Developing a Hybrid Approach for Lean Six Sigma

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IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022 2897
Developing a Hybrid Approach for Lean Six Sigma
Project Management: A Case Application in the
Reamer Manufacturing Industry
Srijit Krishnan , K. Mathiyazhagan , and V Raja Sreedharan
Abstract—Lean six sigma (LSS) is a well-structured process
improvement methodology aimed at removing wastes and defects
to increase the operational efficiency of a process. In this article,
the authors were tasked to identify the root causes of the reworks
and rejections occurring in the polycrystalline diamond (PCD)
reamer line of a tool manufacturing industry and provide solutions
and implement methods to overcome the rejections. Therefore, the
author constructed a hybrid approach comprising the select, define,
measure, map, analyse, improve, control, sustain (SDMMAICS)
model to enhance the define, measure, analyse, improve, control
(DMAIC) approach. Further, decision-making trial and evaluation
laboratory (DEMATEL) was incorporated in the improve phase
of the LSS model to ensure effective decision making. The model
is backed by a KAIZEN framework to ensure the sustenance of
the improvements implemented. This hybrid LSS framework was
successfully applied and resulted in an increased sigma level from
3.3 to 4.3, improving the cycle time of PCD reamer production by
12%. The hybrid SDMMAICS-DEMATEL approach used is easy
to follow and can be adopted in any LSS project. Moreover, the
relevance of the model in a part manufacturing setup has been
effectively tested and will serve as a reference for researchers in
process improvement studies.
Index Terms—Decision-making trial and evaluation laboratory
(DEMATEL), KAIZEN, lean, PDCA, poka-yoke, process
capability, quality improvement, reamer, SDMMAICS, six
sigma, sustainability.
I. INTRODUCTION
THE Indian manufacturing sector has emerged as one of
the most developed sectors in India. With the push from
the “Make in India” initiative by the Indian Government, it is
expected that India would be placed in the world map as a hub
for manufacturing. This sector is widening its domain across
economic sectors by producing a diverse range of products to
meet domestic and global markets. This sector alone would cre-
ate 100 million jobs by 2022, create value in the domestic supply
Manuscript received 31 May 2020; revised 20 July 2020; accepted 28 July
2020. Date of publication 23 September 2020; date of current version 1 Novem-
ber 2022. Review of this manuscript was arranged by Department Editor E.
Kongar. (Corresponding author: K. Mathiyazhagan.)
Srijit Krishnan and K. Mathiyazhagan are with the Department of Me-
chanical Engineering, Amity School of Engineering & Technology, Amity
University, Noida 201313, India (e-mail: srijitkrishnan@outlook.com;
kmathiyazhagan@amity.edu).
V Raja Sreedharan is with the Department of Supply chain Management, Ra-
bat Business School, Université Internationale de Rabat, Rabat 11100, Morocco
(e-mail: raja.sreedharan@uir.ac.ma).
Color versions of one or more figures in this article are available at
https://doi.org/10.1109/TEM.2020.3013695.
Digital Object Identifier 10.1109/TEM.2020.3013695
chain and contribute significantly to the gross domestic product
[18]. Most manufacturers in India fall under the micro, small, and
medium enterprises category (MSMEs). PIB Delhi [32] reported
that 31% of (MSMEs) in India is engaged in manufacturing
activities. The machine tool industry of India has a good position
in the world market. There are more than 1000 machine tool
industrial units in the production of machines tools, attachments,
subsystems, and parts. India stands 12th in the production of
machine tools and 8th in its consumption. There is a need for
adding capacities in this sector given the current gap between
supply and demand [12]. The Indian tool manufacturing sector
has several opportunities for expansion driven by demand from
key consumers such as automobiles, aerospace, etc. Therefore,
developing capabilities and increased investments in this sector
would cater to increasing demands, and yield long-time benefits.
These efforts may be implemented through quality improvement
and quality management (QM) programs. For Indian manufac-
turers to position themselves for sustenance in the competitive
environment, tool manufacturers need to focus on their efforts
toward improving the quality of their processes, products, and
services. To deal with declining profit margins, these companies
are increasingly required to improve productivity, inventory
management, waste reduction, and value creation of their supply
chains [34]. With various schemes and policies support by the
Indian Government, several of these companies have begun
focusing on building their global competitive advantage through
quality improvement initiatives. Nevertheless, these efforts are
in their infancy stage in both academic research and practical
application. The push to be globally competitive requires QM
strategies with visible returns and keeping with customer satis-
faction [54]. This article significantly contributes by providing a
model-based on Lean six sigma (LSS) for quality improvement
project in an Indian tool manufacturing company.
