The relation between six sigma barriers and aerospace tier 1 suppliers

Investigating the barriers that would affect the success of implementing Six
Sigma in a relationship with quality management maturity in the Aerospace
Tier 1 Supply Chains, and finding solutions to avoid these barriers
Submitted by: Shadi Saffour
Supervised by: Edward Walker
Student ID# 8202549
A dissertation submitted to Coventry University
in partial fulfilment of the requirements for the degree of MASTER OF SCIENCE
IN
ENGINEERING AND MANAGEMENT
Coventry University
January 2019

i
Declaration
Declaration of Originality
This project is all my own work and has not been copied in part or in whole from any
other source except where duly acknowledged. As such, all use of previously
published work (from books, journals, magazines, internet, etc.) has been
acknowledged within the main report to an item in the References or Bibliography lists.
I also agree that an electronic copy of this project may be stored and used for the
purposes of plagiarism prevention and detection.
Copyright Acknowledgement
I acknowledge that the copyright of this project and report belongs to Coventry
University.
Signed: Shadi Saffour Date: 06 January 2019

ii
Acknowledgements
I would like to extend my thanks and giving this project for everyone who helped me
to reach this stage, in first place my parents who were tired with me since childhood
to help me reach this stage in the best way and, of course my supervisor Edward
Walker, for his patience, advice and endless support he gave to me, to help me finish
this research. Also, I would like to acknowledge the contribution from respondents that
added to my thinking and supported this research.
Thank you all, it would not be done without you.

iii
Abstract
In this research, the barriers to the successful implementation of Six Sigma in
aerospace Tier 1 suppliers in relation to quality management maturity will be
investigated. There are some common barriers to Six Sigma, and their degree of
importance varies in relation to the quality management maturity of a company.
Research Objective
The main objective of this research is to examine the barriers to successful
implementation of Six Sigma. Moreover, the research will identify the common
barriers, rank them, and explain how they affect the quality maturity level of any
company.
Research Methods
Primary and secondary research methods were used to collect data. Primary data
were collected using a questionnaire survey. Six respondents from different
companies with different levels of experience replied to the questionnaire. Secondary
data were collected through a literature review.
Findings
A set of common barriers was identified and ranked.
Keywords: Six Sigma, Barriers to Six Sigma, Quality Management Maturity, Supply
Chain, Aerospace

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Contents
Declaration......................................................................................................................................... i
Acknowledgements........................................................................................................................... ii
Abstract ........................................................................................................................................... iii
List of Figures ................................................................................................................................... vi
List of Tables ....................................................................................................................................vii
Chapter 1 Introduction................................................................................................................... 1
1.1 Research Background......................................................................................................... 1
1.2 Research Aim, Objectives, and Questions........................................................................... 2
1.3 Research Hypothesis.......................................................................................................... 3
1.4 Dissertation Structure ........................................................................................................ 3
1.5 Rationale behind the Research........................................................................................... 4
Chapter 2 Research Methodology................................................................................................... 1
2.1 Introduction....................................................................................................................... 1
2.2 Research Design................................................................................................................. 1
2.3 Research Strategy: Qualitative Research ............................................................................ 3
2.4 Research Ethics .................................................................................................................. 4
2.5 Data Collection................................................................................................................... 4
2.6 Data Analysis...................................................................................................................... 6
2.7 Project Management.......................................................................................................... 7
Chapter 3 Literature review.......................................................................................................... 13
3.1 Introduction..................................................................................................................... 13
3.2 Six Sigma.......................................................................................................................... 13
3.2.1 Definition and critical features.................................................................................. 13
3.2.2 Reported Benefits of Six Sigma Implementation ....................................................... 15
3.2.3 DMAIC Methodology................................................................................................ 16
3.2.4 Six Sigma Hierarchical Structure ............................................................................... 17
3.3 Tier 1 Aerospace Industry Suppliers.................................................................................. 18
3.4 Barriers to Six Sigma Project Implementation and the top five barriers: ........................... 19
3.4.1 Barriers to Six Sigma Project Implementation ........................................................... 19
3.4.2 Top five common barriers......................................................................................... 24
3.5 Quality Maturity Model.................................................................................................... 25
3.5.1 Purpose of Quality Maturity Model .......................................................................... 26
3.5.2 Overview of Maturity Approaches ............................................................................ 26

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Chapter 4 Results and Analysis ..................................................................................................... 28
4.1 Questionnaire Survey Responses...................................................................................... 28
4.2 Quality Management System Definition Analysis.............................................................. 28
4.3 Six Sigma Definition Analysis ............................................................................................ 28
4.4 Questionnaire Analysis..................................................................................................... 29
4.4.1 Quality Management Maturity ................................................................................. 29
4.4.2 Questionnaire Responses ......................................................................................... 31
Chapter 5 Discussion .................................................................................................................... 45
5.1 Hypothesis....................................................................................................................... 45
5.2 Research Limitations........................................................................................................ 46
5.2.1 Barriers .................................................................................................................... 46
5.2.2 Research Design....................................................................................................... 47
5.2.3 Analysis.................................................................................................................... 47
Chapter 6 Conclusion.................................................................................................................... 48
6.1 Research Question........................................................................................................... 48
6.2 Research Objectives......................................................................................................... 48
6.3 Future Research............................................................................................................... 49
References ...................................................................................................................................... 50
Appendix A...................................................................................................................................... 59
Questionnaire Survey Questions.................................................................................................. 59
Appendix B...................................................................................................................................... 71
Six Sigma Roles and Responsibilities ............................................................................................ 71

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List of Figures
Figure 2.1: The Research Process ‘Onion’........................................................................................... 1
Figure 3.1: Six Sigma DMAIC process ............................................................................................... 17
Figure 3.2: The Quality Management Maturity Grid......................................................................... 27
Figure 3.3: The Quality Management Process Maturity Grid ............................................................ 27
Figure 4.1: Bar chart of Quality Management Maturity.................................................................... 29
Figure 4.2: Results bar chart of participants’ age.............................................................................. 31
Figure 4.3: Bar chart of responses on work status............................................................................ 31
Figure 4.4: Bar chart of responses on qualification........................................................................... 32
Figure 4.5: Results bar chart of responses to length of service......................................................... 32
Figure 4.6: Bar chart of responses to time in current job role........................................................... 33
Figure 4.7: Bar chart of responses to whether the respondents had a Six Sigma role ....................... 34
Figure 4.8: Bar chart of responses to awareness of quality management......................................... 34
Figure 4.9: Bar chart of responses to awareness of Six Sigma........................................................... 35
Figure 4.10: Bar chart of responses to company sector.................................................................... 35
Figure 4.11: Bar chart of responses to number of employees........................................................... 36
Figure 4.12: Bar chart of responses to global reach of company ...................................................... 36
Figure 4.13: Bar chart of responses to supply chain tier category..................................................... 37
Figure 4.14: Bar chart of responses to Six Sigma implementation requirement................................ 37
Figure 4.15: Bar chart of responses to importance of Six Sigma ....................................................... 38
Figure 4.16: Bar chart of responses to the company having an established system .......................... 39
Figure 4.17: Bar chart on satisfaction with Six Sigma........................................................................ 40
Figure 4.18: Bar chart on responses to number of people in Six Sigma............................................. 40
Figure 4.19: Bar chart on responses to provision of Six Sigma training ............................................. 41
Figure 4.20: Bar chart on responses to company engagement with Six Sigma.................................. 41
Figure 4.21: Bar chart on responses to Six Sigma being considered in project planning strategy ...... 42
Figure 4.22: Bar chart on response to clear understanding of how Six Sigma contributes to profits.. 42
Figure 4.23: Bar chart on response to ranking Six Sigma barriers ..................................................... 43

vii
List of Tables
Table 2.1: Project plan....................................................................................................................... 8
Table 2.2: Risk mitigation plan......................................................................................................... 10
Table 3.1: Reported benefits and savings from Six Sigma in the manufacturing sector ..................... 15
Table 4.1: Crosstabulation with counts for leadership as a barrier and quality management maturity
categories........................................................................................................................................ 30
Table 4.2: Requirement of implementing Six Sigma by suppliers compared with quality management
maturity .......................................................................................................................................... 38
Table 4.3: Weighted score and overall ranking of barriers following analysis ................................... 44

Introduction Chapter 1
1
Chapter 1 Introduction
1.1 Research Background
According to Thomas (2018), the aviation industry represents the safest form of travel
owing to the high standards of safety implemented within this field. Moreover, a study
conducted by Deloitte (2018) on the global aerospace and defence (A&D) industry
which is about studying how aircrafts manufacturing whether civil or military has been
advanced with time, reveals that the industry has grown by 4.1% in 2018, yielding
revenues of about US $491.9 billion in 2016 and the US $502.3 billion in 2017, with a
2.1% increase in turnover. According to the same study report, the A&D industry is
expected to grow by 3% between 2017 and 2022, with revenues crossing US$ 2 trillion
by 2022. Clearly, this rapid expansion in the aerospace industry creates challenges in
meeting the high level of standards for quality with regard to the suppliers. Such
challenges include sourcing of raw materials, mitigating supply disruption risks, coping
with modernisation and emerging technologies, and a shortage of skilled workers
(Brand, 2017).
Companies have utilised quality management approaches since the 1930s, resulting
in the development of quality management systems (QMS) (Dahlgaard-Park, 2011).
A QMS is a formal structure that contains the procedures, methodologies, and duties
concerning meeting the necessary policies and objectives by focusing on the
organisation's processes to meet client and management demands (Asq.org, 2018).
The AS9100 (1999) standard, based on the ISO9001 standard (British Standards
Institution, 2018), was established in December 1998 by the aerospace industry when
the International Aerospace Quality Group (IAQG) carried out critical enhancements
in quality and lowered the costs throughout project processes (SAE International,
1999). Due to the rapid expansion within the aerospace industry, aircraft
manufacturers and airlines started looking for other ways to improve the quality of
aeroplanes and relevant services (Khaled, 2013).
According to Crosby (1979, as cited by Sower et al., 2005), quality can be estimated
by cost, or, in other words, the expense of doing things wrong. Sower et al. (2005)
noted that the cost of quality could be divided into prevention, appraisal, internal
failure, and external failure costs, often referred to as PAF (prevention, appraisal, and

