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SELECTION AND IMPLEMENTATION OF QUALITY CONTROL AND
IMPROVEMENT INITIATIVES: CASE STUDIES OF TWO MALAYSIAN
MANUFACTURING COMPANIES
SITI ARFAH BINTI HASHIM
A project report submitted in partial fulfilment of the requirement for the award of
the Degree of Master of Mechanical Engineering
Faculty of Mechanical and Manufacturing Engineering
Universiti Tun Hussein Onn Malaysia
FEBRUARY 2014
iii
For my beloved family
Khairul Anhar Bin Fathir@Fadzil, Nur Allesya Hana Binti Khairul Anhar and
Muhammad Aqeef Hazim Bin Khairul Anhar
iv
ACKNOWLEDGEMENTS
First of all, I am grateful to the All Mighty God, ALLAH for establishing me
to complete this research.
I would like to express my gratitude to my supervisor Dr Musli Bin
Mohammad for the useful comments, remarks and engagement through the learning
process of this master thesis. Furthermore I would like to thank participants in my
survey, who have willingly shared their precious time during the process of
interviewing. Also, I like to thank all the class members of the Faculty of Mechanical
and Manufacturing Engineering, UTHM for their help and encouragement. I also
thanks to my parents and in laws for their unceasing encouragement and support. I
would like to thank my loved ones, Khairul Anhar who have supported me
throughout entire process, both by keeping me harmonious and helping me putting
pieces together. I will be grateful forever for your love.
Finally, I also place on record, my sense of gratitude to one and all who
directly or indirectly have lent their helping hand in this research.
v
ABSTRACT
Quality Control and Improvement Initiatives (QCII) refer herein to
approaches, systems, tools and/or techniques and included, for example: Statistical
Process Control (SPC), Six Sigma, Design of Experiment (DOE), Failure Mode and
Effect Analysis (FMEA) and Acceptance Sampling. Unfortunately, there is a
relatively lack of guidance available to organisations on how to select and implement
appropriate QCII according to the context. In addition, very limited study has been
found on the selection and implementation of multiple QCII in Malaysian
manufacturing companies. The objectives of this study are to (1) identify the main
QCII currently being used by the case companies, (2) investigate the processes
involved in selecting and implementing multiple QCII, and (3) propose a framework
for selecting and implementing QCII. Research approach used is case study,
involving two Malaysian manufacturing companies. Main data collection method
used is interview. The main QCII currently being implemented by the case
companies are Quality Improvement Team, 8D Problem Solving Technique, Quality
Gates, Failure Mode and Effect Analysis, Process Control Plan and Work
Instruction. Based on case study data and literature review, a framework for selecting
and implementing QCII has been developed. The framework summarises six main
steps for selecting and implementing QCII which involved: (1) Diagnose current
situation and performance, (2) Identify area(s) for improvement, (3) Identify and
understand relevant QCII, (4) Select appropriate QCII, (5) Implement the QCII, and
(6) Monitor progress and evaluate performance.
vi
ABSTRAK
Inisiatif Kawalan dan Penambahbaikan Kualiti (QCII) merujuk kepada
pendekatan, sistem, alat dan/atau teknik dan termasuklah, sebagai contoh: Kawalan
Proses Statistik (SPC), Six Sigma, Reka Bentuk Eksperimen (DOE), Analisis Kesan
dan Mod Kegagalan (FMEA) dan Pensampelan Penerimaan. Namun begitu, secara
umumnya masih kurang garis panduan kepada organisasi tentang bagaimana untuk
memilih dan melaksanakan QCII yang sesuai mengikut konteks. Di samping itu,
sangat terhad kajian yang telah dibuat berkaitan pemilihan dan pelaksanaan pelbagai
QCII dalam syarikat-syarikat perkilangan di Malaysia. Objektif kajian ini adalah
untuk (1) mengenal pasti QCII utama yang sedang digunakan oleh syarikat kajian,
(2) menyiasat proses yang terlibat dalam memilih dan melaksanakan pelbagai QCII,
dan (3) mencadangkan satu rangka kerja untuk memilih dan melaksanakan QCII.
Pendekatan penyelidikan yang digunakan ialah kajian kes, yang melibatkan dua
syarikat perkilangan di Malaysia. Kaedah pengumpulan data yang digunakan ialah
sesi temuduga. QCII utama yang sedang dilaksanakan oleh Naza Automotive
Manufacturing Sdn Bhd (NAM) dan SAM Engineering & Equipment (M) Berhad
adalah Pasukan Peningkatan Kualiti, Teknik Penyelesaian Masalah 8D, ‘Quality
Gates’ Analisis Mod dan Kesan Kegagalan, Pelan Kawalan Proses dan Arahan
Kerja. Berdasarkan data kes kajian dan kajian literatur, satu rangka kerja untuk
memilih dan melaksanakan QCII telah dibangunkan. Rangka kerja ini meringkaskan
enam langkah utama untuk memilih dan melaksanakan QCII yang melibatkan: (1)
Kenal pasti keadaan semasa dan prestasi, (2) Kenal pasti peluang untuk
penambahbaikan, (3) Kenal pasti dan memahami QCII, (4) Memilih QCII sesuai, (5)
Melaksanakan QCII, dan (6) Memantau kemajuan dan menilai prestasi.