Every industry is striving to dominate and take a leading posi-
tion in its target market. For this, firms aim for higher sales highly
impacted by the quality of the product and its cost. The LSS
management philosophy is based on the theory that to achieve
lower costs and improve customer loyalty, reduction in defects
is an effective approach. Developing product quality is essential
to gain a competitive advantage for profitability and customer
satisfaction [6], [55]. Though traditionally, importance relies on
measuring output and instituting controls, LSS aims to eliminate
them in the first place. LSS is widely used and accepted to both
researchers and practitioners [57]. Hence, quality improvement
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https://orcid.org/0000-0003-4323-3405
https://orcid.org/0000-0002-2340-7394
https://orcid.org/0000-0003-3601-8002
mailto:srijitkrishnan@outlook.com
mailto:kmathiyazhagan@amity.edu
mailto:raja.sreedharan@uir.ac.ma
https://doi.org/10.1109/TEM.2020.3013695
2898 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
is most sought after by companies ranging from small scale to
large corporations.
As far as an application framework is concerned, define,
measure, analyse, improve, control (DMAIC) is the most widely
used. However, there are cases where the DMAIC frame-
work was critiqued to be ineffective in some organizations [2].
DMAIC lacked proper alignment to organizational goals, lead-
ing to incorrect project selection, unsuccessful deployment, and
inability to sustain the results obtained from project execution.
Literature provides various frameworks developed to address
these shortcomings. Majority of these frameworks are theo-
retical and lack validation through case application. However,
Sreedharan and Sunder [45] developed and validated the SD-
MMAICS framework to address the shortcomings of DMAIC.
This novel framework introduces three new phases in addition to
the conventional DMAIC that include the “select,” “map,” and
“sustain” phases. Further, Pareto analysis was used to choose
the critical to quality (CTQ) dimensions using their frequency
values and used for further analysis. However, the other CTQ
dimensions were not considered due to lesser frequency values.
Similarly, many kinds of literature ignore the observations from
multiple dimensions, which could be used for improvement
initiatives.
Also, from previous studies, it was found that there is a
significant relationship between LSS projectspp. 1–6.
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2914 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
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Srijit Krishnan received the bachelor’s degree in
mechanical engineering from Amrita School of En-
gineering Coimbatore, Coimbatore, India, in 2017,
and the master’s degree in industrial and production
engineering with distinction from the Department of
Mechanical Engineering, Amity University, Noida,
India, in 2020.
He has been partaking in process improvement
projects and is a Certified Black Belt in Lean Six
Sigma. He is currently engaged as a Patent Analyst in
a reputed firm in Delhi under the Intellectual Property
Rights Division – Engineering. His research interests include lean six sigma,
TQM, process simulation & analysis, operations research and machine learning.
K. Mathiyazhagan received the Ph.D. degree in
industrial engineering from National Institute of
Technology, Tiruchirappalli, India, in 2014, and
the postdoctoral degree in sustainable supply chain
from the University of Southern Denmark, Odense,
Denmark, in 2017.
He is an active Researchers and Academicians in
the field of Sustainability and Multicriteria Decision
Making. Currently, he is an Associate Professor with
the Department of Mechanical Engineering, Amity
University, Noida, India. He has authored or coau-
thored in top tier journals, including the International Journal of Production
Economics, International Journal of Production Research, Production Planning
and Control, and Journal of Cleaner Production.
Prof. Mathiyazhagan is the recipient of the Excellence Citation Award by
Emerald Publisher Ltd. Also, he is currently an Associate Editor of Environment,
Development and Sustainability - Springer- Impact Factor 2.1 and edited many
special issues in International journals.
V Raja Sreedharan received the graduate degree in
industrial engineering and the Ph.D. degree in lean
six sigma from the College of Engineering Guindy,
Anna University, Chennai, India, in 2013 and 2017,
respectively.
He is currently an Assistant Professor with the
Supply Chain Management, BEAR Lab (Business,
Economie et Actuariat), Rabat Business School, Uni-
versité Internationale de Rabat, Morocco. He has
published many works in top tier journals. He also
consults in the field of Process Optimization with
industries in private sectors. His current research interests are in the field of
managing the VUCA in business operations, and process improvement for
services industries.
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 >>
>> setdistillerparams> setpagedeviceand business per-
formance. However, the relationship differs for every project and
has a nonlinear pattern, which influences the decision taken in
the LSS projects. Moreover, no LSS project has reported on the
nonlinearity in the LSS project evaluation. Further, the available
information is not adequate to prioritize the key dimension for
the initiatives and no measure was considered to address the
nonlinearity in the LSS project evaluation. Therefore, the authors
have proposed, a hybrid approach, which integrates the SDM-
MAICS with the DEMATAL for identifying the key initiatives
in the improve phase and thereby enhancing the LSS project
management. Further, the hybrid approach, identify the key
dimension for a given project which can reduce the nonlinearity
in the process evaluation.