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failure). The following cost definitions (Campanella, 1990) show the importance of
quality and how it affects the production costs:
• ‘prevention costs: the costs of all activities specifically designed to prevent poor
quality in products and services (p. 22);
• appraisal costs: the costs associated with measuring, evaluating, or auditing
products or services to assure conformance to quality standards and
performance requirements (p. 23);
• internal failure costs: the costs resulting from products or services not
conforming to requirements or customer/user needs (which) occur prior to
delivery or shipment to the customer (p. 23); and
• external failure costs: the costs resulting from products or services not
conforming to requirements or customer/user needs (which) occur after delivery
or shipment of the product, and during or after furnishing of a service to the
customer’ (p. 23).
1.2 Research Aim, Objectives, and Questions
This research aims to study the barriers affecting the success of Six Sigma
implementation in relation to quality management maturity in aerospace tier 1
suppliers and to find possible solutions. To achieve these aims, the following
objectives are outlined:
• Identify Six Sigma and quality management maturity concepts
• Identify the tier 1 supply chain of the aerospace industry
• Identify the barriers to the successful implementation of Six Sigma from the
literature review
• Identify how these barriers are ranked against each other both in the
literature and from primary research
• Analyse the impact of quality management maturity on the ranking
Based on a review of the literature concerning this topic, the following research
questions were established:
1. How would these barriers affect the success of a project with the
implementation of Six Sigma within tier 1 suppliers of the aerospace
industry?

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2. How can quality management maturity be measured?
3. How can the barriers be ranked based on their critical effect on Six Sigma
implementation?
4. What is the relation between quality management maturity and Six Sigma
barriers?
5. How can these barriers be overcome in the future?
1.3 Research Hypothesis
Based on the initial thoughts the research has about Six Sigma and its barriers from
literature, he some common themes that drove his interest which led to the
development of the following hypotheses:
1. Barriers to Six Sigma implementation.
2. Quality Management Maturity can be measured using various tools.
3. Some barriers are more important than others based on their impact to Six
Sigma implementation.
4. The Quality Management Maturity of a company can be identified by linking it
with the impact of the barriers.
5. Suggested solutions to reduce the impact of the barriers.
1.4 Dissertation Structure
Chapter One is followed by Chapter Two, which outlines the research methods and
the findings in the literature review as well as presents the data collection and analysis
methods. Chapter Three presents the existing literature on Six Sigma relevant to this
study, including Six Sigma’s main features, the methodology for deploying a Six Sigma
project, barriers to successful Six Sigma implementation as identified by previous
authors, Quality Management Maturity (QMM), and aerospace tier 1 suppliers.
Chapter Four presents the findings obtained from the survey. Chapter Five discusses
the findings from Chapter Four and compares them with the literature review findings.
Finally, Chapter Six concludes with a review of the research aim and objectives and
provides some practical implications and limitations of this study.

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1.5 The rationale behind the Research
Nonthaleerak and Hendry (2008) state that it is essential for the academic network to
carry on researching the Six Sigma phenomenon, given its role in the industry.
Academic research is required to ‘develop an additional in-depth, scientific
understanding of Six Sigma and separate fact from fiction’ (Schroeder et al., 2008,
p.537). Additionally, Nonthaleerak and Hendry (2008) mention the need for more
definitive experimental proof that enables making determinations on issues, for
example, strengths and weaknesses of the Six Sigma approach.
Aboelmaged (2011) identified the major barriers to Six Sigma implementation by
conducting a questionnaire survey and proposed that further research should enhance
the questionnaire data by utilising different techniques, for example, case study or
longitudinal data, in order to provide in-depth comparative experiences related to the
barriers to Six Sigma implementation in various settings or time periods. However,
owing to the nature of this research, survey and cross-sectional data were used in this
research. The author also suggests a constructed procedure approach that focuses
on boundaries related to each stage of the process through which a Six Sigma project
is executed. By outlining the QMM model and boundaries of Six Sigma project
implementation, it is possible to search for connections between these barriers and
QMM.
In this sense, by identifying the necessity of additional in-depth research on barriers
to Six Sigma project implementation in aerospace Tier 1 suppliers and of verification
of the current hypothetical knowledge in the field, it is conceivable to participate in the
research by looking at more Six Sigma Projects, identifying and investigating their
outcomes, and by having questionnaire survey on the critical barriers to
implementations and the relationship of these with QMM. Therefore, this study will
investigate these issues to find solutions that can minimise the impact of these barriers
in aerospace Tier 1 suppliers and evaluate the quality maturity level of the companies.

Research Methodology Chapter 2
1
Chapter 2 Research Methodology
2.1 Introduction
This chapter will discuss the research methodology, explaining how the data were
collected and analysed. Researchers tend to use different research methodologies,
focusing on qualitative research rather than quantitative research.
2.2 Research Design
Research involves several stages, and these stages are illustrated by the research
onion that was developed by Saunders et al. (2007). In this section, these stages will
be discussed briefly. Figure 2.1 below illustrates the research onion.
(Source: Saunders et al. 2003, as cited by Institut Numerique, 2012)
The first stage is the research philosophy; it refers to a set of points of view concerning
the nature of the reality being investigated (Bryman, 2012). Research philosophies
may vary depending on the research objectives and on the best way used to achieve
these objectives (Goddard & Melville, 2004). According to Monette et al. (2005) and
Figure 2.1: The Research Process ‘Onion’

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Bryman (2012), two main ontological frameworks can determine the research process:
positivism and interpretivism. According to positivism, reality exists free of the thing
being examined. Practically, this implies the significance of a phenomenon being fixed
between subjects (Newman, 1998). On the contrary, interpretivism suggests that the
inherent meaning of social phenomena is created by each observer or group (Östlund
et al., 2011). Therefore, since this research is based on a fixed Six Sigma methodology
and is not required to involve a methodology based on a few observations of a sample
of people, the positivism philosophy was chosen.
The second stage is the research approach. There two types of research approach:
deductive and inductive. The deductive approach is used when the researcher is
studying a pre-existing theory to develop a hypothesis to test it (Silverman, 2013). In
the inductive approach, the perceptions are the beginning stage for the researcher,
and models are searched in the data (Beiske, 2007). In this methodology, no system
first informs the data collection, and the research focus would thus be formed after the
data have been gathered (Flick, 2011). Therefore, this research adopted the deductive
approach, mainly because the researcher will rely on previously published theories
related to Six Sigma and the related barriers.
The third stage is the research strategy. The research strategy shows how the
researcher will carry out his/her research (Saunders et al., 2007). The strategy can
involve different approaches, such as experimental research, action research, case
study research, interviews, surveys, or systematic literature review. The strategy used
for collecting data in this research in order to answer the research hypotheses
mentioned in section 1.3 was a piloted survey involving relevant participants.
The fourth stage is the time horizon, which can be defined as the time period within
which a project is expected to be done (Saunders et al., 2007). There are two types of
time horizons: cross-sectional and longitudinal (Bryman, 2012). Cross-sectional time
horizon means that the data must be collected at a specific point in time (Flick, 2011).
In contrast, the longitudinal time horizon refers to collecting data repeatedly over an
extended timeline to examine the changes over time (Goddard & Melville, 2004). This
research adopted the cross-sectional time horizon method by collecting real data at a
specific time period.

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The final stage is data collection and analysis. This stage depends on the
methodological approach used (Bryman, 2012). There are two types of data: Primary
data and secondary data. Primary data are derived from direct sources, such as
surveys or interviews (Bryman, 2012). Secondary data are derived from the works or
opinions of other researchers (Newman, 1998). This research uses a combination of
primary and secondary data.
The research design should be practical and within the limitations of the researcher
and resources, such as time, budget, and skills, to produce the required information
(Ghauri and Grønhaug, 2005). In this case, the defined research questions aim to
identify the barriers that affect the success of Six Sigma implementation within Tier 1
aerospace suppliers as well as to find some solutions to avoid or minimise these
barriers. Hence, given the type of questions and limitations (i.e. lack of resources), a
qualitative research strategy was developed. The qualitative research strategy was
chosen for the advantages mentioned by Atieno (2009), such as simplifying and
managing the collected data, generating new ways of looking at existing data, and
allowing qualitative data to be coded quantitatively, meaning qualitative data can be
assigned numerical values. The researcher also mentioned some limitations of this
type of research: the findings from qualitative research cannot be generalised to a
broader population with the same degree of certainty as quantitative findings can
owing to the small sample sizes and subjective nature of the research. Such limitations
cannot be avoided due to the nature of data; for instance, when doing secondary
research, it is difficult to find reliable data due to its date of publication, its nature, and
how it has been collected in the first place; therefore, such limitations are usually
acceptable.
2.3 Research Strategy: Qualitative Research
The word qualitative applies to entities, processes, and meanings that are not
analysed experimentally or measured by quantity, frequency, or amount (Denzin and
Lincoln, 2005). Therefore, qualitative research can be defined as a fixed process that
helps researchers know where they are located in research, consisting a set of
interpretive, material practices that make the world visible, by studying things in their
natural state, attempting to make sense of, or interpret, phenomena in terms of the
meanings people bring to them (Denzin and Lincoln, 2005). Qualitative research