vii
CONTENTS
TITLE i
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENTS iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xi
ABBREVIATIONS xii
LIST OF APPENDICES xiii
CHAPTER 1 INTRODUCTION 1
1.1 Introduction to the chapter 1
1.2 Background of the study 1
1.3 Problem statement 2
1.4 Objectives of study 3
1.5 Scopes of study 3
1.6 Importance of study 4
1.7 Outline of the study 4
CHAPTER 2 LITERATURE REVIEW 5
2.1 Introduction to the chapter 5
2.2 Definition of Quality 5
2.3 Overview of Quality Control 7
2.4 Overview of Quality Improvement 8
2.5 Quality Control and Improvement Initiatives 8
viii
2.5.1 Statistical Process Control (SPC) 10
2.5.2 Design of Experiment (DOE) 11
2.5.3 Failure Mode and Effect Analysis (FMEA) 12
2.5.4 Six Sigma 13
2.5.5 Acceptance Sampling 13
2.5.6 Quality Function Deployment (QFD) 14
2.6 Previous studies related to quality control and
improvement initiatives 15
2.7 Conclusion to the chapter 17
CHAPTER 3 RESEARCH METHODOLOGY 18
3.1 Introduction to the chapter 18
3.2 Research approach 18
3.3 Research procedures/process 20
3.4 Data collection methods 22
3.4.1 Interviews 22
3.4.2 Observations 24
3.4.3 Document review 24
3.5 Conclusion to the chapter 25
CHAPTER 4 RESULTS AND DISCUSSION 26
4.1 Introduction to the chapter 26
4.2 Profile the case companies 26
4.2.1 Case 1: Naza Automotive Manufacturing
Sdn Bhd (NAM) 27
4.2.2 Case 2: SAM Engineering & Equipment (M)
Berhad 29
4.3 Profile of interviewees 31
4.4 Main quality control and improvement initiatives
Current being used by the case companies 33
4.4.1 Three Main QCII by Case Company 1 34
4.4.1.1 Quality Improvement Team (QIT) 34
4.4.1.2 Eight Disciplines (8D) 35
Problem Solving
4.4.1.3 Quality Gate 36
ix
4.4.2 Three Main QCII by Case Company 2 38
4.4.2.1 Failure Mode and Effect Analysis
(FMEA) 38
4.4.2.2 Process Control Plan 40
4.4.2.3 Work Instruction 41
4.4.3 The Strengths and Limitations of three main
QCII for both case companies 41
4.5 Processes involved in selecting and implementing
the quality control and improvement initiatives 44
4.5.1 Processes involved in selecting QCII 44
4.5.2 Processes involved in implementing QCII 45
4.6 Propose framework for selecting and implementing
the quality control and improvement initiatives 46
4.7 Conclusion to the chapter 50
CHAPTER 5 CONCLUSION AND RECOMMENDATIONS 51
5.1 Introduction to the chapter 51
5.2 Summary of the main research findings in relation to
the research objectives 51
5.3 Recommendations for future research 53
5.4 Conclusion to the chapter 53
REFERENCES 54
APPENDICES 61
x
LIST OF TABLES
Table 2.1 The approach, management systems, tools and
techniques for improving organisation performance 9
Table 2.2 Comparison between previous studies related to the
multiple improvement initiatives 15
Table 4.1 Significant Milestones of NAM 28
Table 4.2 Awards and recognition that have achieved by SAM
Engineering & Equipment (M) Berhad 30
Table 4.3 Profiles of the interviewees 31
Table 4.4 Three (3) main QCII currently being implemented by
the case companies 42
Table 4.5 The purposes, strengths and limitations of three (3) main
QCII for both case companies 34
Table 4.6 Steps involved in selecting and implementing QCII 47
xi
LIST OF FIGURES
Figure 3.1 Process involved in case study 19
Figure 3.2 Procedures for conducting research 21
Figure 4.1 Logo of NAM companies participated in this research 28
Figure 4.2 Logo of SAM companies participated in this research 29
Figure 4.3 Awards and recognition that have achieved by SAM
Engineering & Equipment (M) Berhad 29
Figure 4.4 Eight Disciplines (8D) Problem Solving Steps 36
Figure 4.5 Overview of a Stage-Gate System 37
Figure 4.6 Types of FMEA 39
Figure 4.7 Proposed framework for selecting suitable quality control
and improvement initiatives 46
xii
ABBREVIATIONS
8 D Eight Disciplines Problem Solving
DoE Design of Experiments
FMEA Failure Mode and Effect Analysis
NAM Naza Automotive Manufacturing
PQS Preferred Quality Supplier
QA Quality Assurance
QCII Quality Control and Improvement Initiatives
QFD Quality Function Development
QIT Quality Improvement Team
QMEA Quality Management Excellence Award
QSR Quality System Regulation
SOP Standard Operation Procedure
SPC Statistical Process Control
SSQA Standardized Supplier Quality Assessment
TCM Total Control Methodology
xiii
LIST OF APPENDICES
APPENDIX TITLE PAGE
A Example of Interview Question A 62
B Example of Interview Question B 66
C Naza Automotive Manufacturing
Sdn Bhd (NAM) 69
D SAM Engineering & Equipment (M)
Berhad 70
1
CHAPTER 1
INTRODUCTION
1.1 Introduction to the chapter
This chapter explains the background of study, problem statement, objectives, scopes
and importance of the case study.
1.2 Background of the Study
The pressure from globalisation has made manufacturing organisations moving
towards three major competitive arenas: quality, cost, and responsiveness. Quality is
a universal value and has become a global issue. In order to survive and be able to
provide customers with good products, manufacturing organisations are required to
ensure that their processes are continuously monitored and product qualities are
improved. Manufacturing organisation applies various quality control techniques to
improve the quality of the process by reducing its variability. A range of techniques
are available to control and improve product or process quality. These include Seven
Statistical Process Control (SPC) tools, Acceptance Sampling, Quality Function
2
Deployment (QFD), Failure Mode and Effects Analysis (FMEA), Six Sigma, and
Design of Experiments (DoE).
A few companies continue to emphasize only the inspection aspect of quality
control, whereas inspection is actually one useful element in an overall quality
system who stated by (Stephen, 2000). The quality control of company is very
important because of being the strategy that can bring:
i. Better quality as well as at incoming materials, production and assembly
parts until the finish goods before outgoing and delivery.
i. Better quality in term of saving cost or cheap with good quality due to apply
continuous improvement.
ii. Better providing the customer satisfaction, creating greater markets and thus
reducing overall cost resulting from improved quality is a reasonable measure
of the correctness of its application.
Key competitive business strategies include both achieving lower cost and
adding value through differentiation (Porter, 1980). Quality improvement is one
important way in which competitive performance may be achieved. Through this
strategy, if defects are eliminated or minimized, the cost of production due to waste
will decrease. Organisations are facing problems in selecting appropriate
improvement initiatives due to a plethora of initiatives currently available in the
market (Hendra, 2010, Thawesaengskulthai, 2010). Improvement initiative refers
herein to approaches systems, tool and/or technique and include, for example: Six
Sigma, Lean, Business Process Reengineering, ISO9001, and benchmarking (Van
der Wiele, Van Iwaarden, Dale & William, 2007).
1.3 Problem Statement
There is a myriad of initiatives that can be used to control and improve quality in the
production, such as Statistical Process Control (SPC), Acceptance Sampling,
ISO9001, Failure Mode and Effect Analysis (FMEA) and Benchmarking.
