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UNIVERSITI TEKNIKAL MALAYSIA MELAKA ASSESSING A SYSTEM RELIABILITY: A CASE STUDY IN ARM REAR AXLE ASSEMBLY This report submitted in accordance with requirement of the Universiti Teknikal Malaysia Melaka (UTeM) for the Bachelor of Manufacturing Engineering (Manufacturing Management) (Hons.) by NUR AWALIAH BINTI ABD RAHMAN B051110140 920706-10-6192 FACULTY OF MANUFACTURING ENGINEERING 2015

UNIVERSITI TEKNIKAL MALAYSIA MELAKA - eprints.utem.edu.myeprints.utem.edu.my/16596/1/Assessing A System Reliability A Case Study...DECLARATION . I hereby, declared this report entitled

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UNIVERSITI TEKNIKAL MALAYSIA MELAKA

ASSESSING A SYSTEM RELIABILITY: A CASE STUDY IN ARM

REAR AXLE ASSEMBLY

This report submitted in accordance with requirement of the Universiti

Teknikal Malaysia Melaka (UTeM) for the Bachelor of Manufacturing Engineering

(Manufacturing Management) (Hons.)

by

NUR AWALIAH BINTI ABD RAHMAN

B051110140

920706-10-6192

FACULTY OF MANUFACTURING ENGINEERING

2015

UNIVERSITI TEKNIKAL MALAYSIA

MELAKA BORANG PENGESAHAN STATUS LAPORAN PROJEK SARJANA MUDA

TAJUK: Assessing a System Reliability: A Case Study in Arm Rear Axle Assembly

SESI PENGAJIAN: 2014/15 Semester 2 Saya NUR AWALIAH BINTI ABD RAHMAN mengaku membenarkan Laporan PSM ini disimpan di Perpustakaan Universiti Teknikal Malaysia Melaka (UTeM) dengan syarat-syarat kegunaan seperti berikut:

1. Laporan PSM adalah hak milik Universiti Teknikal Malaysia Melaka dan penulis. 2. Perpustakaan Universiti Teknikal Malaysia Melaka dibenarkan membuat salinan

untuk tujuan pengajian sahaja dengan izin penulis. 3. Perpustakaan dibenarkan membuat salinan laporan PSM ini sebagai bahan

pertukaran antara institusi pengajian tinggi.

4. **Sila tandakan ( )

SULIT

TERHAD

TIDAK TERHAD

(Mengandungi maklumat yang berdarjah keselamatan atau kepentingan Malaysia sebagaimana yang termaktub dalam AKTA RAHSIA RASMI 1972)

(Mengandungi maklumat TERHAD yang telah ditentukan oleh organisasi/badan di mana penyelidikan dijalankan)

Alamat Tetap:

NO.1 Jalan 6,

Taman Bukit Belimbing Indah,

45000 Kuala Selangor, Selangor.

Tarikh: ________________________

Disahkan oleh:

Cop Rasmi: Tarikh: _______________________

** Jika Laporan PSM ini SULIT atau TERHAD, sila lampirkan surat daripada pihak berkuasa/organisasi berkenaan dengan menyatakan sekali sebab dan tempoh laporan PSM ini perlu dikelaskan sebagai SULIT atau TERHAD.

DECLARATION

I hereby, declared this report entitled “Assessing A System Reliability: A Case Study in

Arm Rear Axle Assembly” is the results of my own research as cited in references.

Signature : ……..............................

Author’s Name : Nur Awaliah binti Abd Rahman

Date : ……..............................

APPROVAL

This report is submitted to the Faculty of Manufacturing Engineering of UTeM as a

partial fulfillment of the requirements for the degree of Bachelor of Manufacturing

Engineering (Manufacturing Management) (Hons.). The member of the supervisory

committee is as follow:

…………………………………………..

(Professor Madya Dr. Lukman Sukarma)

i

ABSTRACT

This study aims at assessing System Reliability in manufacturing industry.

This takes place in the arm rear axle assembly of factory A. The problems

arise when the workers need to do other works while waiting the robot to

function again. The problem occurs when one of the robot frequently abruptly

terminates during the process. Thus, the research was conducted to improve

poor reliability of robots as well as the reliability of system.