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methods are focused on providing an in-depth understanding of the world surrounding
the research participants by learning about the sense they make of their social,
experiences, material circumstances, histories, and perspectives (Ritchie et al., 2014)
in order to obtain useful explanations (Miles and Huberman, 1994). Therefore, the
qualitative method was chosen to answer the research questions since there is no
need for experimentation or measurements of quantity, amount, or intensity. Another
reason for choosing qualitative data was that qualitative research tends to analyse the
beliefs or points of view of individuals via small group discussions (Hammarberg et al.,
2016). For this research, a survey was conducted with experienced employees due to
the large number of responses the survey can provide, however, this may cause bias
and uncertainty of the nature of data received.
2.4 Research Ethics
Given the ethical implications of any research, it is essential to protect the participants
from any undue harm and to ensure that the following principles are taken into
consideration (Resnik, 2015):
• Inform the participants of the objectives and aims of the research and any risks
posed by the research prior to their involvement in data collection.
• Avoid carelessness and errors by keeping track of the research activities.
• Be legally authorised to collect data by having the consent form read and signed
by the participants.
• Ensure confidentiality by storing the acquired data in a safe place.
Therefore, per the CU Ethics guidelines, informed consent was granted by the
participants, and they were informed about the purposes of the research and asked
for approval before recording any of the interviews. The participant's information,
survey responses, and interview data were anonymised to protect the identity of the
participants.
2.5 Data Collection
This research consists of two components: Collecting data through the literature
review and collecting data from a survey questionnaire. The survey was designed to
be simple in order to enable the participants to answer it with ease. The participants
were chosen based on their experience in the quality, Six Sigma, quality management
maturity, and aerospace supply chain fields, such as employees certified in Six Sigma,

5
senior quality engineers, suppliers, and managers; the selection was made using the
filter feature in LinkedIn, and potential participants were contacted by private
messaging and posting on related groups on LinkedIn.
Survey questionnaire
The survey methodology begins with the assumption that responding to survey
questions includes many, frequently iterative, strides of complex data processing
(Cannell et al., 1981; Hippler et al., 1987; Tourangeau et al., 2000; Aday et al., 2006,
as cited by Lietz, 2010). While other researchers like Hunt et al. (1982) and Foddy
(1996, as cited by Lietz, 2010) consider a survey as complex communication process
whereby the result of the cooperation among researchers and respondents prompts
the sharing and creating of meaning. From the definitions of survey questionnaire
mentioned above, it can be described as a complicated process to analyse the
collected data from the respondents by the researcher. According to Peterson (2000);
Murray (2011), and Blaxter et al. (2010), it is essential to follow a thorough method for
survey creation in order to maximise the results of the survey questionnaire.
Furthermore, it is essential for the researcher to comprehend the data required, i.e.
what is required and how it will be utilised, before developing a survey (Peterson,
2000); this step facilitates data analysis and hypothesis testing. The survey
questionnaire was based on findings from the literature review and was a web-based
survey – JISC Online Surveys – that could be distributed online; this made the survey
efficient regarding time and cost. A copy of the survey can be found in the Appendix.
The survey was designed in line with the literature review and allowed comparison of
the responses. Additionally, a ranking system was established for identifying the most
common barriers in Six Sigma project implementation and their relationship with the
quality maturity of a company to analyse and compare the relevance and accuracy of
the data from the literature and survey.
The survey consisted of the following sections:
• About your company
• About you
• About your company’s Six Sigma
• Ranking matrix

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The first sections – about your organisation and about you – included profiling
questions. The questions contained in this segment aimed to collect data about the
respondents' organisation and the respondents themselves to profile them to such an
extent that the conclusions drawn could be connected with a specific profile.
The next section – about your organisation’s quality management & Six Sigma – gave
the respondents a chance to continue with the questionnaire depending on their own
comprehension of quality management and Six Sigma, or in the event that they did
not comprehend what quality management and/or Six Sigma entailed, a standard
definition created from the literature review could be used to proceed with the survey.
The respondents who knew about quality management and Six Sigma were given a
chance to write their very own definition in free text; their definition would help shed
light on the respondents' comprehension of quality management and Six Sigma.
The questions following the definition helped describe the quality management
maturity of the respondent's organisation and collect information related to the
hypotheses.
The last segment of the survey, the ranking matrix, was created to enable the
respondents to rank the regular barriers to Six Sigma; additionally, the choice of ‘not
applicable (N/A)’ was permitted if they felt that the barrier did not make a difference to
them.
At the end of the survey, the respondents were given the option to leave their email
address if they were interested in receiving additional data or if they wished to be
informed about the results of the research.
2.6 Data Analysis
The data analysis in this research followed the specific guidelines suggested by Miles
and Huberman (1994):
Minimise the data – includes choosing, focusing, clarifying, abstracting, and changing
the information that shows up in written-up field notes or translations, by utilising
designs or tables to arrange data and distinguish subjects and patterns; present the
data – arranging and packing the information to allow making determinations by
means of tables and figures; lastly, draw conclusions from the findings.

7
There are several tools to help analyse the findings, such as R, SPSS, Excel, Chi-
squared test and descriptive statistics. R is a programming language software
environment for statistical computing and graphics supported by the R Foundation for
Statistical Computing (The R Foundation, 2018). The IBM SPSS® software platform
offers tools for advanced statistical analysis, a vast library of machine-learning
algorithms, text analysis, open-source extensibility, integration with big data, and
seamless deployment into applications (IBM, 2018).
For managing time and simplicity, Excel and descriptive analysis were used in this
research. However, this type of analysis does not give detailed reasoning during the
analysis. Hence, the risk of bias may be high while giving recommendations at the end
of this research.
2.7 Project Management
According to Kerzner (2017), project management can be defined as a series of tasks
with a specific objective, defined start, and end; that consumes human and nonhuman
resources, and is multifunctional. Moreover, the same author states that any
successful project must go through five project phases and this section will present
these phases, which are (1) initiation, (2) planning, (3) executing, (4)
controlling/monitoring, and (5) closing of the project. Therefore, for any project a
timeline should be defined, and a risk mitigation plan should be produced. Therefore,
Table 2.1 and Table, 2.2 below present the timeline and risk mitigation plan for this
research, respectively. During the research and by keeping an eye on the project plan
some risks were encountered such as time and data collection. The main cause of
time was that the researcher had to be away many times which let him lose so much
time and be slightly behind schedule. Where this lost time can be used to modify and
add more data to the literature. Also, the researcher had to add many things to the
literature to support his hypothesis. Therefore, the start of the data collection stage
has started very late, and that led to a lack in responses to do the analysis. One
solution to mitigate time is by putting more efforts to limit the timeline and keep within
the timeline margin sat by the researcher. As for data collection risk, it could not be
mitigated due to the short time left.

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Table 2.1: Project plan
2018 2019
Sep-18 Oct-18 Nov-18 Dec-18 Jan-19
Activity 20 _ 30 01 _ 11 12 _ 21 22_31 1 _ 3 4 _ 8 9 _ 30 1 _ 10 11 _ 20 21 _ 31 1 _ 7
Consider Academic Theory
Establish a reading list 3
Investigation of theory
Collate rough 'Body of knowledge.'
Investigate new topics (if identified)
Refine notes
Conclude main literature investigation
Submission of Literature Review 11
Investigate Industry
Identify relevant case studies 3
Review case studies
Identify success factors
Investigate new topics (if identified)
Finalise notes
Submission of Methodology 3

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Data Collection
Making a questionnaire 18
Conducting interviews 20 17
Submission of Data Collection 20
Discussion
Analyse data collected from interviews 10 25
Compare the data collected from the literature review 25
Conclusions
Draft conclusions 1 1 1
Review and revise 1 1 1
Submission of the Discussion and Conclusions 1 1 1
Completion Stages
Begin outline first draft
First draft complete
Review of draft
Improve the final draft
Submission 7

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Table 2.2: Risk mitigation plan
RISK
ID
TITLE DESCRIPTION RESULT(S) CATEGORY PROB IMPACT SEVERITY RESPONSE PROB IMPACT RESIDUAL
1 Failure to meet the deadline
Failure to achieve a submission
date
Fail/resit qualification TIME 2 5 10
Develop a project
management plan
Develop a risk register
with mitigations
Review plan regularly
Agree on draft submission
with supervisor
1 5 5
2 Insufficient literature reviewed
A literature review is unable to
support the research objectives
Poor quality primary
research
Poor quality discussion
and conclusions
Potential fail of MSc
LITERATURE
REVIEW
3 5 15
Have a variety of
resources
Choose sources with a
high number of citations
Use recent sources
2 3 6
3 Low-quality literature review
A literature review is carried out in
an unscientific/unprofessional
manner
Key findings are based on
inadequate evidence/support
Method of research
cannot be explained or
repeated
Lower confidence in any
findings
LIT REVIEW 4 4 16
Choose relevant topics
and arguments by reading
the abstract, introduction
and conclusion of any
journal, article and book
found
1 3 3
4
Inadequate research
methodology
Inappropriate sequence METHOD 3 5 15 Organise the ideas 1 5 5
5 Lack of respondents Less research analysis DATA 3 4 12
Try different ways to get
in touch with respondents,
as for survey by posting it
on relevant groups on
LinkedIn and pick the right
people based on their
qualifications, roles and
experience.
2 2 4
6 Questions not understood
Wrong data collected
Wrong analysis
DATA 3 4 12
Draft the questions
carefully and review them
1 3 3