Unfortunately, there is a lack of clear understanding by people regarding why, where
and how to implement the initiatives. One reason may be due to lack of knowledge
in the field of quality control. Lack of disclosure and review of quality control will
3
cause this problem to continue happening. Strong knowledge of quality control will
facilitate a manufacturing company to determine the appropriate quality control
initiatives for every critical process. In addition, the implementation of the quality
control initiatives can be done in a better way. To address this issue, this project aims
to investigate the selection and implementation of Quality Control and Improvement
Initiatives (QCII) in Malaysia manufacturing companies.
1.4 Objectives of Study
The objectives of this study are:
i. Identify the main QCII currently being used by the case companies.
ii. Investigate the processes involved in selecting and implementing the
QCII.
iii. Propose a framework for selecting and implementing the QCII.
1.5 Scopes of Study
The scopes of this study are:
i. These studies are being carried out at two selected manufacturing
companies.
ii. Data are collected through interviews, document review, and observation
focussing on three main QCII implemented in the case companies.
1.6 Importance of Study
The importance area of study for selection improvement initiatives due to the
following main reasons:
4
i. Previous literature have highlighted the importance of selecting the right
initiative for a given contact or situation, such as Basu (2004), Francis
(2010), Hendra (2010), and Rigby and Bilodeau (2005). Selections
processes will help organisations doing the right things (Mohammad,
2012).
ii. Help Malaysian manufacturing companies to select and implement
appropriate quality control and improvement initiatives.
iii. To enrich the pool of case study materials and finding related to the
selection and implementation of quality control and improvement
initiatives.
1.7 Outline of the Study
There are five chapters in this thesis. The first chapter represents the background,
aims, objectives, scopes and importance of the research. Chapter 2 describes the
literature review on what has been highlighted by the previous researchers on the
QCII. Chapter 3 explains the research design and methodology being used. This
chapter will briefly explain on the research design, research procedures, and data
collection methods. Chapter 4 discusses the results and findings from the research..
Chapter 5 concludes the findings related to the aims and the objectives. It also
comprises the limitation of the research, and also the suggestion for future research.
5
CHAPTER 2
LITERATURE REVIEW
2.1 Introduction to the chapter
This chapter reviews the relevant literature and provides background which
underpins this research. It contains with definition of quality, overview of quality
control and quality improvement, quality control and improvement initiatives and
previous study related to quality control and improvement initiatives. Finally, it
concluded with a conclusion for this chapter.
2.2 Definition of Quality
Quality can be defined as fulfilling specification or customer requirement. A product
is said to be high in quality if it is functioning as expected and reliable. Quality is a
universal value and has become a global issue. Manufacturing organisations are
required to ensure that their processes are continuously monitored and product
qualities are improved in order to survive and be able to provide customers with
good products. By the ways, one of the most important tasks in any quality program
is to understand and evaluate the needs or expectations of the customer and then
6
provide products and services that meet or exceed those needs or expectations (Basu,
2004).
Quality is a significant element of production or services in keeping the
customers satisfied. There are different definitions and competing views of the term
quality by different people and the common element of the business definitions is
that the quality of a product or service refers to the perception of the degree to which
the product or service meets the customer's expectations. Crosby, (1979) defined
quality as the conformance to requirements or specifications and also suggested that
to manage quality adequately; it must be able to be measured. ISO 9000: (2000)
(cited in Vorley and Tickle, 2001) defined quality as the degree to which a set of
inherent characteristics fulfill requirements. Thus, the essential factors to Quality is
quality must be measurable, quality must be based on customer needs, quality should
be able to be edified with function ability and interchange ability (Mitra, 1998).
Three aspects are usually associated with the definition of quality: quality of
design, quality of conformance and quality of performance. Quality of design deals
with the stringent conditions that the product or service must minimally process to
satisfy the requirements of the customer. It implies that the product or service must
be designed to meet at least minimally the needs of the consumer (Mitra, 1998).
Quality of conformance implies that the manufactured product or the service
rendered must meet the standards selected in the design phase. With respect to the
manufacturing sector, this phase is concerned with the degree to which quality is
controlled from the procurement of raw material to the shipment of finished goods
(Mitra, 1998).
Quality of performance is concerned with how well the product functions or
service performs when put to use. It measures the degree to which the product or
service satisfies the customer. This is the final test of product or service acceptance
always lies with the customers (Mitra, 1998).
2.3 Overview of Quality Control
Quality control is a conventional way that businesses have used to manage quality.
Quality control is concerned with checking and reviewing work that has been done.
7
This is mainly done by inspection of products and services (checking to make sure
that what’s being produced is meeting the required standard) take place during and at
the end of the operations process. Juran (1988) defined quality control as the
regulatory process through which we measure that actual quality performance,
compare it with standards, and act on the difference. It is a more sophisticated
management tool aims at preventing goods and services which do not conform to
basic requirements from getting to the final consumer.
Quality control refers to activities to ensure that produced items are fulfilling
the highest possible quality. Most of tools and techniques to control quality are
statistical techniques. Quality control techniques can be classified into basic,
intermediate, and advance level, but there is no consensus among researchers in the
classification. For example, Xie and Goh (1999) consider DoE as an intermediate
level technique whereas Antony et al (1998) classified the technique as advanced.
Nevertheless, the content is more important than the classification. Among
the basic techniques are SPC. SPC is a statistical approach for assisting operators,
supervisors and managers to manage quality and to eliminate special causes of
variability in a process (Oakland, 2003). The initial role of SPC is to prevent rather
than identify product or process deterioration, but Xie and Goh (1999) suggest for its
new role to actively identifying opportunities for process improvement. The main
tools in SPC are control charts. The basic idea of control charts is to test the
hypothesis that there are only common causes of variability versus the alternative
that there are special causes. By continuously monitoring the process, the
manufacturing organisation could prevent defect items to be processed in the next
stage and to take immediate corrective action once a process is found to be out of
control (Hairulliza et al., 2005).
2.4 Overview of Quality Improvement
Improvement can define as the act or quality of improving or state of being
improved. FDA’s quality system regulation (QSR) and ISO 9000 encourage device
manufacture to incorporate continuous quality improvement process as a part of their
quality systems. The intent is always the same while companies have adopted
8
different methods to control design and manufacturing outcomes: quality
improvement.
Hitoshi Kume, a recipient of the 1989 Deming Prize for use of quality
principles, defines problems as “undesirable results of a job”. Work best efforts of
quality improvement when problems are addressed systematically using a consistent
and analytic approach, the methodology should not change just because the problem
changes. Keeping the steps to problem-solving simple allows workers to learn the
process and how to use the tools effectively.
