes additionally show the successful

integration of visual management (VM) tools towards the Internet of Things (IoT) in managing

the production activity. These achievements help Autokeen efficiently manage its production

activity. At the same time, keep motivating their operator in operating the tasks that can also

be applied to other industries that can widen the globalization of industry.

7.2 Future works

In the future, the Digital Visual Management System (DVMS) will be one of the VM tools that

considering all the user needs. It allows managers of organizations to manage their production

activity. Meanwhile, the production activity is being controlled by the system. The employees

controlled by DVMS will feel motivated, and peace of mind has been offered to them. In short,

listed below on some criteria and issues raised from the research findings need to be resolve to

make DVMS successful in the future:

• Memory management of Python Application

• Re-evaluate the variable who control the productivity indicator

• Simplified the visualization of production history data

• Wider the coverage of DVMS (warehouse to quality check)

• Detailed the production timing

• Improve the screen size of DVMS and replicate the screen to cover the whole

production floor


111

• Allow the remote access of the DVMS for management

The issues were ranked in priority: high, medium, and low. There were three issues with a high

priority, two with medium priority and one with low priority. The high priority issues are the

important issues that need to be resolved for the DVMS to be worked successfully in the real-

time production situation without having a problem. In contrast, the medium issue is the

consideration for the system in redesign or modification to make the production activities more

effective as it will broaden the coverage of DVMS. The issues are not urgent for the low

priority, and they are mainly 'nice to have'. These issues are the recommendation for DVMS to

be working as the real production management system.

112

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Digitalization of Visual Management System (mieruka)