11
prior to use
Organise the questions
7 Data loss Poor analysis DATA 3 4 12
Make back-ups on
OneDrive
1 3 3
8 CU Ethics violation METHOD 4 5 20
Follow CU Ethics
guidelines with each step
2 4 8
9 Inadequate analysis Poor recommendations DATA 3 3 9
Get as much data as
possible
1 3 3
10 Lack of confidence in findings Poor recommendations DATA 3 3 9 Ensure data accuracy 2 2 4
11 Emerging issue
Identification of new
evidence/information reduces the
viability of a research project or
suggests alternative/further
research is required
GENERAL 2 2 4
Include any new evidence
found during the results
and analysis stage in that
chapter and recommend
further research on that
evidence in the
concluding chapter.
1 1 1
14 Question order bias
Poor data collection from
respondents
GENERAL 2 3 6
Set the questions in the
appropriate order
1 3 3
15 Personal issue
A personal reason, such as illness,
prevents completion of the MSc
project or key step
Fail/resit qualification GENERAL 2 5 10
Not delaying the work to
last minute by working on
the feedback received
from the supervisor on the
day and keep reading and
implement the findings
straight-away
Report to supervisor and
faculty for an extension if
necessary.
1 5 5
16
Interview candidates are
unavailable
Less data collected DATA 3 5 15
Continuously attempt to
set-up a convenient
meeting time by searching
for other candidates and
2 3 6

12
re-contact the previous
candidates.
17
No access to Boston Online
survey
Less data collected DATA 1 5 5
Search for alternatives by
asking the supervisor for
recommendations that
comply with the CU Ethics
Guidelines.
1 3 3
18
Failure to submit due to
computer issues
Fail/resit qualification TIME 3 5 15
Make back-ups, on
OneDrive
2 3 6
19 Missed/Inaccurate referencing Fail/resit qualification GENERAL 3 5 15
Follow CU Harvard
referencing guidelines
2 3 6
20 Accidental plagiarism Fail/resit qualification GENERAL 3 5 15
Follow CU Harvard
referencing guidelines
2 3 6
RISK ASSESSMENT MATRIX
Probability
Impact 1 2 3 4 5
1 1 2 3 4 5
2 2 4 6 8 10
3 3 6 9 12 15
4 4 8 12 16 20
5 5 10 15 20 25
Score Category Response
1 to 4 Very low Accept Risk
4 to 5 Low Accept/Minor mitigation
6 to 12 Medium Mitigation required
15 to 25 Severe Mitigation required
There should be no SEVERE risks remaining after mitigation

Literature Review Chapter 3
13
Chapter 3 Literature review
3.1 Introduction
This chapter will introduce and evaluate the current research done on Six Sigma. It
will start with Six Sigma’s definition and its key features. Also, it will examine the
strategy used for Six Sigma project implementation. Furthermore, it will review the
literature on obstructions to Six Sigma project implementation. Then, a brief
explanation of the Quality Maturity Model (QMM) will be presented. Afterwards,
research on Tier 1 suppliers for the aerospace industry will be reviewed.
3.2 Six Sigma
3.2.1 Definition and critical features
According to Easton and Rosenzweig (2012), Six Sigma was created in the 1980s as
to encourage employees to engage in learning, problem-solving, and process
improvement, resulting in significant benefits to organisational efficiency (Swink and
Jacobs, 2012). Several definitions for Six Sigma exist; for instance, Pande et al. (2000)
see it as a means for understanding client needs, restrained use of information and
statistical analysis, constant attention to management and processes, and enhancing
and reinventing business processes. Easton and Rosenzweig (2012), Swink and
Jacobs (2012), and Pande et al. (2000) agree that Six Sigma is a process that helps
organisations be more efficient by understanding the customer’s needs, paying
attention to management processes, and encouraging employees to engage in
learning and solving problems and thus ensure continuous improvement.
Six Sigma is based on the Define - Measure - Analyse - Improve - Control (DMAIC)
methodology, which is a data-driven quality strategy used to improve processes based
on ASQ (2018). Some of the benefits of implementing Six Sigma in a project were
noted by Pande et al. (2000) and De Mast (2006) as follows: cycle-time reduction,
product/service development, defect reduction, culture change, productivity
improvement, cost reduction, and understanding customer needs. Six Sigma is
thought to create a structure and culture that promotes continues improvement,
process analysis, and issue/opportunity identification (Swink and Jacobs, 2012).
However, Linderman et al. (2003), Sinha and Van de Ven (2005), and Schroeder et
al. (2008, as cited by Swink and Jacobs, 2012) argue that Six Sigma is unique in

14
relation to different process management approaches based on organisation
structure, standardised methodologies, and emphasis on client-situated
measurements. Six Sigma tries to minimise defects in business processes by applying
a few tools and procedures under a methodological and maintained structure (Kumar
et al. 2008). In numerical terms, Six Sigma refers to a limit of 3.4 defects per million
opportunities (DPMO), where the term sigma represents the deviation in the average
process cycle (Coronado and Antony, 2002). This systematic methodology for
managing enhancement activities is represented by the Define - Measure - Analyse -
Improve - Control (DMAIC) methodology, utilised in process development or Define -
Measure - Analyse - Design - Verify (DMADV) employed in product/service design
development (Linderman et al., 2003).
Numerous critical features add to the capability of Six Sigma, as presented below
(Goh, 2002):
1. Top-down initiation of a serious quality journey (not a book-keeping exercise)
2. Hierarchy of expertise and execution (champions, Black Belts)
3. Structured deployment of tools (DMAIC)
4. Customer focus (in contrast to inward-looking standardisation)
5. Clear performance metric (sigma levels; dpmo)
6. Fact-based decisions (not procedure or judgment based)
7. Application of statistics (analytical, not willpower)
8. Service as well as engineering applications (thus extending the horizon of
statistical thinking)
9. Recognised time effects in process analysis (with explicit provisions for short-
term and long-term variations)
10.Result oriented (project by project; three- to six-month-project duration makes
progress tangible)
11.Business-oriented (achievements often need to be expressed in financial
terms)
12.Right timing (coming at a time when personal computing hardware and
statistical software packages had become widely available, making pervasive
implementation possible)

15
3.2.2 Reported Benefits of Six Sigma Implementation
After the implementation of Six Sigma by Motorola in the 1980s as part of its quality
performance measurement and improvement programme, it was later successfully
applied in other manufacturing and engineering companies such as General Electric,
Boeing, DuPont, Toshiba, Seagate, Allied Signal, Kodak, Honeywell, Texas
Instruments, Sony, etc. The following table summarises the reported benefits and
savings after Six Sigma implementation in the projects of various companies.
Table 3.1: Reported benefits and savings from Six Sigma in the manufacturing sector
Company/Project Metric/Measures Benefit/Savings
Motorola (1992)
In-process defect
levels
150 times reduction
Raytheon/aircraft
integration systems
Depot
maintenance
inspection time
Reduced 88% as measured
in days
GE/Railcar leasing
business
Turnaround time at
repair shops
62% reduction
Allied Signal
(Honeywell)/laminate plant
in South Carolina
Capacity cycle
Time inventory
On-time delivery
Up 50% Down 50% Down
50% Increased to near
100%
Allied Signal
(Honeywell)/Bendix IQ
brake pads
Concept-to-
shipment cycle
time
Reduced from 18 months to
8 months
Hughes aircraft's missiles
systems group/wave
soldering operations
Quality/productivity
Improved 1,000%/improved
500%
General electric Financial $2 billion in 1999
Motorola (1999) Financial $15 billion over 11 years
Dow chemical/rail delivery
project
Financial
Savings of $2.45 million in
capital expenditures
DuPont/Yerkes plant in
New York (2000)
Financial
Savings of more than $25
million

16
Telefonica de Espana
(2001)
Financial
Savings and increase in
revenue by 30 million euros
in the first 10 months
Texas instruments Financial $ 600 million
Johnson and Johnson Financial $ 500 million
Honeywell Financial $1.2 billion
(Adapted from Weiner, 2004; de Feo and Bar-El, 2002; Antony and Banuelas, 2002; Buss and Ivey,
2001; McClusky, 2000, as cited by Anbari and Kwak, 2006)
The data presented in Table 3.1 is outdated, and it shows the benefits and the results
that companies have obtained by implementing Six Sigma within their projects.
However, some of the findings in this table raise questions such as how does this
improvement happen? Was the company experiencing severe failure and suddenly its
quality improved ten times than before? Some recent case studies showed how Six
Sigma as a methodology has been developing, and when six sigma was implemented
in a company, it improved the company’s business, for example, a case study was
carried out by Chakraborty and Chuan Tan (2012) in service organisations such as
hospitals in Singapore, and they found how they successfully implemented Six Sigma
and what challenges they faced during the implementation.
3.2.3 DMAIC Methodology
In this section, the DMAIC methodology will be discussed due to its importance in
understanding Six Sigma. In Six Sigma, DMAIC offers a clear direction that can help
individuals solve problems and enhance processes; hence, it helps to avoid rushed
judgment (Schroeder et al., 2008). The Six Sigma strategy can help teams accomplish
their objectives, particularly for challenging projects (Linderman et al., 2006). The five
steps of the Six Sigma DMAIC framework were described by Henderson and Evans
(2000) and Senapati (2004) (Figure 3.1).