2.5 Quality Control and Improvement Initiatives
Foley (2010) said performance of an organization need to be improved so that the
purpose of their existence can be met, and to satisfy and exceed customers,
employees, shareholders, supply chain partners, community and other stakeholder’s
expectations. To stay ahead of the market segment, organisational must strive to
increase faster than their competitors (Mohammad, 2012). In-depth knowledge in the
field of quality control and applied to facilitate the organization to compete and stay
ahead.
QCII can be defined as approach, management system, tool and technique
that can be used to control and improve quality (Mohammad, 2012; Van der Wiele
et. al., 2007). QCII are also known as management tools (Rigby & Bilodeau, 2005),
quality management and improvement initiatives (Thawesaengskulthai, 2007),
business process improvement methodologies (Bendell, 2005) and performance
improvement methods (Harrington & Lomas, 2000). Management gurus, academics
and/or practitioners are those that are developing this initiative (Baxter & MacLeod,
2008; Davenport et al., 2003; Greatbatch & Clark, 2005). Table 2.1 summaries the
definition and examples of approach, management system, tool and technique.
9
Table 2.1: The approach, management systems, tools and techniques for improving
organisation performance (Mohammad, 2012).
No Item Definition Examples
1 Approach
An approach needs resources (e.g. training,
hiring additional and specific personnel), senior
management commitment, strategic planning and
an “intellectual effort in term of its deployment
and adoption” (Van der Wiele et al., 2007, p.
561)
TQM, BPR, Six
Sigma, Lean
2 Management
System
“A system comprises written information in the
form of instructions and procedures in order to
direct and control some form of operation”
(Van der Wiele et al., 2007, p. 561).
Quality
Management
System
(ISO9000),
Environmental
Management
System
(ISO14000),
Occupational
Health and
Safety
Management
System
3 Tool
A tool can be “described as a device which has a
clear role and defined application. It is often
narrow in its focus and can be and is usually used
on its own” (Dale, 1993, as cited in Van der
Wiele et al., 2007, p. 562)
Cause and Effect
Diagram, Pareto
Diagram,
Control Chart,
Histogram,
Relationship
diagram,
Flowchart
4 Technique A technique “has a wider application than a
tool”. It requires “more thought, skill,
SPC,
Benchmarking,
10
knowledge, understanding and training to use
them effectively. A technique may even be
viewed as a collection of tools” (Dale, 1993, as
cited Van der Wiele et al., 2007, p. 562)
QFD, FMEA
Quality control is a topic pioneered by manufacturing sector. Nowadays, the field
has developed tremendously and its techniques, tools, concepts, and methodologies
can be applied widely in both service and manufacturing sectors. There are wide
available techniques to control product or process quality. The following sub-
sections explain several examples of the main quality control and improvement
initiatives. These initiatives are 7 Statistical Process Control (SPC) tools, Design of
Experiment (DOE), Failure Mode and Effect Analysis (FMEA), Six Sigma,
Acceptance Sampling and Quality Function Deployment (QFD).
2.5.1 Statistical Process Control (SPC)
Among the basic techniques are SPC. SPC is a statistical approach for assisting
operators, supervisors and managers to manage quality and to eliminate special
causes of variability in a process (Oakland, 2003). The initial role of SPC is to
prevent product or process deterioration rather than identify product or process
deterioration, but Xie and Goh (1999) suggest for its new role to actively identifying
opportunities for process improvement.
SPC involves using statistical techniques to measure and analyze the
variation in processes. Most often used for manufacturing processes, the intent of
SPC is to monitor product quality and maintain processes to fixed targets. Statistical
quality control refers to using statistical techniques for measuring and improving the
quality of processes and includes SPC in addition to other techniques, such as
sampling plans, experimental design, variation reduction, process capability analysis,
and process improvement plans (Montgomery, 2005).
The most comprehensive and detail studies of identifying SPC critical
success factors for SPC implementation was done by Antony et. al. (2001), Antony
11
et. al. (2000), Rungasamy et. al. (2001) and Antony and Taner (2003). Antony
identified and discussed the key ingredients for the successful implementation of
SPC in both manufacturing and service organizations. They identified 10 key
ingredients which are as follows: man4gement commitment and support, process
prioritisation and definition, selection of appropriate characteristics, define system
devices, selection of control charts, training and education, team world cultural
change and use of computer and software packages. In their continuing study on the
deployment of SPC, Antony and Taner (2003) reviewed and compared four existing
SPC implementation frameworks and proposed their conceptual framework for the
successful introduction and application of SPC program in organization.
2.5.2 Design of Experiment (DOE)
DoE and Taguchi methods are powerful tools for product and process development.
Taguchi methods, for instance, aim at making product or process that robust to
undesirable disturbances such as environmental and manufacturing variations.
However, the application of these two methods by industries is limited (Antony and
Kaye, 1995). Antony et al (1998) explore the difficulties in the application including
improper understanding and fear of statistical concepts in the methods, thus propose
a methodology for the implementation. Process capability study is an efficient
method to examine the capability of a process to produce items that meet
specifications. The method gains rapid growing interest due to increased use of
quality system QS9000, where use of process capability studies is requested
(Deleryd et al, 1999). The findings from capability study might require adjustment of
process using other statistical technique such as SPC or DoE. Capability studies
conducted by Motorcu and Gullu (2004) and Srikaeo et al (2005) show that the
machine tool and process capability and production stability was evaluated and
necessary steps to reduce poor quality production was carried out using other
statistical techniques.
There are various DOE techniques known as 'factorial' (complete or
fractionated), 'Taguchi', Plackett-Burmam, among others, but whenever possible a
method allows the experimental search of the influence of N variables and their
12
interactions. The statistical analysis of the results allows the determination of the
significance of the results and to obtain an experimental equation that relates the
variables and the results. It is often impractical to perform the experimental runs of
fractional factorial in completely random order. Bingham and Sitter (2001)
introduced that restrictions on the randomization of the experimental trials are
imposed and the design is said to have split-plot structure. Similar to fractional
factorials, the goodness of fractional factorial split-plot designs can be judged using
the minimum aberration criterion. However, from their studies, the split-plot nature
of the design implies that not all factorial effects can be estimated with the same
precision. In this paper, they discuss the impact of the randomization restrictions on
the design and also show how the split-plot structure affects estimation, precision,
and the use of resources. Besides that, how these issues affect design selection in real
industrial experiment was demonstrated.