In this article, we apply and enhance select, define, measure,
map, analyse, improve, control, sustain (SDMMAICS) by in-
troducing DEMATEL. DEMATEL is a strong tool, capturing
group knowledge and precisely establishing a cause-effect re-
lationship in a problem measurement. The previous study by
Gupta et al. [15] used the DMAIC and DEMATEL model in their
study, where DEMATEL was used as a project selection tool.
However, in the present study, SDMMAICS is integrated with
the DEMATEL to prioritize the key dimension of LSS projects.
Further, the DEMATEL is used to address the nonlinearity in the
decision-making process in various phases of the SDMMAICS.
Furthermore, this article also brings in a KAIZEN approach into
the framework toolbox to enhance the feature of the LSS project.
KAIZEN focuses on the continuous improvement feature of LSS
projects. Once project goals are obtained, it is good practice
to not only sustain but continuously seek improvements in
performance and quality standards.
The hybrid approach applicability is illustrated through its
deployment in a medium-scale tool manufacturing firm facing
reworks and rejections in their polycrystalline diamond (PCD)
reamer manufacturing production line. Major costs associated
with reworks and rejections were realized by the management.
This affected customer delivery adherence to about 70% only.
So, to improve the productivity of the firm, the management LSS
project is reported in this article.
The rest of this article is organized as follows. Section II
provides a literature review, followed by Section III that presents
the methodology followed under this case study. Section IV
illustrates the use case of the aforementioned SDMMAICS–
DEMATEL model. The results are discussed in Section V,
followed by Section VI, which concludes this article.
II. RELATED WORKS
A. LSS in Part Manufacturing
LSS is ultimately aimed at achieving success in achieving
the satisfaction of customer requirement and not to meet the
internal requirements. Additionally, the business’ sustenance
heavily relies on its internal and external process efficiency [8].
LSS is a philosophy focused on achieving operational excellence
[23]. To generate maximum monetary benefits and competitive
advantage, a considerable number of global organizations have
used LSS [50]. Literature provides several definitions for LSS
[10], [21]. It is a problem-solving methodology, to identify and
validate the root cause of process problems. Since intuitionistic
based solutions do not help identify root causes, this scientific
methodology is used [34]. LSS has proven to be a powerful
philosophy [31], [39]. Lean philosophy is used to create the most
value for the customer, while the least amount of resources is
consumed for designing, building, and sustenance of the product
[17], [60]. LSS is an integration of tools and techniques of
waste elimination (lean) and the SS tools and techniques for
variation reduction. Companies combine lean tools into the SS
framework to achieve a higher degree of competitiveness [56].
LSS has widespread application in the manufacturing sector.
Its applicability in improving process performance is evident
from literature [25], [48]. The LSS roadmap has advocated
design thinking and has been frequently used to bring about
breakthrough improvements in the manufacturing sector. Many
works of literature provide cases of LSS applicability in manu-
facturers to achieve higher process capabilities, reduced costs,
and improved organizational performance [1].
B. LSS Hybrid Model
LSS does not target a single quality characteristic, it rather is
an approach for continuous improvement. All dimension of busi-
ness processes that are critical to the customer are focused upon
and LSS identifies and eliminates the root causes of defects under
these dimensions [43]. Organizations aim to achieve bottom-line
improvements to realize increased customer satisfaction and
an expanded reach of the market [53]. As pointed out in the
previous section, the application of multiple criteria decision
making (MCDM) into the LSS model has a limited presence
in literature. MCDM tools have extensive applicability in both
academic research and industry [11].
LSS is widely recognized as a statistical approach with
QM tools incorporated in it. However, problems such as
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2899
TABLE I
REVIEW SUMMARY
multidimensional defect prioritization, production planning
and services, training unskilled and semiskilled operators,
waste management, resource allocation, and investment
decisions cannot be handled using LSS alone. However, they
can be effectively tackled using MCDM techniques [53],
[47]. The goal of MCDM is to support decision makers by
ensuring the most effective decision/course of action that the
company should take to manage operations involving multiple
criteria, incorporating well into the LSS framework [46]. Also,
continuous improvement requires utilization of both qualitative
and quantitative information and play a significant role in an
efficient and effective business process [9]. Therefore, MCDM
must be integrated into the LSS structure by practitioners to
enhance LSS applications and for the sustenance of the value
of LSS for improvements in business processes [47]. Literature
provides many instances where researchers integrated LSS with
MCDM tools like DEMATEL, analytical hierarchy process,
analytical network process (ANP), and goal programming [19],
[36], [15]. However, due to limited availability of literature
establishing the use of MCDM in LSS phases, practitioners’
acceptability of these tools is low and hence limits the capability
of LSS in strategic decision making. In this article, we use the
MCDM technique for a decision-making quality issue in the
implementation phase of the SDMMAICS implementation in
the reamer manufacturing process. We provide a listing of few
studies in literature where MCDM has been integrated with
quality improvement programs (see Table I).