17
(Adapted from Henderson and Evans, 2000; Senapati, 2004)
3.2.4 Six Sigma Hierarchical Structure
To understand Six Sigma and its benefits, knowing the roles of employees working on
Six Sigma projects is essential. Therefore, this section will describe their duties in
detail. Several development specialists can help realise Six Sigma objectives: they are
known as Black Belt (BB), Master Black Belt (MBB), Green Belt (GB), and Project
Champion (Linderman et al., 2003). These specialists have distinctive jobs and duties,
with customised training targeted to their positions and intended to enhance their
knowledge and skills in measurable strategies, project management, process design,
problem-solving methods, leadership, and other management skills (Zu et al., 2008).
Who are the clients and what are their needs?Define (D)
• A Six Sigma venture group recognises a task appropriate for Six Sigma endeavours in light of
business targets and additional client needs and criticism.
• The Supplier-Input-Process-Output-Customer (SIPOC) mapping activity can be utilised
successfully to depict the procedure.
How is the procedure estimated and how is it performing?Measure (M)
• The group recognises the key procedures that impact Critical to Quality Characteristics (CTQs);
they also measure the imperfections at present concerning those procedures.
• Estimation of process factors through information quality checks.
• Repeatability and reproducibility (R&R) regarding process dependability.
What are the most important causes of defects?Analyse (A)
• The utilisation of graphical systems to break down the procedure.
• The group finds why probems emerge by recognising the key factors that make process variety.
How do we remove the causes of the defects?Improve (I)
• The team confirms the key variables and quantifies their effects on the CTQs.
• Change of the current procedure through experimentation and reproduction systems.
How can we maintain the improvements?Control (C)
• Develop the control plan for process improvement.
• Tools are put in place to ensure that, under the modified process, the key variables remain
within the maximum acceptable range over time.
Figure 3.1: Six Sigma DMAIC process

18
The DMAIC strategy includes a hierarchy of many individuals at several steps.
Champions play an essential role in the define step, although playing a supporting
position in the rest of the steps; process leaders have a more dynamic role in the
control step, but a supporting position in other steps. Green Belts tend to have a more
dynamic position in the measure, analyse and improve steps, even occupying
leadership roles. Finally, Black Belts fill in as project leaders and are dynamic in all
parts of the procedure (Schroeder et al., 2008). In the Six Sigma philosophy, belts
symbolise both specialised and management skills, the capability to comprehend and
execute the tools and procedures, and the ability to mentor groups (Gijo and Rao,
2005). In this manner, these belts signify successful Six Sigma implementation (Gijo
and Rao, 2005). A summary description of the different roles in a Six Sigma
organisation can be found in Appendix B.
3.3 Tier 1 Aerospace Industry Suppliers
Supply Chain Management (SCM) was defined by Monczka et al. (1998, as cited by
Mentzer et al., 2001) as a system to merge and deal with the assets and stream and
control materials by utilising viewpoint frameworks over different capacities and tiers
of suppliers. Nagurney et al. (2003) developed an equilibrium network model for global
supply chain comprising three tiers to obtain price patterns and product shipments
within the network to promote cooperation between tiers. The three tiers can be
divided into three different companies or departments depending on the company
structure with three different functions in order to supply the manufactures known as
original equipment manufacturers (OEMs) with the required material. The differences
between the tiers in the manufacturing industry were explained by Amatech Inc (n.d.)
as follows: Tier 1 suppliers are companies who directly provide OEMs with parts or
systems (e.g. General Electric and Rolls-Royce); Tier 2 suppliers are companies who
specialise in a specific field; and Tier 3 suppliers are companies who provide raw
materials to all companies. Some companies fall under any of the mentioned tiers
above depending on the departments they have. For instance, Siemens is a cutting-
edge company specialising in the electrical field and has many departments – some
specialise in power generation, making it an OEM, while other departments
manufacture small electrical components that are sent to other OEMs, making it a Tier
2 or Tier 3 supplier, depending on the required project. Many aerospace industry
manufacturers such as Rolls-Royce require their suppliers to implement Six Sigma

19
within their projects in order to minimise the defects and cost and maximise the safety
and durability of the components/materials.
3.4 Barriers to Six Sigma Project Implementation and the
top five barriers:
3.4.1 Barriers to Six Sigma Project Implementation
Despite the various advantages of Six Sigma, challenges may arise during project
execution which, if not managed the right way, can hinder project execution, which
may fail the project. For instance, in a case study done by Chakravorty (2009), using
an escalation model for an electrical products company in the southern United States,
the company started implementing Six Sigma from 2004 to 2008 when they
abandoned Six Sigma because they were experiencing failures during these four
years after having invested nearly US$ 25 million. Therefore, Six Sigma project
implementation can fail for a few reasons. For example, Snee (2001) identifies such
barriers as the absence of help by management, vast project scope, inadequate time
to work on a project, and lack of a connection between the project and the
organisation's critical objectives. Other authors, for example, Proudlove et al. (2008),
examined the use of Six Sigma in the service industry, and found a few barriers such
as trouble in distinguishing clients and procedures, deviations from the rigorous
DMAIC process, lack of emphasis on the soft/people/cultural factors, and limited Black
Belt support. Further, Kumar et al. (2009) reported low emphasis on the voice of
customers (VOC), short-term reserve funds, and over-emphasis on the convenient
and fast selection of a large and complex project with an excessively broad scope.
Furthermore, Aboelmaged (2011) examined the most compelling obstructions to Six
Sigma usage by means of a cross-sectional review focusing on CEOs and task or
quality supervisors in different organisational settings.
Of the barriers mentioned above, most have been portrayed in previous academic
research. This can result in having various opinions on the barriers, which would have
an impact on the accuracy of the results of this research. The following sections
summarise the findings from existing research on the barriers to Six Sigma project
deployment.

20
• Deficient Project Selection:
Poor project selection methodology (i.e. no organised way of dealing with choosing
ventures) is a significant barrier to successful Six Sigma venture execution (Kumar et
al., 2009; Antony and Desai, 2009). Some companies focus on belts, thus compelling
them to consider everything as a Six Sigma venture (Gijo and Rao, 2005) while other
companies prioritise projects that have the highest cost reduction (Kumar et al., 2009).
Hence, failure in project selection would lead to catastrophic consequences such as
monetary loss.
• Project Scope Too Large:
The project scope ought to include enhancements that are feasible in three to a half
year of the period (Snee, 2001). Huge and complex tasks increase the likelihood of a
project being postponed or abandoned (Kumar et al., 2009; Gijo and Rao, 2005). As
indicated by Snee (2001), the unexpected extension is a common reason for task
disappointment. Therefore, an unrealistic project scope can lead to a high chance of
project failure.
• Project Objectives not Important to the Organisation or not Linked to the
Organisation’s Strategic Goals:
While project associations should be attached to the primary concern, some cannot
connect their tasks to their objectives and goals (Snee, 2001; Gijo and Rao, 2005).
Projects lacking this link fall behind schedule or even fail (Kumar et al., 2009). Having
a clear, realistic, and linked project objective increases the chances of project success.
• Insufficient/Deficient Training:
Adequate training that gives employees the required knowledge is a crucial element
for the success of Six Sigma implementation (Kreisler Buch and Tolentino, 2006).
Therefore, inadequate and/or deficient training may result in issues in project
execution, such as the inability to select and apply the appropriate tools.

21
• Difficulties Selecting and Applying Complex Six Sigma Tools and Techniques:
Nonthaleerak and Hendry (2008) found that the recognition of tool complexity relies
on the instructive foundation of the belts. For instance, belts with engineering degrees
and work experience in manufacturing fields may have fewer concerns than those from
the non-manufacturing areas, regarding the utilisation of factual apparatuses.
Furthermore, Nonthaleerak and Hendry (2008) noted that less experienced belts
require more help from a Master Black Belt in executing projects and choosing proper
devices. It is important to assign each role to the right employee based on his/her
experience and qualification in order to utilise the correct tools while executing
projects.
• Lack of Managerial Support:
As mentioned previously, managerial responsibility and support are essential to the
success of Six Sigma project execution. The management and leadership may not be
dedicated to the framework due to, for instance, the absence of the connection
between Six Sigma ventures and an extensive strategic approach to deal with change
(Proudlove et al., 2008). In some firms, the top management is occupied with Six
Sigma execution while process owners or champions of the tasks are not (Gijo and
Rao, 2005). The examples mentioned above justify the importance of excellent
managerial support in any project.
• Insufficient Time to Work on Project:
Snee (2001) noted that Black Belts are prescribed to work all day, having the ability to
spend 80 per cent of their time on a project. Green Belts, however, are different
workers who work part-time on process development. According to Snee (2001),
Green Belts ought to have the capacity to spend 20 per cent of their time on their
ventures. However, Pyzdek and Keller (2010) found that although most specialists
advocate that the Green Belts spend around 10 and 20 per cent of their time on
ventures, the time they spend falls in the range of 2–5 per cent. In this sense, venture
delays occur when belts and their groups do not have adequate time to focus on their
tasks since the more significant part of a Green Belt's time is spent on their typical
work obligations. However, Snee’s (2001) data is limited and old; therefore, it is less