Chantarat and Allen (2000) used simulation and assumptions from George
and McCulloch (1993) to evaluate the abilities of fractional factorial designs and
several analysis methods as well as popular designs on successfully identifying
important factors to achieve model identification-related objectives. Kasperski et al.
(1993), as well as analysis of variance followed by multiple t-tests. A new class of
fractional factorial design, including an unbalanced design, which directly
maximizes the probability of correct model identification, was proposed in this
study. The results confirm that the probability of identifying important factors is low
for commonly used approaches. New fractional factorial designs, derived from
simulation optimization, are proposed that maximize the probability of correct
selection.
2.5.3 Failure Mode and Effect Analysis (FMEA)
The FMEA was innovated by NASA in the 1960´s. This is a tool that in a structured
way helps to analyse and document complex problems. The FMEA is normally used
at an early stage in the product or process design life, but can also be used as a
corrective tool. It is widely used in for example the automotive and the aerospace
industry. FMEA is used to:
13
identify potential failure modes,
determine their effect on a product or process,
identify possible causes for the effect and
find solutions that eliminate the most critical failures.
FMEA is a powerful method to detect where exactly problems can occur and to
prioritise possible problems in the order of their severity (Dale et al., 2003). The tool
is useful to identify problems in product, i.e. design FMEA, as well as to trouble
shoot problems in process, i.e. process FMEA (Xie and Goh, 1999).
2.5.4 Six Sigma
Six sigma is also a statistical tool for ensuring defect free products through process
continuous improvement. The term six sigma originated at Motorola and many
inspired worldwide organizations have set goal towards a six sigma level of
performance (Breyfogle and Cupello, 2001). The application of six sigma has been
mainly used in manufacturing industry. An example of the use of six sigma in
nonmanufacturing industry is in software development (Mahanti and Antony, 2005).
Today, the six sigma is used worldwide, across continents, across different sector of
industry.
Pojasek (2003) said that:
“The six sigma philosophy maintains that reducing “variation” will help solve
process and business problems. By using a set of statistical tools to understand
the fluctuation of a process, management can begin to predict the expected
outcome of that process. If the outcome is not satisfactory, associated tools can
be used to further understand the elements influencing the process. Most six
sigma programs focus on process improvement. These efforts seek to eliminate
the causes of variation in processes while leaving the basic process intact.”
2.5.5 Acceptance Sampling
Acceptance sampling is another statistical technique to make a decision whether to
accept or reject a lot based on the information from sample. The application of
14
acceptance sampling allows industries to minimise product destruction during
inspection and testing, and to increase the inspection quantity and effectiveness. The
application of acceptance sampling has been mainly used in manufacturing industry
(Hairulliza, 2005). Similarly, its application in nonmanufacturing industry is widely
reported such as Thorpe et al. (1994), Gardiner and Mitra (1994) Bathika (2003) and
Slattery (2005).
2.5.6 Quality Function Deployment (QFD)
According to Rosenthal and Tatikonda (1992), it is a systematic approach for the
design of new products or services based on close awareness of customers desires,
coupled with integration of corporate functional groups. QFD is a set of planning and
communication techniques that focus and coordinate organizational capabilities in
order to develop products that closest meet customers’ needs. King (1989) defines
QFD as a system for designing product or service based on customer demands and
involving all members of the producer or supplier organization.
According to Hutton (1999) QFD, when implemented correctly, can bring
several benefits for both companies and their customers. The advantages of QFD are
listed below:
improved communication and sharing of information within a cross-functional
team responsible for developing a new product,
identification of weaknesses in the current knowledge of the design team,
the capture and display of a wide variety of important design information in one
place in a compact form,
support for understanding consensus, and decision making, especially when
complex relationships and tradeoffs are involved,
the creation of informational base which is valuable for repeated cycles of
product improvement.
As it can be observed, the benefits of implementing QFD methodology go far
beyond satisfying customers’ needs and gaining higher profit margins as well as
increasing market share. It provides a company with an opportunity to improve a
15
broad scope of its operations that reach far beyond the development of products, for
example it facilitates team work and knowledge sharing within organizations.
2.6 Previous Studies Related to Quality Control and Improvement Initiatives
Most of the previous studies only focused on one specific initiative, such as,
benchmarking (Adebanjo & Mann, 2008), ISO9000 (Bendell, 2000) and Six Sigma
(Antony, 2007). Each of these studies tends to promote the particular initiative and
goes into detail about the purpose, strengths, limitations and/or implementation
process of the initiative. Unfortunately, very limited studies have been found (such
as, Mohammad, 2012, Thawesaengkhultai, 2007 and Kwok & Tummala, 1996) to
address how to implement and manage multiple improvement initiatives in the
manufacturing companies. Table 2.2 summarise three previous studies related to
multiple improvement initiatives.
Table 2.2: Comparison between previous studies related to the multiple improvement
initiatives
Author(s) Methodology Main Outcomes/Findings Limitations
Mohammad (2012) Global
exploratory
survey
17 experts
interview
conducted in
Malaysia,
Singapore and
New Zealand
Evaluation
survey
Document
review
- A guidance model for
selecting organizational
improvement initiatives was
developed using acronym of
GUIDE which represents the
five key steps to select
improvement initiatives: (1)
Goal setting; (2) Understand
relevant improvement
initiatives; (3) Identifying
decision criteria; (4)
Deciding on the appropriate
initiative, and (5) Evaluating
Focuses on the
decision making
process in
selecting
appropriate
improvement
initiatives. Does
not cover the
adoption and
maintenance of
initiatives.
16
the decision.
- The proposed GUIDE
model is one of first to focus
on holistic processes to be
used in selecting
improvement initiatives
whereby it contents are
explicitly aligned to
Business Excellence Models
such as Baldrige Criteria for
Performance Excellence.
- Part of the GUIDE model
consist of a framework that
shows the examples of 30
main improvement
initiatives that can be
adopted towards BE by
narrowing down the option
according to the areas of
implementation and
organisational maturity.
Thawesaengkhultai
(2007)
Literature review
Case studies –
conducted in
Thailand
Interviews with
experts –
conducted in
Thailand
A decision aid for
selecting quality
management and
improvement initiatives.
Only focus on
six initiatives:
TQM, Six
Sigma, ISO
9001, Lean,
Business Process
Reengineering,
and Business
Excellence.