C. Addressing Limitations of DMAIC Using SDMMAICS
Although there is plenty of evidence that DMAIC leads or-
ganizations to significant performance improvement, there is,
however, room for improvement. McLean et al. [24] claimed
that the DMAIC framework does not consider the sustainability
of the results of its implementation. LSS focuses on continuous
improvement and emphasizes on achieving long-term sustain-
ability of process improvement, which is not addressed in the
DMAIC methodology [42]. Pinedo-Cuenca et al. [33] pointed
out that projects suffer due to project teams rushing to finish
projects and as a result not ensuring sustainability.
Most frameworks lack practitioners or consultants, hence, a
rigorous framework is needed to validate project benefits [37].
Continuous improvement projects fail due to failure in linking
the business goals to the project methodology, so, a customized
SS framework should address this issue. Furthermore, one of
the main reasons for project failure is incorrect selection.This
becomes more apparent when these projects do not align with
the business’ goals ([35], [57]).
Sreedharan and Sunder [45] expanded on the limitations of
DMAIC and conceptualized a new framework, SDMMAICS.
The SDMMAICS is claimed to fill in the gaps addressed by
DMAIC implementation. Sreedharan and Sunder [45] devel-
oped this framework based on data from manufacturing in-
dustries. This novel model supports the effective deployment
of LSS projects effectively. It is also flexible enough to ac-
commodate business goals and provide sustainable measures
to the improvements. The select phase of the novel framework
ensures an effective project selection by capturing the driving
and restraining forces of a project. The map phase enriches LSS
by further synergizing lean and SS. The sustain phase ensures
the control phase maintains and does not deviate from the
project objectives even after several months. The sustain phase
pushes the control phase to ensure process stability postproject
by reviewing the possibilities to improve process performance
are monitored. DMAIC is considered the most common and
effective of the various available frameworks, though, it has
been used extensively. SDMMAICS, however, fills the gaps
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2900 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
in the DMAIC framework, making it more effective in LSS
projects. In this article, the SDMMAICS framework is further
enhanced by incorporating an MCDM tool. Literature does not
provide a setting where several dimensions to improvements but
insufficient information to prioritize the major dimensions [15],
[47]. Tang et al. [53] reported that most SS tools and methods
are drawn from statistics or part of QM theoretical developments
[16]. Gupta et al. [15] suggested that MCDM tools such as
DEMATEL intensifies the effectiveness and broadens the appli-
cation of LSS projects. Gupta et al. [15] utilized DEMATEL
as an enhancement feature of the DMAIC framework. With
this take, the DEMATEL tool has been applied in the improve
phase of the new framework, hence expanding the toolkit of LSS
with MCDM-based methods. This hybrid framework empowers
employees, management of stakeholders, and also the narrow
project only approach of deploying LSS in a process [45].
D. Approaching Reamer Production Issues
Reamers are fluted multiedge cutting tools having applica-
tions in a widespread of industrial sectors to enlarge, accurately
sizing, and smoothening existing holes on workpieces. The qual-
ity of the bore is affected mainly, not exclusively, by the reamer
properties and dimensions [28]. Reamers have a high demand
in the manufacturing sector. The quality of the end product is,
therefore, crucial to ensure customer satisfaction and sustenance
of the company in the global market. The case company has not
implemented automation, and this exposes the production line
to various dimensional quality issues as a result of traditional
manufacturing methods. The company has been experiencing
major reworks and rejections of reamers due to inaccuracies in
dimensions as per customer requirement. This being a quality
issue, this called for a strategic quality improvement program.
To resolve the big problem, that is the big “Y,” the root causes
were required to be identified and resolutions were implemented
for improvements based on data and various quality criteria in
reamer production.
The case company had previously deployed LSS under
DMAIC, however, its use was not effective. First, there have
been previous instances in the case company when projects
conducted had not achieved its objective, resulting in wastage
of time and money. This was a frequent threat to the firm as
they had not attempted a project selection evaluation previously.
Second, it was identified that there was less practice of lean in
the manufacturing line. Employees only focused on achieving
the target for the day rather than strategically operate using
a methodical practice such as lean. Finally, with increasing
demand for reamers, it was necessary to ensure sustenance of
the production process to ensure that future demands are met
with international quality and satisfied customers.
Considering the limited literature and LSS cases reporting
on the hybrid LSS frameworks, this article illustrates a case
report on the hybrid SDMMAICS–DEMATEL model for an
LSS project in a medium-scale manufacturing plant. With the
addition of DEMATEL, we also bridge the gap for practitioners
to address the nonlinearity in decision making. Further, the
authors specifically utilize DEMATEL rather than other MCDM
tools because it accounts for nonlinearity or biases in evaluating
the expert’s opinion and its applicability in different scenarios.