22
reliable, but Pyzdek and Keller (2010) data is newer – less than ten years old – so it
is reliable.
• Limited Black Belt Support:
Black Belt support is viewed as a major factor for project success. When Black Belt
support is constrained, Green Belts may have issues, thus stalling project execution
and making wrong decisions (when they are unprepared for instance) amid project
execution. However, Proudlove et al. (2008) confirmed that restricted Black Belt
support in a few events is not a noteworthy barrier for ventures.
• Very Large Team:
Snee (2001) recommends that the group working with the Black Belts (or Green Belt
group leader) be small, no more than four to six individuals. As the group grows, it
becomes harder to set common meeting times and achieve coordination (Snee, 2001).
• Difficulties in Collecting Data:
Six Sigma is an information-driven methodology, and it is required to help any
conclusion from the project by the right information collection and its analysis (Gijo
and Rao, 2005). In some cases, the applicable information is difficult and costly to
gather. As indicated by Feng and Manuel (2008), non-accessibility of information is
the central point in the deferral of a task, particularly for those that require information
procurement from various divisions. The reluctance of individuals to gather information
may likewise hamper the advancement of a Six Sigma venture (Gijo and Rao, 2005).
It is essential to secure all data collection resources before accepting any project so
that it does not result in catastrophic losses in the middle of project implementation.
• Resistance to Change/Non-Supportive Culture:
As in numerous other management processes, Six Sigma activities often and
unsurprisingly experience opposition from organisations, individuals, and officials
(Feng and Manuel, 2008). Hence, organisations without a backup management plan
may face the risk of failure. Hence, senior management's commitment, support, and
leadership are primary factors in managing social issues identified in Six Sigma

23
implementation (Kwak and Anbari, 2004). According to Proudlove et al. (2008), a
noteworthy shortcoming of Six Sigma is the absence of emphasis on the
soft/people/cultural variables.
• Deviations from the Structured DMAIC Process/Over-emphasis on Quick Fix:
A few organisations may tend to feel restless waiting for results, thus deviating from
the DMAIC methodology and searching for alternate techniques (Gijo and Rao, 2005).
The utilisation of the DMAIC procedure has been observed to be useful yet
troublesome, making it a source of frustration for some Green Belts (Proudlove et al.,
2008). As Proudlove et al. (2008) mentioned, this can happen because of the desire
for 'speedy wins', especially evident in past ventures.
• Insufficient Resources to Work on the Project (i.e. computers):
At times, Six Sigma ventures require a great deal of data collection and examination,
requiring the necessary resources (Gijo and Rao, 2005). Furthermore, Gijo and Rao
(2005) noted that a few companies could not afford extra training in the Six Sigma
methodology. Other authors such as Chakrabarty and Chuan (2009), Kumar et al.
(2009), Antony (2008), and Antony et al. (2005, as cited by Shamsi and Alam, 2018)
agree on the importance of having sufficient resources.
• Difficulty in Sustaining Project Improvement:
Nonthaleerak and Hendry (2008) noticed that project leaders express concerns about
the control period of the DMAIC procedure stage, as this can be especially tricky when
the venture is cross-functional and when venture ownership is not legitimately
exchanged to a process owner. Hence, they infer that procedure control apparatuses
alone are inadequate to support the change results and that the job of administration
alongside a decent quality control framework is critical. Likewise, Snee (2001) noted
the significance of support from management as key to successful Six Sigma
advancement.

24
• Difficulties with Integration of Different Areas/Coordination Between
Functions:
As Six Sigma ventures are cross-functional, the absence of legitimate coordination
may lead to an improper determination of CTQs and off-base information,
investigation, and arrangements (Gijo and Rao, 2005). Numerous tasks have
collapsed because of staff deficiencies (Snee, 2001).
The importance of the mentioned barriers above can differ depending on the type of
business and its complexity. For instance, building a new computer system is entirely
different from building an aeroplane; the materials used to build an aeroplane are
much stronger, more heat resistant, and more flexible than the materials used for
making a new computer system.
3.4.2 Top five common barriers
According to Kumar et al. (2005), 80 per cent of the enterprises the responded to their
survey on Six Sigma barriers within the UK (Small-to-Medium Enterprises) SMEs said
that lack of resources was one of the factors impeding the successful introduction of
Six Sigma initiatives in UK SMEs, while lack of resources covered a wide range of
aspects, including financial resources, human resources, time, and so on. Other
factors included lack of leadership, inadequate training/coaching, internal resistance,
poor project selection, and so on, signifying that the common themes among these
barriers are management related (Snee, 2001).
The barriers portrayed in section 3.4 affect various phases of Six Sigma project
implementation. Also, some might be more crucial than others, depending on the
amount of restraint they place on the flow of a project. In this manner, studying the
effect of these barriers provides specialists with useful knowledge that may help them
maintain a strategic distance from or control these issues. Therefore, in this research,
the most common barriers (lack of resources, lack of leadership, inadequate
training/coaching, internal resistance, and poor project selection) will be studied due
to their importance and impact on Six Sigma project implementation. For example,
lack of leadership would have a significant impact on other barriers such as resources
– if the manager does not secure all the required resources such as materials, data,

25
and machines, by monitoring the employees responsible for the supply chain and
logistics of the company, this will affect the project timeline and delay the project.
Based on the findings from the literature review, the barriers listed below based on
their importance are the most common barriers that need to be explored:
1. Leadership
2. Time
3. Resources
4. Training
5. Project Selection
These barriers are usually linked, for example, poor leadership would cost time, lack
of resources, insufficient training, and wrong project selection, thus H1 is supported.
3.5 Quality Maturity Model
To understand how a company implements quality within its projects and the stage it
is at, quality management maturity models were introduced. Therefore, it is essential
to understand what this model is. In this section, the quality management maturity
model will be discussed briefly in light of the findings from other studies in the literature.
Many aspects of product development have applied the concepts of process or
capability maturity, both as a means of analysis and as part of framework
enhancement (Fraser et al., 2002). Maturity models have been suggested for many
kinds of activities such as quality management (Crosby, 1979). For instance, De Bruin
et al. (2005, as cited by Egberongbe et al., 2017) identified three distinct features of
maturity models:
a) offering a deeper understanding of the prevailing situation in an organisation;
b) serving as an improvement over the first stage, as it specifies how to identify
desirable future maturity levels as well as providing improvement measures;
and
c) applying the model to different areas to obtain adequate information for better
assessment of a given situation.
The basic idea of maturity is to describe the typical behaviour demonstrated by a firm
at various stages of maturity for each aspect of the area under the study (Fraser et al.,

26
2002). The authors clarified that this step provides the opportunity to identify good or
bad practice, along with some intermediate or transitional stages.
3.5.1 Purpose of Quality Maturity Model
There are four purposes of QMM. These were described by Wilson (2015) as
follows:
1. To guide enterprises to determine where they are in their journey of achieving
their own unique quality culture
2. To enable the enterprise's management team to prioritise their decisions
3. To assess quick, cheap, and easy measures of the quality culture
4. To provide a common language and a shared vision for a community of practice
3.5.2 Overview of Maturity Approaches
Fraser et al. (2002) stated that maturity has rigorous approaches in the field of quality
management. For instance, Fraser et al. (2002) point out to the Capability Maturity
Model (CMM) which defines software process maturity as ‘the extent to which a
specific process is explicitly defined, managed, measured, controlled, and effective’.
Therefore, the CMM takes a different approach from the quality grid. Another maturity
approach is Crosby's Quality Management Maturity Grid (QMMG), which is considered
one of the earliest models. For simplicity and lack of time, Crosby’s model was chosen
in this research, which might lead to a lack of accuracy in the findings. Crosby’s model
describes the typical behaviour demonstrated by a firm at five levels of maturity, for
each of the five aspects of quality management (Crosby, 1979). Fraser et al. (2002)
noted that the QMMG had a strong evolutionary theme, suggesting that companies
were likely to evolve through five phases – Uncertainty, Awakening, Enlightenment,
Wisdom, and Certainty – in their ascent to quality management excellence. Figure 3.2
and Figure 3.3 explain these stages:

27
(Source: Crosby, 1979)
(Source: Crosby, 1996)
Figure 3.2: The Quality Management Maturity Grid
Figure 3.3: The Quality Management Process
Maturity Grid

Results and analysis Chapter 4
28
Chapter 4 Results and Analysis
In this chapter, the data collected from the survey questionnaire will be presented
along with the methods used for analysis and significant findings for further
investigation in the discussion chapter.
4.1 Questionnaire Survey Responses
The survey was completed by six respondents, and their data will be analysed herein.
The response rate could be considered low as the number of members available on
LinkedIn forums as well as those in other forums totalled over 500,000, so the
responses received only represent 0.0012% of the total available potential
respondents, although there is a potential for double counting as members could be
in multiple groups. This low number of responses has many reasons such as the timing
of the survey, where everyone was busy with the Christmas and New Year holidays.
This would result in a weak analysis that would affect the hypotheses of this research
and more reliance on the literature review rather than on real-time data.
4.2 Quality Management System Definition Analysis
During the survey questionnaire, the respondents were given the opportunity to
provide their definitions of ‘quality management systems’ and state whether they agree
or disagree with the definition provided by ASQ.org (2018) in the questionnaire. One
out of six respondents provided a text response, while the others only agreed on the
definition provided. The respondent who wrote a text response after agreeing with the
definition provided mentioned that the quality management system connects the
procedures of different areas/departments within the organisation to make sure they
work together to reach a common goal.
4.3 Six Sigma Definition Analysis
During the survey questionnaire, the respondents were given the opportunity to
provide their definitions of Six Sigma and to agree or disagree with the definition
provided by Easton and Rosenzweig (2012), Swink and Jacobs (2012), and Pande et
al. (2000) in the questionnaire. Two out of six respondents provided a text response,
while the others only agreed on the definition provided. Both respondents agreed that
Six Sigma is a methodology that helps organisations reduce variation in their

29
processes to meet the customer’s needs. Therefore, the client is impacted by this
variation, when a company does not have their processes under control the client
sometimes receives a good service or product and sometimes not. The respondent
agrees that Six Sigma has various tools that help to reduce the deviations within the
company processes and to ensure that what the customer request is what the
customer is going to receive.
4.4 Questionnaire Analysis
Due to the small number of responses received compared to the huge amount of
people contacted, the findings cannot be considered statistically significant. Hence, it
is going to be difficult to conclude a proper analysis from this chapter.
4.4.1 Quality Management Maturity
Respondents were given the opportunity during the survey to categorise their
company based on Crosby’s Quality Management Maturity Grid (1979); the results of
this question are presented in the bar chart below.
0
1
2
3
4
Count
Crosby’s Quality Management Maturity Grid (1979)
Figure 4.1: Bar chart of Quality Management Maturity

30
Further, cross-tabulation with the leadership barrier was carried out to simplify the
analysis, as shown in Table 4.1.
Table 4.1: Crosstabulation with counts for leadership as a barrier and quality
management maturity categories
Leadership
(Barrier)
Based on Crosby's Quality Management Maturity Grid (1979)
attached below, would you be able to put your company in
ONE of the stages based on its maturity in QMS?
Uncertainty Awakening Enlightenment Wisdom Certainty
Not very
Important
0 0 0 0 0
Not Important 1 0 0 0 0
Neutral 0 0 0 1 0
Important 0 0 1 0 0
Very Important 0 0 2 1 0
From the table above, it can be seen that the more the value given to the leadership
barrier the more the company is quality matured based on Crosby’s grid, which
partially supports H4. However, this result is not reliable due to the insufficient number
of responses received which it is not enough to build a conclusion due to the bias
introduce when having such low number of responses and it makes the data unclear
to be analysed.