Kwok & Tummala
(1996)
Literature review
Consulting
experiences
A quality control and
improvement system
based on total control
methodology to integrate
isolated quality control
tools.
Only focus on
quality control
tools used by the
companies in
Hong Kong.
17
Based on a literature review has been made, it can be concluded that there is
very limited available case study focuses on the selection and/or execution of quality
control and improvement initiatives in Malaysian manufacturing companies. It is
likely that the case studies and in-depth knowledge related to this issue in Malaysia
is still lagging. Applying appropriate quality control and improvement initiatives is
one of crucial steps to improve the production system and product quality in the race
of globalization. To prosper and always be on top, the manufacturing companies
must constantly improve the quality of their operation and products.
2.7 Conclusion to the Chapter
Based on the literature review that has been made, it is found that there are various
types of QCII used in manufacturing industry today. Among these are the SPC,
DOE, FMEA, Six Sigma, and Acceptance Sampling. This initiative aims to improve
the quality of use of a product produced apart from getting useful feedback from
customers.
18
CHAPTER 3
RESEARCH METHODOLOGY
3.1 Introduction to the chapter
In this chapter, it explains the research methodologies that were used for supporting
the analysis of the study. Some of the elements in methodology include the study
plan, flowchart of the research, and data collection methods.
3.2 Research Approach
This research has been conducted using case study approach. Two manufacturing
companies involved in this study.
A case study is the problem of narrative about something that can be resolved
through appropriate methods. The problems that can be solved through case study
might be likely including a special, unique or interesting thing involves organization,
process, people, or even things. (Yin & Robert, 2003).
Yin (2003) said that”
“a case study design should be considered when: (a) the focus of the study is to
answer “how” and “why” questions; (b) you cannot manipulate the behaviour
of those involved in the study; (c) you want to cover contextual conditions
19
because you believe they are relevant to the phenomenon under study; or (d)
the boundaries are not clear between the phenomenon and context.”
The information gained from a case study might provide a much more detailed
compared to the other methods. It also allows to presents the data collected from
multiple methods in order to strengthen the ideas towards the conclusion. The
method could be find through several sources such as project documents, project
reports, monitoring visits, mystery client reports, facility assessment reports,
interviews, questionnaire/survey results, evaluation reports, and observation (Yin &
Robert, 2003).
The steps in doing a case study might be different from one another. But
basically there are some main processes involved that must be included to make sure
that the result from the case study is reliable. The main processes involved as in
Figure 3.1.
Figure 3.1: Process involved in case study
It is important to have a systematic plan before conducting the case study.
Part of the planning processes involved identifying potential case companies,
contacting potential case company and finalizing the case companies that willing to
participate in this research. Planning process is very important in a case study. This
20
is because, with the planning process structured and organized, it will facilitate a
method to run. How to collect the necessary data will be more easily and quickly.
Further ways to analyze the data to be more systematic and effective.
Subsequently, a data collection instrument has been developed. There are
three methods used in collecting data. Firstly, through interviews with industry
representatives ranging from the quality manager and followed by three employees
who perform or carry out three quality control tools. The second method is through
observation. This observation is like looking at the state of the industry in terms of
quality control and also see how people who are responsible for implementing a
quality control of the work. The last method used is through the document reviews.
Documents are as magazines, industry web site, Standard Operation Procedure
(SOP), newsletters and others. Once all the data has been collected, the final process
is to analyze the data.
3.3 Research Procedures/Processes
These research procedures/processes are shown in Figure 3.2. First of all, the case
companies are identified. The application to industry visit being preceded to confirm
the manufacturing industry for the study. When it gets approval from the case
company, the preparation for visits in detail are done. Design data collection
instruments (questionnaire) are made to ease the process while in the industry. This
is in preparation so that there are no problems will occur during the interview and
observation sessions on case studies conducted. So, till the stage of data collection,
an observation for the data whether in control limit specification or out of the
standard using different of tools. Besides, some of the measurements need to be
carried out for getting the data.
A visit to the case companies have done twice to do interviews and
observations to obtain information related to the study. At the first visit, is the first
interview conducted on the manager, people who selected the QCII. Observations
were also made at various levels in the application of quality control set. Second visit
are made to interviews the persons who are implementing the QCII. The second visit
carried over to improvements to the data collected and the study. This step shows the
21
quantity of the data measurements has been carried out whether is enough for the
research.
Figure 3.2: Procedures for conducting research
At the stage of data analysis, it will concern to analysis some of the data that
has been measured achieved the numbers of acceptance or not. If the data analyzed
Start
Identify case companies
Obtain approval from the case companies
Result & Discussion
End
1st visit to the company + Interview manager / people involved in
selecting QCII
Design data collection instrument (Questionnaire)
2nd visit to the company + Interview people involved in implementing QCII
Data Analysis
22
do not meet the objectives set, then it will be performed again to get the correct and
accurate data. Result and discussion was made on the data obtained.
3.4 Data Collection Methods
Data of the study are collected through interviews, observations and document
review.
3.4.1 Interviews
An interview is a series of questions a researcher addresses personally to
respondents. An interview may be structured (where ask clearly defined questions)
or unstructured, where allow some of questioning to be led by the responses of the
interviewee. Semi-structured interviews were used in this study. It was one of the
sources in the data collection of a case study. Semi-structured interview was also
known as qualitative interviews (Saunders, 2009).
Interviews are a useful method to investigate issues in an in depth way. It
discovers how individuals think and feel about a topic and why they hold certain
opinions. Besides that, interviews can investigate the use, effectiveness and
usefulness of particular library collections and services. It also informs decision
making, strategic planning and resource allocation. A sensitive topic which people
may feel uncomfortable discussing in a focus group is also a useful method of
interviews. Interviews also add a human dimension to impersonal data and deepen
understanding and explain statistical data.
In this interview, researchers may give a set of written questions about the
research, record the interview session using audiotape, or transcribe the interview.
There are several types of interviews such as face-to-face, focus group, online focus
group, and telephone interviews (Saunders, 2009). Face-to-face interview was used
for this research. The interviews were conducted in two phases:
23
1st Phase Interview
Respondents for 1st phase interview are people who involved in the selection of
QCII in the case company such as Quality Manager and General Manager.
The interview questions are attached in Appendix A. As shown in Appendix
A, the questions asked during the 1st phase interview are: company profile, work
background, the list of quality control and improvement initiatives currently being
implemented, three main initiatives being implemented, key process involved in
the selection of the initiatives, person in charge for three main initiatives,
purposes, strengths and limitations of the three main initiatives, main challenges
faced and how to overcome the challenges.