Times to failure were recorded based on historical data. The life data analysis

was conducted based on the survival data. The objective is to assess the

reliability of robots in the assembly system. In contrast, the series

configuration is identified in order to assess reliability of the system. The

prediction based on statistical method analysis was applied by analyzing the

result of the life data analysis and identifying the causes of failures. The

application in Minitab was used as a tool to predict the lifetime of the robot

instead to measure the survival probabilities of the individual failure mode

that give effect to the performance of reliability system. In conclusion, the

improvement was made by analyzing the failure mode and made suggestion

regarding on conducting and maintaining the robot in the system.

ii

ABSTRAK

Kajian ini bertujuan untuk menilai Sistem Kebolehpercayaan dalam industri

pembuatan. Ini berlaku di lengan pemasangan gandar belakang kilang A. Masalah

timbul apabila pekerja perlu melakukan kerja-kerja lain sementara menunggu robot

berfungsi semula. Masalah ini berlaku apabila salah satu robot yang sering tiba-tiba

menamatkan semasa proses tersebut. Oleh itu, kajian ini dijalankan untuk

meningkatkan kelemahan dari segi kebolehpercayaan robot dan kebolehpercayaan

sistem.

Kali kegagalan direkodkan berdasarkan data terdahulu. Analisis data hidup telah

dijalankan berdasarkan data jangka hayat. Objektifnya adalah untuk menilai

kebolehpercayaan robot dalam sistem pemasangan. Sebaliknya, konfigurasi siri

tersebut dikenalpasti untuk menilai kebolehpercayaan sistem. Ramalan berdasarkan

analisis kaedah statistik telah digunakan dengan menganalisis hasil daripada analisis

data hidup dan mengenal pasti punca-punca kegagalan. Aplikasi dalam Minitab telah

digunakan sebagai alat untuk meramalkan jangka hayat robot selain adalah untuk

mengukur kebarangkalian jangka hayat bagi mod kegagalan secara individu yang

memberi kesan kepada prestasi sistem kebolehpercayaan. Kesimpulannya,

peningkatan itu dibuat dengan menganalisis mod kegagalan dan membuat cadangan

mengenai mengendalikan dan mengekalkan robot dalam sistem.

iii

DEDICATION

I dedicated this research to my beloved family, lecturers and friends whose have

encouraged and inspired me in complete this project.

iv

ACKNOWLEDGEMENT

In the name of Allah, the most gracious, the most merciful, I would like to express

my gratitude to the people who directly or indirectly involved during the preparation

and after I successfully manage to complete this PSM project.

First and foremost, I would like to thank Prof Madya Dr. Rizal bin Saleh, (Dean of

Faculty of Manufacturing Engineering) and special thank to my dedicated and

committed PSM supervisor, Prof Madya Dr. Lukman Sukarma for his excellence

guidance and encouragement. I also like to show my gratitude to the Mr. Nor

Akramin B. Mohamad, Mr. Muhammad Syafiq B. Syed Mohamed, Dr. Effendi B.

Mohamad, Dr. Isa B. Halim as PSM I and PSM II examiners, and all the PSM

Committee for their fully support and commitment.

I also want to express my appreciation and thanks to all my beloved families for their

support especially Miss Nor Linda Binti Daud, for her advice and valuable

information. Not to forget to Mr. Fahmi B. Ismail and all my friends who those really

help in giving and sharing their idea, comment, supportive, and encouragement.

Thank you for all of you.