31
4.4.2 Questionnaire Responses
Question 1: What is your age?
This was a profiling question to determine the age of the respondents, and it can be
seen that all respondents were in the age group of 25–50 years.
Question 2: Which of the following describes your employment status?
This question was asked to categorise the employment status of the respondents; as
shown in the chart, the majority of the respondents were full-time employees.
0
1
2
3
4
5
6
7
18-24 25-50 51-70
Count
Age
Figure 4.2: Results bar chart of participants’ age
0
1
2
3
4
5
6
Full-time Part-time Self-employed Retired
Count
Work Status
Figure 4.3: Bar chart of responses on work status

32
Therefore, the bias can be considered low by having responses from people
currently have a contract with a company.
Question 3: What is your highest academic qualification to date?
The responses to this question were equally divided between the master’s and
bachelor’s degree – there may be many reasons behind this. For instance, the
importance of being qualified in a quality field or/and being certified in Six Sigma.
However, due to lack of responses this conclusion above cannot be relied on and base
the research conclusion on it.
Question 4: How long have you worked for your current company?
0
1
2
3
4
PhD Master's Bachelor's Diploma Other
Count
Qualification
Figure 4.4: Bar chart of responses on qualification
0
1
2
3
< 6
months
6-12
months
1-2
years
2-5
years
5-10
years
10-15
years
> 15
years
Count
Length of service
Figure 4.5: Results bar chart of responses to length

33
This was a profiling question to determine how long the respondent had been
employed with the current company; this question would help select the most accurate
responses based on the respondent’s knowledge of the company.
Question 5: For how long have you been in your current role?
The responses to this question show that the majority of the respondents had worked
in their role for 1–2 years, while the rest had worked for 2–5 years. This result would
reduce the bias of the responses in the survey which will help get more accurate
results than if the majority were less than 12 months. However, this number of
responses is not enough to have an accurate conclusion about this answer.
0
1
2
3
4
5
< 6
months
6-12
months
1-2
years
2-5
years
5-10
years
> 10
years
Count
Time in Role
Figure 4.6: Bar chart of responses to time in current job
role

34
Question 6: Do you work in a role related to Six Sigma?
All the respondents were working in a role related to Six Sigma; this could reduce the
bias in this research as the respondents knew what the survey was about, so they
would give appropriate answers. However, this number of responses is not enough to
have an accurate conclusion about this answer.
Question 7: Are you aware of the concept of quality management?
All the respondents believe that they are aware of the quality management concept,
but their knowledge of quality management could vary; which might make a bias in
this research when the respondents assume to know what the survey about, so they
can give the appropriate answers.
0
1
2
3
4
5
6
7
Yes No Other
Count
Six Sigma Role
Figure 4.7: Bar chart of responses to whether the
respondents had a Six Sigma role
0
1
2
3
4
5
6
7
Yes No
Count
Awareness of Quality Management
Figure 4.8: Bar chart of responses to awareness of
quality management

35
Question 8: Are you aware of the concept of Six Sigma?
In this question, all respondents believe that they are aware of Six Sigma, but their
knowledge of six sigma could vary, which might make bias in this research when the
respondents assume to know what the survey about, so they can give the
appropriate answers.
Question 9: Which sector is your company involved in?
This question was developed to identify the sectors that the respondent worked in.
However, as the bar chart shows, all respondents worked in the aerospace sector; this
would minimise the bias of this research since its focus is on the aerospace industry.
0
1
2
3
4
5
6
7
Yes No
Count
Awareness of Six Sigma
Figure 4.9: Bar chart of responses to awareness of
Six Sigma
0
1
2
3
4
5
6
7
Aerospace Manufacturing Logistics Supply Chain Other
Count
Sector
Figure 4.10: Bar chart of responses to company sector

36
Question 10: How many employees does your company have?
This question was designed to get an overview of the company size that the
respondents work with. As shown in the bar chart above, only two size categories were
identified; the majority worked in companies with >10,000 employees. Therefore, and
due to the inadequate responses, there will not be any further analysis of this question,
which will damage the research analysis and conclusion.
Question 11: Is your company multinational?
This question was asked to determine whether the companies who implement Six
Sigma in the aerospace sector are multinational or not. The results show that all
companies were multinational. This feature may introduce a language barrier between
0
1
2
3
4
5
Count
Number of Employees
Figure 4.11: Bar chart of responses to number of
employees
0
1
2
3
4
5
6
7
Yes - Worldwide Yes - Europe No
Count
Multinational
Figure 4.12: Bar chart of responses to global reach
of company

37
the employees and customers from different countries who speak different languages;
hence, the customer may not receive the product he asked for.
Question 12: Under which supply chain tier is your company?
This question was asked to identify the tiers category of the company that the
respondents work with. The majority of respondents were working within a Tier 1
supplier company, i.e. 66.7% of the respondents, while the other 33.3% was divided
equally between Tier 1 & 2 and Tier 2 suppliers. For this research focus, Tier 2 will
filter from the analysis.
Question 13: Does your company require Six Sigma implementation by their
suppliers?
0
1
2
3
4
5
Tier 1 Tier 2 Tier 3 Tier
1&2
Tier
1&3
Tier
2&3
Tier
1,2&3
Count
Supply Chain Tiers
Figure 4.13: Bar chart of responses to supply chain
tier category
0
1
2
3
4
Yes No Unsure
Count
Six Sigma Implementation
Figure 4.14: Bar chart of responses to Six Sigma
implementation requirement

38
This question was asked to identify the quality maturity of the company. A comparison
with Crosby’s grid is made for further analysis in the table below.
Table 4.2: Requirement of implementing Six Sigma by suppliers compared with
quality management maturity
Does your
company
require Six
Sigma
implementation
by their
suppliers?
Crosby's Quality Management Maturity Grid
Uncertainty Awakening Enlightenment Wisdom Certainty
Yes 1 (16.7%) 0 0 1 (16.7%) 0
No 0 0 2 (33.3%) 1 (16.7%) 0
Unsure 0 0 1 (16.7%) 0 0
Based on the comparison shown in the table above, companies who do not require
the implementation of Six Sigma from their suppliers have a lower quality maturity
level. Therefore, these companies may have many defects in their products due to
low-quality control. Again, this conclusion cannot be accurate due to the lacking
number of responses.
Question 14: How important do you feel Six Sigma is to your company’s
success?
0
1
2
3
4
Not Very
Important
Not
important
Neither Important Very
Important
Count
Six Sigma Importance
Figure 4.15: Bar chart of responses to importance of Six
Sigma

39
This question was asked to know the respondent's opinions about the importance of
Six Sigma to their company’s quality maturity. However, the results shown in the bar
chart above were unexpected; it was expected that the majority would say that Six
Sigma is very important. This result triggers a couple of questions:
• What quality tools do the companies use within their projects?
• How do companies maintain the safety, durability and quality of their products?
Question 15: Does your company have an established method for managing
Six Sigma implementation?
This question was used to support the determination of quality management maturity
as evidence of having a system to manage Six Sigma implementation. As the bar chart
above shows, the majority of respondents indicated that their company adopted a
system to manage Six Sigma.
0
1
2
3
4
5
6
Yes No Not Yet Unsure
Count
Established System
Figure 4.16: Bar chart of responses to the company
having an established system

40
Question 16: How satisfied are you with the Six Sigma method?
This question was asked to determine the respondent’s feelings towards Six Sigma.
The results of the survey were divided equally between unsatisfied, satisfied, and very
satisfied, making the analysis difficult.
Question 17: How many people in your company work in Six Sigma?
This question was asked to understand how much emphasis a company places on
Six Sigma overall; this could be achieved by determining the size of the Six Sigma
team of a company.
0
1
2
3
Very
Unsatisfied
Unsatisfied Neither Satisfied Very
Satisfied
Count
Six Sigma Satisfaction
Figure 4.17: Bar chart on satisfaction with Six Sigma
0
1
2
3
1-10 11-20 21-50 51-100 > 100
Count
Number of people in Six Sigma
Figure 4.18: Bar chart on responses to number of
people in Six Sigma