The sustenance of the LSS project deployment was ensured
by a customized KAIZEN model that the team developed. The
proposed SDMMAICS–DEMATEL can address the LSS project
needs in a better manner. Further, the majority of the models con-
stitutes statistically derived tools; methods and developments
in LSS. This leaves room for expansion of the available LSS
toolkit. However, limited studies have integrated MCDM and
managerial methods with LSS frameworks and findings from
such studies are in the early stage for generalization. So, in
the present work, DEMATEL in the improve phase, and also,
illustrates the incorporation of a KAIZEN model developed in
this article to ensure sustenance of the model aforementioned.
III. METHODS
The case study approach was used to illustrate how the LSS
project improves in-house rejection at a tool manufacturing
company by reducing the reamer tool production defects. The
associated implications and lessons learnt are also presented.
A case study approach is followed because it gives flexibility in
design and application. Further, both qualitative and quantitative
analysis can report effectively the organizational complexities
than pure quantitative methods [52]. Further, case study ap-
proach explores the complex and critical value chain activities in
the organization. This methodology is thereby relevant for LSS
implementation studies. A case study is advantageous because
it provides a first-hand and an in-depth understanding of a par-
ticular situation. It relies on direct observation and data capture
in a natural setting rather than relying on derived data [45].
In this article, a real-time problem of customer dissatisfaction
resulting from high production cycle time of reamer production
at a tool manufacturing company is examined and resolved using
the SDMMAICS–DEMATEL approach, however, the generality
of a single case study that can be claimed to be limited. However,
documenting the experiences from the case is a valuable addition
to the available knowledge for researchers and future practition-
ers. It is evident from the literature that case study research is
well-accepted by scholars. DMAIC has been used effectively by
both practitioners and scholars for LSS implementation in orga-
nizations for continuous improvement, however, it is found to
be unsuccessful in a few cases. SDMMAICS is a more powerful
approach to DMAIC with addition to the “select,” “map,” and
“sustain” phases. These eight phases strategically guide project
managers in LSS deployment from the initial step of project
selection, step by step LSS execution, and the sustenance of
project outcomes. Though SDMMAICS systematically follows
a sequence of phases, amendments can be made to it to suit
the context of the organization. It is, therefore, not a rigid
generalized guideline to LSS project deployment.
In most LSS applications, multiple quality dimensions pro-
mote improvement effort. For instance, Gijo and Scaria [14]
applied LSS to improve the first past yield for the honing process
in an automotive parts manufacturing unit. Whereas, in the case
when more than one critical quality dimensionsare identified,
Pareto analysis is used to prioritize them. It is worth noting that
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2901
Pareto requires large datasets for prioritization related issues
and obtaining such large data could not just be costly, but also
time consuming [63]. Existing literature does not provide sce-
narios when several dimensions are analyzed wherein efforts for
improvement can be targeted but with insufficient information
to prioritize the key dimensions. Therefore, in this study, an
analytical approach illustrates the application of DEMATEL, an
MCDM tool, to prioritize CTQ factors of the electron discharge
machine (EDM) process in the improve phase of SDMMAICS,
thereby expanding the LSS toolkit. DEMATEL is used here
because it helps to evaluate nonlinear relationships and also
accounts for biases in decision making.
LSS tools such as force-field analysis, project charter, suppli-
ers, inputs, process, outputs, and customers (SIPOC), Ishikawa
diagram, process capability, gage R&R, Pareto analysis, Takt
time analysis, and control charts are used in the case study
following SDMMAICS. As aforementioned, DEMATEL is em-
bedded in the framework, making this article unique in the
perspective of literature and live application. Since the step by
step SDMMAICS methodology has been already captured in
detail by Sreedharan and Sunder [45], we present an overview
as follows.
1) Select phase: Emphasize the correct selection of the LSS
project aligned with the business priorities.
2) Define phase: Understand and formulate the problem.
3) Measure: Understand thoroughly the current state of the
process, and reliable data are collected to underlay the root
causes of problems
4) Map: Strengthen the lean aspect of LSS. In this phase,
process-oriented tools may be utilized to identify causes
through visual methods.
5) Analyze: Identify the root causes of issues in the process.
6) Improve: Selects these process characteristics (X’s) that
need to be improved to mitigate or eradicate Y. The im-
provements are suggested and implemented. DEMATEL
tool is embedded in this phase to prioritize the quality
features that require improvement in the EDM process.
The details of the steps undergone for DEMATEL are
provided in the Appendix.
7) Control: Ensure that the implemented process conditions
are continuously monitored using control charts and doc-
umented.
8) Sustain: An extension of the project for monitoring beyond
the control phase to ensure that the benefits from the LSS
project sustain on a long-term basis.