v

TABLE OF CONTENT

Abstrak i

Abstract ii

Dedication iii

Acknowledgement iv

Table of Content v

List of Table ix

List of Figures x

List Abbreviations, Symbols, and Nomenclature xii

1. INTRODUCTION 1

1.1 Background of the study 1

1.2 Problem Statement 3

1.3 Objectives 4

1.4 Scope of the study 5

1.5 Structure of Project 5

2. LITERATURE REVIEW 7

2.1 Manufacturing system 7

2.2 Machine configuration 8

2.2.1 Series configuration 9

2.2.2 Parallel configuration 10

vi

2.2.3 Combination of Series and Parallel 11

2.2.4 Complex System 12

2.3 Definition of reliability 12

2.4 Purposes of system reliability 15

2.5 Lifetime distribution 16

2.5.1 Exponential distribution 17

2.5.2 Weibull distribution 17

2.5.3 Normal distribution 18

2.6 Failure Analysis 19

2.6.1 Failure mode and effect analysis (FMEA) 20

2.6.2 Fault tree analysis (FTA) 20

3. METHODOLOGY 22

3.1 Flow chart of conducting the PSM I and PSM II 22

3.2 Phase 1 24

3.2.1 Define the problem statement 24

3.2.2 Establish Objective and scope 25

3.2.3 Literature review on related topic 25

3.2.4 Identify the system and method 25

3.3 Phase 2 26

3.3.1 Data Collection 26

3.3.2 Assess the distribution and evaluate the system 27

3.3.3 Analysis of result 27

3.3.4 Discussion 27

vii

3.3.5 Conclusion and Recommendation 28

3.4 Methodology the objective of the study 28

3.4.1 Methodology for objective 1 28

3.4.1.1 Data Collection 29

3.4.1.2 Plot the distribution by Minitab software 30

3.4.1.3 Statistical data analysis 30

3.4.1.4 Make prediction on each robots’ lifetime 32

3.4.1.5 Measure and analyze the reliability system configuration 32

3.4.2 Methodology for objective 2 32

3.4.2.1 Classified the failure mode into individual failure modes 33

3.4.2.2 Identify the most critical individual failure mode 34

3.4.3 Methodology for objective 3 34

3.4.3.1 Further study regarding to avoid the failure 35

3.4.3.2 Make corrective action 35

4. RESULT AND DISCUSSION 36

4.1 Data of the time to failure 36

4.1.1 Historical data of welding robot 1 37

4.1.2 Historical data of welding robot 2 38

4.2 Choice of Distribution Model 39

4.2.1 Probability plot for time to failure 39

4.2.2 Distribution ID Plot 41

4.3 Parametric Distribution Analysis 42

4.4 Characteristic of distribution 47

4.4.1 Survival Plot for time to failure 49

viii

4.4.2 Survival Probabilities of Normal distribution 50

4.4.3 Statistical term 50

4.4.3.1 Reliability of each welding robot 51

4.4.3.2 Reliability of the system 52

4.5 The Parametric Distribution Analysis with multiple failure modes 53

4.5.1 Individual failure mode of welding robot 1 55

4.5.2 Probability plot of the individual failure modes 59

4.5.3 Table survival probabilities of individual failure mode 60

4.5.4 Interpretation of processing failure mode 62

5. CONCLUSION 65

REFERENCES

APPENDICES

A Gantt Chart for PSM 1

B Gantt Chart for PSM 2

C Historical data of process welding (Part A)

D Historical data of process welding (Part B)