For the first interview, a formal approach is for people who were interviewed
were from the upper classes. It is much to get information about the QCII
selection itself. An appointment has been made with the Quality Manager of each
company for an interview. The meeting enables to get as much information about
quality control selecting and implementation in the company. A list of questions
has been prepared prior to the company visit as a guidance to get the information.
The interviews with the Quality Manager and factory visit take about two to three
hours for each company.
2nd
phase interview
Interviewees for 2nd
phase interview include executives, engineers and/or
technicians who are involved in the implementation of three main QCII. The
interview questions are attached in Appendix B. As shown in Appendix B, the
questions asked during the 2nd
phase interview are: key processes involved in
implementing the initiatives; purposes, strengths and limitations of the three main
initiatives; main challenges faced; how to overcome the challenges.
An appointment has been made with the people who are in charge with the
quality control tool of each company for an interview. The interviewing enables
to get as much information about quality control implementation in the company.
A list of questions has been prepared prior to the company visit as a guidance to
24
get the information. The interviews with the engineer and technician and also
another factory visit take about two to three hours for each company.
3.4.2 Observations
Observation is an action or process of observing something or someone carefully or
in order to gain information. In this case study, the observation is to see how the
person in charge does the work to achieve the established quality control and
improvement initiatives. Through observation, the data obtained is through observing
the workers in industries undergoing their daily lives at work wrought. It was
obtained during visits to industrial environments after interviews held. During this
session, the questions and the problems that arise will be recorded and planned to
find an answer in order to facilitate the process of report writing.
Often, during the interviews, a lot of things that cannot be remembered by the
people interviewed. Therefore, this very important observation is done so that all the
remaining data can be recorded. In the other word, in an interview situation or in
response to a questionnaire item, a person may not always provide accurate or
complete information, or they might answer in ways that correspond to what is
socially desirable. There is a recognised source of bias in self-report techniques
referred to as a 'social desirability set', which means that in many spheres of social
life there are socially desirable ways of behaving and, consciously or unconsciously,
individuals will tend to respond in that way, although in the 'real world' they might
behave differently.
3.4.3 Document Review
Document review is a way of collecting data by reviewing existing documents.
Documents are as magazines, industry web site, Standard Operation Procedure
(SOP), newsletters and others. Through the study of these documents, many
54
REFERENCES
Ambartsoumian, V., Dhaliwal, J., Lee, E.T., Meservy, T., Zhang, C., (2011).
“Implementing Quality Gates Throughout the Enterprise IT Production
Process,” Journal of Information Technology Management, vol. XXII,
Number 1.
Antony, J., M. Kaye, & A.Frangou, (1998). A strategic methodology to the use of
advanced statistical quality improvement techniques. The TQM Magazine,
10(3), pp.169-176.
Antony, J. Balbontiru A & Taner,T. (2000). Key ingredients forthe effective
implementation of Statistical Process Control, Work StuSt, a9(6): 242-247.
Antony, J. & Taner, T. (2003). A conceptual framework for the effective
implementation of statistical process control, Busines s Process Management,
9(4): 47 3 489.
Basu, R.(2004). Implementing Quality: A practical guide to tools and technique.
London: Thomson
Baxter, L. F. & MacLeod A. M. (2008). Managing performance improvement. New
York: Routledge.
Bendell, T (2005). Structuring business process improvement methodologies. Total
Quality Management & Business Excellent. 16(8-9), 969-978.
55
Bingham, D.R. & R.R. Sitter. (2001). Design Issue in Fractional Factorial Split-Plot
Experiments. K.S.A.M. 5: 67-85.
Bosch, V.G. & Enriquez, F.T. (2005). “TQM and QFD: exploiting a customer
complaint management system”, International Journal of Quality &
Reliability Management, Vol. 22 No. 1.
Breyfogle, F.W.III & J.M.Cupello, (2001). Managing Six Sigma: A Practical Guide
to Understanding, Assesing and Implementing the Strategy that Yield Bottom-
Line Success. John Wiley and Sons, New York.
Chantarat, N & T.T. Allen. (2000). Fractional Factorial Designs that Maximize the
Probability of Identifying Active Factors. M.A. thesis, Louisiana State
University, Baton Rough, Louisiana.
Charvat, (2010). J. P. How to Use Quality Gates to Guide IT Projects.
http://articles.techrepublic.com.com/5100-10878_11-1061893.html.
Cooper, R. G. (1990). Stage‐Gate Systems: A New Tool for Managing New Products
‐ Conceptual and Operational Model. Business Horizons, May‐June.
Crosby, P. B., (1979), „Quality is Free: The Art of Making Quality Certain, New
American Library, New York, NY: Penguin
Dale, B.G., H.S., Bunney, & P. Shaw, 2003.Quality management tools and
techniques: an overview. In Dale, B. G. (ed): Managing Quality (4th
Edition). Blackwell, Oxford.
Deleryd, M., R. Garvare, & B. Klefsjo, 1999. Experiences of implementing statistical
methods in small enterprises. The TQM Magazine, 11(5), pp.341-350.
Foley, K. J. (2010). Third generation quality management: From atoms to bits, or
quality management in the knowledge society. Paper presented at the
56
QUALCON 2010 International Conferences in Quality Management,
Canberra.
Francis, F (2010). One hundred to one. Quality World. 36(1), 26-31.
George & McCulloch. (1993). Keyfinder-A Complete Toolkit Generating Blocked
and/or Fractional-Replicate Factorial Designs. Technometrics. 35: 379-387.
Greatbatch, D. L. & Clark, T. (2005). Management speak: Why we listen to what
management gurus tell us. London: Routledge.
Hairulliza, M.J (2005). Some Experiences of Quality Control Implementation in
Malaysian Companies. European Journal od Scientifics Research.
Harrington, H. J. & Lomas, K. C. (2000). Performance Improvement Methods:
Fighting the war of waste. New York, NY: McGraw Hill Inc.
Hendra, I (2010). Horses for courses – picking your winner when it comes to quality
improvement systems. In. L Nickoloff, New Zealand.
Hutton, David (1999). Quality Function Deployment: A Practitioners Notes.
Available on World Wide Web:<URL:
http://www.dhutton.com/visitors.html>. Retrieved 01.07.09.