A. Data Collection
Depending on the phase, data capture methods varied from
brainstorming sessions, direct measurements from operations,
and historic data from the line manager. We present the capture
methods accordingly under each phase of case illustration. The
project spanned three months, during which time, visits were
made only when direct interactions or brainstorming sessions
were required. This included visits during the select, define and
improve phases. Otherwise, quantitative data were captured by
the line manager and shared with the team. Data were collated
in Microsoft Excel and basic analysis was done on it. Minitab, a
statistical software tool was used for complex data analysis. This
software was used due to its ease of use. Results generated from
the software are in a standard format for data presentation. The
word “standard” meaning the output is presentable and easily
understood.
IV. USING THE SDMMAICS–DEMATEL MODEL:
A CASE ILLUSTRATION
A. Case Background
This article aimed at improving the quality of the PCD reamer
production line by reducing reworks in a tool manufacturing
plant located in the northern region of India. The plant is a
division of a major group, set up in the early 1990s and is
involved in the production of reamers, drill bits and various
other tools for industrial application. The company has grown
exponentially employing about 1000 people with operating rev-
enue of up to Indian Rupee (INR) 500 crores. The organization
has plants spread across the Indian subcontinent with clients
ranging from small-scale local industries to major clients across
the world. The reamer line provides major income to the specific
manufacturing unit in which the study was conducted. However,
the plant has been experiencing high lead times in PCD reamer
production resulting in adherence to on-time delivery of finished
products only about 70% of the time. To maintain commercial
confidentiality, limited details of the firm are disclosed. The
management team was anxious to improve customer satisfaction
levels to establish higher quality standard in their organization.
As there was a lack of a system to measure the current state
of the production process, an LSS team was created to evaluate
the current scenario in the production line. It must be noted that
this is a manufacturing firm that followed DMAIC methodology.
However, it was expressed by management that past instances of
failure in LSS deployment. These varied from improper project
selection due to the rush of completing it, lack of knowledge
of the spread of toolkit and lack of sustenance of project out-
comes over a long period. The project was therefore initiated to
follow SDMMAICS to mitigate reworks and rejections within
the reamer line. The project plan was designed and initiated by
the LSS team. The team consisted of an LSS black belt, two
university professors, the floor supervisor, and the line manager.
As per the direction of the management, a nonstructured inter-
view with the process stakeholders was done to understand how
satisfaction levels of the clients can be improved. Most of the
stakeholders expressed concern in the cycle time of production
due to excess reworks during processing. The management felt
the root cause needed to be understood, the team was tasked with
finding an effective fix by taking this issue as an opportunity for
the project.
A force-field analysis was developed by scoring each of the
change factors identified by a meeting session of the team with
the line manager was scored (see Table II). The scores for each
force were provided. Each force was scored from 1 (weak) to
5 (strong) based on the degree of influence each force had on
the plan to implement LSS. The scores are then added up for
either side (for and against). Since the total “for” conducting the
project exceeded “against” by six points, it was decided to move
forward to the next phase.
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2902 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
TABLE II
FORCE-FIELD ANALYSIS
TABLE III
PROJECT CHARTER
B. Define
To evaluate the various project charter elements, the LSS team
conducted conversational interviews (structured, one-on-one)
with the production head and the reamer line manager. Sub-
sequent to this interaction, the LSS team defined the business
case, problem statement and the goal of conducting the project.
The purpose and scope of the project is captured well in the
project charter (see Table III). It also defines the expectations of
quality from the project. The project charter was submitted to
the management and sanctioned by the plant production head.
A process mapping in the form of SIPOC was then generated
after a study of the entire production process (see Table IV). The
SIPOC gives a helicopter view of the project. With this tool, the
team was able to identify all relevant elements of the process
improvement effort before work began.
C. Measure
The LSS team held brainstorming sessions with personnel
associated with the reamer production line that includes the
production supervisor and the operators to identify the effects
the bigger “Y,”that is, dimensional variation (see Fig. 1).
The DPMO for the reamer line has been calculated and sub-
sequently, the process capability determined considering the 1.5
sigma shift (MJ [27]) is summarized in Table V. The long-term
sigma refers to the actual sigma level the process undergoes.
Short-term sigma signifies the best level the process can undergo
in a finite period under ideal conditions.
The LSS team consulted the production staff associated with
the reamer line to identify the machinery that results in most of
the rejections/reworks, the total machinery-wise reworks for the
past one year were collated and a Pareto chart generated (see
Fig. 4). Pareto analysis helps to focus attention on just a few of
the vital factors of the process instead of all the factors.
Based on Fig. 2, it is observed that CG, VOL, and PG20
account for 80% of the total rejections/reworks. It must be noted
that though CG, PG20, and TCG are separate workstations, their
function is essentially the same that is, grinding. This analysis
was used to discuss the progress of the study with the production
team at the plant. The discussion led to narrowing down of the
potential “X”s to be associated with grinding and EDM. These
“X”s identified as the potential causes of dimensional variability,
is presented in Table VI.