ix

LISTS OF TABLES

4.1 The historical data of welding robot 1 37

4.2 The historical data of welding robot 2 38

4.3 The classification of failure modes 54

4.4 Verification of each causes of the failure 63

x

LIST OF FIGURES

1.1 Frequency number of repairs for six month (Month) 4

2.1 Configuration illustrating Product Layout 9

2.2 Active redundant system 10

2.3 The standby redundancy 11

2.4 k-out-of-m redundancy 11

2.5 Complex System 12

2.6 The life phase 14

3.1 Methodology flow chart 23

3.2 Methodology flow chart of objective 1 29

3.3 Example of Minitab Statistical Software Screen 30

3.4 The example of the distribution selection 31

3.5 Methodology flow chart of objective 2 33

3.6 Methodology flow chart of objective 3 34

4.1 The selection of distribution 39

4.2 Probability plot of graph from three distribution for welding robot 1 40

4.3 Probability plot of graph from three distribution for welding robot 2 40

4.4 The output of Goodness-of- Fit for welding robot 1 in the session window 41

4.5 The output of Goodness-of-Fit for welding robot 2 in the session window 41

4.6 Parameter distribution analysis 42

4.7 Probability plots for time to failure of welding robot 1 43

4.8 Table of percentiles of welding robot 1 44

4.9 Probability plot for time to failure of the welding robot 2 45

4.10 Table of percentile of welding robot 2 45

xi

4.11 Estimates Parameter of the welding robot 1 46

4.12 Estimates Parameter of the welding robot 2 47

4.13 Characteristic of distribution of the welding robot 1 48

4.14 Characteristic of distribution of the welding robot 2 48

4.15 Survival plot from characteristic of distribution of welding robot 1 49

4.16 Survival plot from characteristic of distribution of welding robot 2 49

4.17 The normal distribution 50

4.18 The mean value to obtain reliability welding robot 1 51

4.19 The mean value to obtain reliability welding robot 2 52

4.20 Table of survival probabilities of the welding robot 1 53

4.21 Table of survival probabilities of the welding robot 2 53

4.22 Failure mode column 55

4.23 The distribution analysis for equipment 56

4.24 The distribution analysis for man 57

4.25 The distribution analysis for processing 58

4.26 The probability plot of the individual failure modes 59

4.27 The table of survival probabilities for equipment 60

4.28 The table of survival probabilities for man 60

4.29 The table of survival probabilities for processing 61

4.30 The table of survival probabilities for equipment, man and processing 61

xii

LIST OF ABBREVIATIONS

CMS - Continuous Manufacturing System

CMS - Cellular Manufacturing System

WIP - Work-In-Progress

PDF - Probability Density Function

CDF - Cumulative Distribution Function

MTTR - Mean Time To Failure

MRL - Mean Residual Life

FMEA - Failure Modes and Effects Analysis

FTA - Fault Tree Analysis

MTBF - Mean Time Between Failures

PSM - Projek Sarjana Muda

ID - Individual Identification

ADJ - Anderson – Darling statistic value

ML - Maximum Likelihood

CI - Confidence Interval

IQR - Interquartile Range

Q1 - First Quartile

Q3 - Third Quartile

TIG - Tungsten Inert Gas

1

CHAPTER 1 INTRODUCTION

This chapter provides a review about the project entitled “Assessing a System

Reliability: A Case Study in the Arm Rear Axle Assembly”. These include an

overview of the concept and importance of a system reliability focusing in the

system of arm rear axle assembly process. Background study, problem statements,

objectives and scopes of this study are discussed in the following segments.

1.1 Background of the Study

Generally, manufacturing industry refer to sector areas which involve in the

processing of raw materials, commodities, components, or parts into finished goods

for sale to fullfill the market demand or as intermediate goods used in the production

process. Manufacturing commonly employs human labour, machines, and tools on a

large scale. The continuous flow of machine run is important to produce products or

outputs to meet customers expectation. Any interruptions due to breakdown and

stoppage machine will effect the flow of the production process. Each machine is

characterized by three parameters which are: a) the processing time, b) time between

failures and c) time to repair (Tezcan, 2001). Thats mean, the ability of machine to

perform its function went smoothly without interruption due to fail and takes time to

repair in shorter processing time. The great quality of the products will be produced

as the performance of machines run efficiently. Thus, the manufacturers will gain

higher profit from the sale of quality products produce.

2

Derivation the product probability law of series component was initiated during the

analysis of the missile system by Robert Lusser. The theorem concerns about the

overall systems functioning only if all the components are functioning and is valid

under special assumptions. To make up the system, it reviews that the reliability of

such system is equivalent to the product of the reliability of the individual

components (Rausand and Hoyland, 2004a). From this situation, it explains that the

production of the product in the system will stop and influence the quality of product

as well due to the poor reliability of the machine. The reliability is measured by

analyse the failure rate of machine and on how often does it fail during a certain

amount of time.

The purpose of system reliability is to prevent failures that affect the operational

capability of the system. According Jolly and Wadhwa (2004a), the consequences of

the failure of a system were always considered in the term of ‘reliability’. Thus, the

rate of failure or failure probability of machine in the system need to be measured

during the data collection under specified time for customer requirements

compliance. The system reliability is important to ensure that the failure probabilities

are reduced and failure detection capability needs to be increased.

According to the research made by Coolen (2008a), stated that the purpose and the

reliability theory had been practiced in statistics as it most commonly used as a

parametric probability distribution. By using a statistical method, basic probability

concepts such as random variable and distribution need to define based on the failure

rate data of the machine and measurement will emerge with lifetime distribution.

Thus, operational of the machine during production process in the entire system

needs to be observed. The measurement of machine configuration in the system need

to relate with the concept reliability model.

3

To assess a system reliability of this study, one entire process system in

manufacturing plant of Factory A has been chosen. Factory A is a manufacturing

industry that provides robotic and machinery to join and assembled metal automotive

component. One process of the assembly system in factory A will be selected and the

mapping of the welding robots in the system will be observed and measured. The

assembly process of arm rear axle is chosen since the one of the welding robot in the

system is frequently abruptly stop. This stoppage of the robot is due to unreliable

robot being used in the entire process. Thus, the aim of this study is to assess the

reliability of the system by applying statistical method. Based on the results of this

assessment, this study will emerge with suggestions to improve the reliability of the

system.

1.2 Problem statement

The main problem of this research study is the poor reliability of the robots in a

system of the production process in Factory A. In the arm rear axle assembly

process, it found that one of the robotic welding is frequently abruptly stop as shown

in the Figure 1.1. This event occurs for six months which is caused by the high

failure probabilities of the welding robots in assembly system. The inability of the

welding robot to perform its function during assembly process causes the

performance of the system to be low and the workers need to do other works while

waiting the robot to function again.

4

Figure 1.1: Frequency number of repairs for six month (Month)

This will effect the efficiency of the operation process and consequently reduce the

overall performance of the system to assemble the arm rear axle. Thus, the series

configuration of welding robots is identified through the flow of assembly process in

the entire system. The two types of welding robots are conducted to assemble the

metal automotive components which is the arm rear axle. Factory A has to maintain

their robotic welding in highly reliable conditions in order to be able to struggle in a

highly competitive global.