Hyder, Almas (1995). “SPEL Experience of Quality Circles” Pakistan‟s 1st
International Convention on Quality Control OCT 7-9, 1995.
Ingle, Sud (1988). Quality Circles Master Guide: Increasing Productivity with
People. Prentice Hall of India Pvt. Ltd., New Delhi-11001
Juran, J. M., & Gryna, F. M., (1988), „Juran‟s Quality Control Handbook‟, McGraw-
Hill Book Company New York, NY.
57
Kamble, S. B. (2012). Eight Discipline (8D‟s) Steps to Solve Industrial Quality
Problem, International Conference on Technology and Business
Management, Mumbai India.
Kasperski, Weissfeld & Dong. (1993). The Design of Experiments. 9th ed., Hafner
Publishing Company, New York.
King, Bob (1989). Better Designs in Half the Time: Implementing QFD Quality
Function Deployment in America. Methuen, Massachusets: GOAL/QPC.
Kwok, K. Y. & Tummala, V. M. R. (1996). A quality control and improvement
system based on the Total Control Methodology (TCM). International
Journal of Quality & Reliability Management, 15(1) 13-48.
Leach, Desmond J., Christopher B.Stride & Stphen J. Wood (2006). The
Effectiveness of Idea Capture Schemes. International Journal Of Innovation
Management Vol.10, No.3, 325-350 Imperial College Press
Lucas, (1998). Manufacturing Systems Engineering Handbook, Engineering &
Systems, Mini Guide, UK.
Mahanti, R. & J. Antony, (2005). Confluence of six sigma, simulation and software
development. Managerial Auditing Journal, 20(&), pp. 739-762.
Mann, R., Mohammad, M., & Agustin, M. T. A. (2012). Implementing Business
Excellence: A guidebook for SMEs. Retrieved 11 July, 2012, from
http://www.apo-tokyo.org/coe/files/Implementing-Business-Excellence.pdf
Marjanca Krajnc, (2012). With 8D method to excellent quality. Journal of Universal
Excellence, Professional Article No. 3, pp. 118–129.
Mitra, M (1998). Fundamentals of Quality Control and Improvement. Prentice Hall.
58
Mohammad, M. (2012). Development of the guidance model for the selection of
Organisational Improvement Initiative.(Doctoral Thesis). Massey University,
Palmerston North, New Zealand.
Montgomery, D. C. (2005). Introduction to Statistical Quality Control. Wiley.
Motorcu, A. R. & A.K. Gullu, 2004. Statistical process control in machining, a case
study for machine tool capability and process capability. Materials and
Design, 27, pp. 364-372.
Oakland, J.S. (2003). Statistical Process Control, 5th ed., Oxford: Butterworth-
Heinemann.
Porter, M. (1980), Competitive Strategy, Free Press, NY.
Pojasek, R.B. (2003). “Selecting Your Own Approach to P2.” Environmental
Quality Management, 12(4) 85-94.
Prajapati, Dr. D. R. (2012). Implementation of Failure Mode and Effect Analysis: A
Literature Review. International Journal of Management, IT and Engineering,
Volume 2, Issue 7.
Rigby, D & Bilodeau, B (2005). The Bain 2005 Management Tool Survey. Stratergy
& Leadership. 33(4), 4-12.
Rosenthal, Stephen R. & Mohan U. Tatikonda (1992). Competitive Advantage
Through Design Tools and Practices. In: Susman Gerald I. (1992).
Integrating Design and Manufacturing For Competitive Advantage. New
York, Oxford: Oxford University Press.
Rowley, J. (2002), “Using case studies in research,” Management research news.
Vol.25. No.1, pp. 16-27.
59
Rungfisanafham, M, Anderson,J. & Dooley, K. (1997). Conceptualizing
organizational implementation and practice of Statistical Process Contol,
Journal of Quality Management, 2(l) : 1 13 - 137
Saunders, M., Lewis, P., & Thomhill, A. (2009), Research methods for business
students, 4th ed., Financial Times Prentice Hall, Harlow.
Schmitt, R. (2009). Governing the Process Chain of Product Development with an
Enhanced Quality Gate Approach. CIRP Journal of Manufacturing Science
and Technology 1, pp. 206–211.
Schneider, R. (2004). Quality Gates: A New Device for Evaluation in Cross-Lingual
Information Retrieval. In Proceedings of the LREC-2004 Workshop of
Transparency and Integration in Cross-Lingual Information Retrieval,
Lissabon, Portugal.
Siemen (2013). Teamcenter Electronics Work Instruction. Siemens PLM Software.
Siemens Product Lifecycle Management Software Inc.
Srikaeo, K., J. E., Furst, & J. Ashton, (2005). Characterization of wheat-based
biscuit cooking process by statistical process control techniques. Food
Control, 16, pp. 309-317.
Stuart, I., McCutcheon, D., Handfield, R., McLachlin, R. & Samson, D. (2002),
“Effective case research in operations management: a process perspective,”
Journal of Operations Management, Vol. 20, pp. 419-433.
Subramanian, G. (ed.). (1995). Quality assurance in environmental monitoring.
Instrumental methods. VCH, Weinheim, New York.
Thawesaengskulthai, N. (2007). Selecting quality management and improvement
initiatives: Case studies in industrial in Thailand (Doctoral thesis).
60
Thawesaengskulthai, N. (2010). An empirical framework for selecting quality
management and improvement initiatives. International journal of quality and
reliability management.
Van der Wiele, A., Van Iwaarden, J. D., Dale, B. G., & Williams, A. R. T. (2007).
Improvement approaches. In B. G. Dale, A. Van der Weile & J. Van
Iwaarden (Eds.), Managing Quality (5th ed., pp. 559-575). Malden, MA:
Blackwell Publishing.
Van der Wiele, Van Iwaarden, Dale & William, (2007). Self-assessment, models and
quality awards. Managing Quality. Malden: MA Blackwell Publishing.
Vorley, G., & Tickle, F., (2001) „Quality Management, Principles and Techniques‟,
4 ed. Guildford, Quality Management and Training Publication Ltd
Xie, M., X.S. Lu, T.N. Goh, and L.Y. Chan,(1999). A quality monitoring and
decision-making scheme for automated production processes. International
Journal of Quality and Reliability Management, 16(2), pp.148-157.
Yin, R.K. (2003), Case study research: design and methods, 3rd ed, Sage, London.
Younack, R. (2010).“Quality Gates in Solution Projects,” RCG Information
Technology.