1) Repeatability and Reproducibility (R&R): To conduct a
gage R&R, six reamer parts were measured to determine the
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2903
TABLE IV
SIPOC
Fig. 1. Ishikawa diagram for reworks/rejection of reamer in the production line.
TABLE V
EXISTING PROCESS CAPABILITY CALCULATION
tolerance after operations on a CG were done. The upper limit
of tolerance on diameter was at 0.003 mm. Measurement of
diameter was done by three operators for two trials each with six
TABLE VI
POTENTIAL “X”S
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2904 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
Fig. 2. Pareto chart of reworks associated with workstations.
Fig. 3. Takt time adherence of a batch order.
reamers to check adherence to diameter tolerance. The measured
values were noted and run in Minitab software. The ANOVA
gage R&R test results showed 91.03% against the Gage R&R
contribution of 9.97%; four distinct categories; and 29.96% of
tolerance out of the total variance. Based on general rules iterated
by Barbato et al. [3] for acceptance of measurement system
analysis (MSA), the three rules for Gage R&R passed and hence
concluded that the measurement system is acceptable for data
collection.
D. Map
The processes undergone by a batch order for the month was
analyzed, the takt time was calculated and the process exceeding
the takt time have been identified. Illustrated in Fig. 3 is the
representation of adherence of the various processes undergone
to the takt time in the reamer line to produce the final product.
With reference to Fig. 3, processes 2, 3, 4, 7, 8, and 9 are
various grinding processes in the reamer line. Processes 5 and
6 are EDM and brazing processes, respectively. This indicates
that these processes are taking much longer than the takt time.
Reworks are used to make up for defects and are the major reason
for nonadherence of the aforementioned processes to the takt
time. Processes 1 and 10 are manufacturing sheet generation and
final process of shank grinding, respectively. They can adhere
to the takt time and hence not a focus area. The insights from
this phase are further confirmation of the findings in the measure
phase.
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2905
Fig. 4. Pareto chart of potential “X”s.
TABLE VII
ROOT CAUSE VALIDATION METHOD AND IDENTIFICATION
E. Analyze
As mentioned in the earlier section, it is concluded that the
grinding and EDM processes need to be analyzed. Defects
including “size less,” “aesthetic,” “fouling,” “size plus,” “runout
not ok” are a result of grinding in the production line in either
of the grinding workstations. “Chipping” of the PCD tool and
“coolant hole not ok” are EDM induced defects. “Operation
missing” is a defect caused by operator negligence. Sometimes
the sequence of processing may not be followed exactly as pro-
vided in Table IV. This may lead to the operator unintentionally
neglecting to perform a machining operation on the workpiece.
The quality department identifies the missing operation and
notifies the line in-charge. The LSS team studied the grinding
and EDM processes over one month and the number of rejections
due to the “X”s identified and prioritized (see Fig. 4). The Pareto
analysis shows that the “size less” contributes most, closely
followed by “aesthetic,” “fouling,” “operation missing,” “size
plus,” “chipping,” and “runout not ok” account for 80% of the
total defects.
Some of these “X”s were validated by GEMBA method
whereby the process was observed, and a decision was taken
if it was a root cause or not (Refer Table VII). The remaining
causes were analyzed through process capability analysis to
test if the process can perform within the specifications. The
reamer production process was observed by the team at random
frequency during one month and observations for 25 reamers
were noted. Since the reamers being ordered were in batches of
small numbers of varying specifications, it was decided to collect
the runout and the oversize from the target diameter. Normality
of runout and oversize data was tested and p-values 0.520 and
0.061 were obtained. A p-value > 0.05 indicates normality of
data. Hence both sets of data collected were normal. A process
capability analysis was performed using the collected data, and
capability plots for size plus [see Fig. 5(a)], and runout [see
Fig. 5(b)] generated. Both plots indicate the capability “within”
the sample and the overall (that is, population) capability does
not conform to the specification. It can, therefore, be concluded
that size plus and runout are root causes. Based on the analysis
done, the root causes have been identified and summarized in
Table VII.
F. Improve
Discussions were made and the root causes were further
divided into subclauses. A solution to each of these subcauses
was proposed. Grinding related issues were identified to be
caused mostly due to the use of inefficient grinding wheels. The
replacement of cubic boron nitride (CBN) grinding wheels was
proposed. Furthermore, installing a rotational dog was proposed
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2906 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
Fig. 5. (a) Capability plot—Size plus. (b) Capability plot—Runout.