1.3 Objectives

a) To measure and assess the reliability of each machine as well as the

reliability of the system under study.

b) To identify the causes of failures of the machine in a system that prevent a

system from perform a required function.

c) To give suggestion for improvement of system reliability based on the

identification of failure.

654321

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Month

Fre

qu

en

cy

Number of repair (month)

5

1.4 Scope of the study

This research is limited to one assembly system in the manufacturing plant of

Factory A. Only the flow of the component assembly through the mapping of

welding robots in that process system will be studied. The process of arm rear axle

assembly is selected in this study which involve between two welding robots in

series configuration. The life data analysis of each welding robot in the system is

obtained. The lifetime distribution will be measured by using failure data in that

process. The distribution will be studied using reliability prediction and modelling.

Thus, the reliability of each robot needs to be improved to enhance the system’s

safety, quality and operational availability.

1.5 Structure of Project

The organization for this thesis according to the format in Projek Sarjana Muda 1

and 2 stated as below:

Chapter 1: Introduction

This chapter includes the background of relevant topic, problem statement,

objectives, scope and limitation.

Chapter 2: Literature review

This chapter begins with a review of machine configuration and its capability in

manufacturing system. Concepts, definition, purposes of a system reliability

assessment in manufacturing industry focusing in the production line and followed

by the application of lifetime distribution based on statistical method are explained in

this chapter.

6

Chapter 3: Methodology

This chapter states the flow chart that carried out for the whole process of the

methodology. Next, the data collection that includes the primary resources and

second resources that obtained from production department of factory A is shown to

aid in the problem analysis. The analysis techniques and tools are also summarized

in this chapter.

Chapter 4: Result and Discussion

This chapter covers the reliability system and each welding robot based on the

chosen life data distribution. The statistical method and parameter estimation are

applied to get the result. The system data are collected and analyzed to obtain the

connection between quantified failure modes that affect the system reliability.

Chapter 5: Conclusion

This chapter will conclude the research findings. The manufacturer can predict the

lifetime of each machine based on the statistical method approach. The corrective

planning and continuous improvement will be highlighted to improve the efficiency

of the welding robot processing.

7

CHAPTER 2 LITERATURE REVIEW

This chapter provides a review of the concepts machine configuration that related to

the concept, definition, purposes of a system reliability assessment in manufacturing

industry focusing in the production line. Besides, this chapter also defines and

explains the failure and lifetime term of the component, machine and equipment in

the system that tend to relate with the research study using statistical methods

regarding to exponential, normal distribution and so on. The failure analysis also is

explained in order to define the reliability prediction of the system as well.

2.1 Manufacturing system

Machineries is a very common word in manufacturing process, especially for higher

rate of production output (Subramaniam et al., 2009). The machine capabilities are

needed to produce products during production runs. Machinery investments are high

and costly, therefore industries try to exploit their usage to maximize profit.

Reliability plays a major role within the overall performance of a producing system.

The reliability is especially related to the machines in production system as its

capability to produce product in large quantities in manufacturing. Thus, reliability

of of machines tools influences the whole manufacturing effectiveness and stability

of equipment in the production system (Liu et al., 2014). The study on the reliability

life data analysis in a manufacturing system at the time of machine operated

8

successfully or before it failed showed that the key factor in most of the performance

systems is that reliability of machine (Sun et al., 2007a).

Li and Meerkov (2000) stated that the problem of production variability in

manufacturing system is related to unreliable machine. Based on the Bernoulli

statistics of machine reliability are assumed, unreliable production line also generate

three problems which are the production variance, the constant demand satisfaction

and the random demand satisfaction problems. These problems also are caused as the

long lines smooth out of production and reduce its variability. Based on their study,

the number of parts are produced by the system is a random variable due to machine

breakdown during a fixed interval of time. This shows that its expected value and

variances characterize the production volume and variability respectively. In general,

the production variances only gives theoretical characterization of the production

variability.

2.2 Machine configuration

The system-level reliability of a manufacturing system affected by the machine

configuration selection as it gives a great impact on it. (Sun et al., 2007b). System-

level reliability also is resulted from the unpredictable machine breakdown and

improper maintenance decisions that affect the products quality and tools

degradation.

The reliability of the system needs to be determined either the components in the

systems are series, parallel or mixed systems in series and parallel. The system in

series is the weakest linking or connectivity in the system. The interconnection of the

equipment is in terms of the contribution of component failure gives effect to the

system. This is define that if one of the component fails, the overall system fails. In

contrast, the system in parallel is refer to as a redundant system.