41
Question 18: Does your company provide access to Six Sigma Training?
This question was asked to understand how much a company supports the continuous
improvement method by motivating its employees to learn new concepts and give
them the appropriate training. From the results shown in the bar chart above, most of
the respondents answered ‘yes’, which means that their companies support the
continuous improvement method.
Question 19: How long has your company been engaged in Six Sigma?
By showing how many years the company has been engaged in Six Sigma, it would
mean that is the company is gaining profits of implementing Six Sigma within their
projects. Also, it can be as an indication of its maturity. However, from the results of
this question, the researcher cannot be sufficiently accurate about his conclusion
due to the small number of responses received.
0
1
2
3
4
5
6
Yes No Unsure
Count
Six Sigma Training
Figure 4.19: Bar chart on responses to
provision of Six Sigma training
0
1
2
3
4
< 6
months
6-12
months
1-2
years
2-5
years
5-10
years
> 10
years
Count
Company Engagementin Six Sigma
Figure 4.20: Bar chart on responses to
company engagement with Six Sigma

42
Question 20: Is Six Sigma considered when planning a project strategy?
As the bar chart above shows, three respondents were aware of Six Sigma
consideration in a project planning strategy and two respondents stated that it is not
considered. The unsure response could mean that the respondent does not have a
view of the project plan. Based on these results, we can conclude that Six Sigma is
usually considered in the project planning strategy.
Question 21: Is there a clear understanding of how Six Sigma contributes to
profits?
The majority of the responses to this question were either agree or unsure. This result
is interesting as compared with the Six Sigma definition question, as they all agreed
0
1
2
3
4
Yes No Unsure
Count
Six Sigma Consideration
Figure 4.21: Bar chart on responses to Six Sigma being
considered in project planning strategy
0
1
2
3
4
Yes No Unsure
Count
Six Sigma profit
Figure 4.22: Bar chart on response to clear understanding
of how Six Sigma contributes to profits

43
that Six Sigma is meant to reduce deviations and, hence, reduce costs, which would
be beneficial to the company.
Question 22: Ranking Matrix – Ranking of Six Sigma Barriers in order of
Importance
The respondents were asked to rank the potential barriers to Six Sigma on a scale of
1–5, where 1 meant least important and 5, most important. Moreover, the
respondents were given the opportunity to add to the barriers based on their
experience and knowledge.
To make the bar chart easy to read and rank the barriers based on the responses
received, a weighted score model was utilised to rank the weighted results using
Excel, as shown in the table below.
0
1
2
3
4
5
1 2 3 4 5
Count
Six Sigma Barriers Importance Ranking
Leadership
Time
Resources
Training
Project Selection
Figure 4.23: Bar chart on response to ranking Six Sigma
barriers

44
Table 4.3: Weighted score and the overall ranking of barriers following analysis
Weighted
score
Overall
ranking
Leadership 4.5 1
Time 4 3
Resources 4 3
Training 4.25 2
Project
Selection
3.5 5
The following ranking of barriers was produced, thus supporting H3.
• Leadership
• Training
• Time, Resources
• Project Selection
Other barriers were mentioned by respondents such as lack of control, where
companies are completing green and black belt projects but are not effectively
profitable; another barrier mentioned was customer work share, which means that the
order of a customer with 2% of the orders with tier 1 would be delayed, as the company
may find it difficult to allocate time and resources if they have 95% the orders from a
different customer.

Discussion Chapter 5
45
Chapter 5 Discussion
The purpose of this chapter is to discuss the results of the research and their relation
to the hypotheses and whether the overall research question has been answered or
not.
5.1 Hypothesis
The research hypotheses were introduced in section 1.2; this section will link the
results and analysis conducted in Chapter 4 with the secondary data collected from
the literature review in Chapter 3.
H1 – Barriers effect to Six Sigma implementation
This hypothesis can be considered slightly supported by the analysis carried out in
section 4.4.2, due to lack of sufficient responses. However, based on the responses,
it can be assumed that these barriers affect the success of Six Sigma implementation,
depending on the type of barrier. For instance, if the barrier were lack resources
caused by misleading a project, it will result in a delay in project completion.
H2 - Quality management maturity can be measured using various tools
This hypothesis was answered in section 4.4.1 when the respondents categorised
their company quality maturity level using Crosby’s grid based on their understanding
of their company.
H3 - Some barriers are more important than others based on their impact to Six
Sigma implementation.
This hypothesis was answered in the last question of the survey in section 4.4.2, where
the respondents had to rank each barrier based on their critical effect on Six Sigma
implementation.
H4 - The Quality Management Maturity of a company can be identified by linking
it with the impact of the barriers
This hypothesis was answered in section 4.4.1 based on the responses received. As
the analysis shows when linking Leadership barrier with Crosby’s grid, that companies
give more importance and value to this barrier are more mature in quality management

46
aspect. However, this cannot be relied on due to the insufficient number of responses
received.
H5 - Suggested solutions to reduce the impact of the barriers.
This hypothesis was partially answered when the respondents were asked to state
their barriers in section 4.4.2; regarding the resources barrier, one of the respondents
recommended having a statistical process control system which helps keep track of
the data collected from a company’s processes. As for leadership, the democratic
leadership style was recommended to improve communication between the
employees and their senior managers; the structure of the company should be
reorganised to suit the democratic style, as recommended by N. Root III (n.d.). This
kind of leadership style would let the employees have an overview of the project scope
and participate in its selection. Furthermore, the senior manager would be able to
know the weaknesses of his employees and provide them with the required training.
5.2 Research Limitations
Like any research, there are a few constraints related to the data collection and
analysis methods. This incorporates the concept explanation, data analysis, and
potential bias related to questionnaire wording which is additionally examined in the
sections below.
5.2.1 Barriers
As the analysis showed, most of the common barriers are associated with senior
management as they are responsible for the key challenges faced when implementing
Six Sigma. As Deming (2000) explained, a large portion of the issues arising in a
business can be connected back to the management. Senior management has an
impact on the business culture, hierarchical structure, procedure, vision, and
boundaries.
The barriers to Six Sigma implementation in this research have been identified and
investigated. However, further research with senior managers should be conducted
to determine whether they are aware of the barriers and understand how much
influence they have over Six Sigma implementation.
Throughout the survey, a couple of new barriers were identified such as lack of control,
language and customer work share. Due to the design of this research method, these

47
barriers could not be added to the survey questionnaire. Hence, the researcher could
not assess the importance of these barriers.
5.2.2 Research Design
During the questionnaire survey, a few more questions that could support the research
questions did arise in the researcher’s mind, but the researcher could not add them
as the survey was in progress. Hence, it led to weakness in answering the questions
effectively.
5.2.3 Analysis
This research has insufficient data for analysis that could be able to strengthen the
hypothesis of this research; this is due to three main reasons. The first reason is the
small number of responses received on the survey from LinkedIn groups and email
contacts. The second reason is the lack of the use of tools such as Chi-square tests,
due to the limited time available to understand this tool and use it effectively. The last
reason is the wrong timing of starting the survey. These can be resolved by having an
in-depth future research.

Conclusion Chapter 6
48
Chapter 6 Conclusion
6.1 Research Question
This research was conducted to study the barriers affecting the success of Six Sigma
implementation in relation to quality management maturity in aerospace Tier 1
suppliers and to find possible solutions.
It can be concluded that with the analysis of the primary and secondary data collected
as part of this research, the research question has been answered. The common
barriers to Six Sigma implementation within the aerospace tier 1 suppliers were
identified and evaluated to show their importance.
6.2 Research Objectives
RO1 - Identify Six Sigma and quality management maturity concepts
It was difficult to identify a definition for Six Sigma as many definitions were found in
the literature. However, most of the definitions were agreed on many areas such as
reducing costs and deviations and training employees on the latest technology. As for
the quality management maturity concept, it was easy to identify its definition.
However, it was quite challenging to identify and understand all its models due to their
complexity.
RO2 - Identify the Tier 1 supply chain for the aerospace industry
The Tier 1 supply chain meaning has been identified and compared with the other
Tiers – Tier 2 and Tier3, although the Tier 1 suppliers were identified, and the
researcher was able to identify some companies who are categorised as Tier 1&2 at
the same time, which can be shown in section 1.12.
RO3 - Identify how these barriers are ranked both in the literature and from
primary research
The barriers to Six Sigma were identified and ranked in the literature review and
compared against the survey questionnaire findings regarding their importance, using
a ranking matrix, resulting in the following order of importance:
1. Leadership

Conclusion Chapter 6
49
2. Training
3. Time, Resources
4. Project Selection
Additional barriers were identified during the survey that was not investigated, such as
lack of control and customer work share.
RO4 - Analysing the impact of quality management maturity on the ranking
results
Based on the results from the survey and the cross-tabulation analysis comparing
quality management maturity with the leadership barrier, it was found that the more
consideration given to leadership the better the maturity level of the company.
6.3 Future Research
This research identified some potential areas for future research:
1. The senior management structure would be worth investigating as this research
shows that leadership is the most common and crucial barrier in any project.
2. Research on Lean Six Sigma and its barriers would be interesting as it is
recently being implemented in projects.
3. This research can be repeated with more data collected by conducting semi-
structured interviews in addition to an enhanced survey questionnaire.

References
50
References
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and Service Organizations’. International Journal of Quality & Reliability
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2. Amatech Inc (n.d.) Oems, Tier 1, 2 & 3 - The Automotive Industry Supply
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[27 October 2018]
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http://asq.org/learn-about-quality/quality-management-system/ [29 July 2018].
6. Asq.org. (2018) Define, Measure, Analyze, Improve, Control (DMAIC
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7. Atieno, O. (2009) ‘An Analysis of the Strengths and Limitation of Qualitative
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8. Banuelas Coronado, R. and Antony, J. (2002) ‘Critical Success Factors for the
Successful Implementation of Six Sigma Projects in Organisations’. The TQM

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