TABLE VIII
CLASSIFICATION OF DEFECTS INTO CAUSE AND EFFECT GROUPS
to ensure alignment issues of wok piece holding for the grinding
process. It was found that chips formed during grinding were
affecting the process, hence, it was suggested to install a dispose
vane. Further, to identify the major influencing factor in the EDM
process, DEMATEL was used to priorities the key dimension
based on the expert’s inputs. It must be noted that previously,
it was not possible to establish direct relationship between the
influencing quality dimensions. However, this nonlinearity in
relationship of the critical quality factors with regard to the EDM
process was established using DEMATEL. In the DEMATEL
analysis, it was required to create a pairwise matrix. The initial
matrix was created based on response from two EDM operators,
aline supervisor and the production manager. The responders
were asked to rate the level of influence in a five-point Likert
scale with “0” being “no influence” to “5” being “very high
influence.” Following the DEMATEL steps enumerated in the
Appendix section, the responses were averaged to obtain the
average direct relation matrix (matrix A), which was then nor-
malized to matrix X. A total relation matrix (T) is then obtained,
from which the summation of horizontal values of the matrix
represented by “D” and the vertical summation represented by
“R.” From this, we arrive at Table VIII, illustrating a calculation
for each individual CTQ factor affecting EDM. D–R values
classify factors into either a cause or an effect. For values of
D–R greater than zero, we classify them as cause factors, and for
those values below zero are effect factors. D+R values indicate
the level of prominence of the factors. These values are further
used to create the cause–effect and prominence graphs (see
Figs. 8 and 9). As we are focused on identifying the causes for
reworks/defects in this process, we identified from DEMATEL
application that V3, V4, V5, and V7 are cause factors. However,
V7 had the highest cause rating of 1.11. Furthermore, D+R
values indicate highest prominence on V7. For this reason, it
was concluded by the LSS team that Impurities from brazing
(V7) was the factor most critical to the EDM process undergone
in the plant.
This claim was, therefore, verified through the DEMATEL
approach (Refer the Appendix). It was identified that the brazing
operation was exposed to impurities and a solution to this would
be to install an inert atmospheric glove box to perform the
joining operation. Another major problem was the issue of
operation missing. This problem is induced by the improper
system to ensure no operation goes undone. To address this,
it was suggested to use color coded vacuum bags to ensure a
systematic flow of workpiece in the line. The remedies proposed
are summarized in Table IX. The details regarding improvement
remedies are detailed in Section V. Postimplementation, we
calculated the sigma level and based on data for one month.
A short-term sigma level of 4.3 and long-term sigma level of 2.8
was achieved, elaborated further in Section V.A.2.
G. Control
Making sure that improvements are standardized and moni-
tored is necessary to stabilize the improvements. In this phase,
the SDMMAICS aimed to stabilize operations after improve-
ments where implemented. Postimprovements in the reamer
line, short-term sigma level of 4.3 were achieved from 3.3
calculated preimplementation. Furthermore, the cycle time of
production was reduced to 17.6 d from the baseline 20 d. Once
stabilized, the project team documented all activities on the
project pre- and postimprovement. Employees were trained on
the standard operating procedures to ensure improved process
performance is maintained. It was recommended to process
stakeholders that regular sampling is done to ensure process
performance is monitored. The plant maintains statistical pro-
cess charts to ensure that processes are controlled and within
the limits set out by the required quality. This ensures that any
special causes occurring in the future may be identified and
removed immediately. To check for process control, a p-chart
for fraction defectives was generated (see Fig. 6), indicating
conformance of reamer production within the control limits.
H. Sustain
A major challenge of LSS is not implementing the improve-
ment changes but making sure that the improvement sustains
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2907
TABLE IX
SUMMARY OF SOLUTIONS PROPOSED
Fig. 6. P-chart of defectives.
[14]. It has been shown in the literature that maintaining im-
proved results can be challenging due to people changing jobs
[13]. Since the manufacturing plant was ISO 9001:2015 cer-
tified, they follow standardized documenting procedures and
LSS was documented. This serves as a basic training document
for future employees of the firm. It was proposed that existing
employees be provided with regular training sessions to upscale
the available skills in the firm. It was suggested that at least
green belt level LSS training be provided to employees all the
while using the SDMMAICS as a framework with inclusion of
various tools from OR and QM techniques to enhance project
capabilities. This ensures that the learning from previous phases
could be applied, transferred, and shared across the organization
to yield long-term benefits. The team further suggested the
creation of an internal team involving process stakeholders post
their LSS training. The internal team would be tasked to process
innovation in the plant. As a result, providing KAIZEN ele-
ments of improved morale, personal discipline, and teamwork,
KAIZEN based model was proposed and illustrated in Fig. 7.
V. RESULTS AND DISCUSSION
A. Process-Wise Remedies
1) Grinding Cost-Effective Improvement: It was proposed to
use time–frequency analysis by inspecting the quality of the
surface by monitoring the surface topography in one revolution
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2908 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
Fig. 7. Sustain—a KAIZEN approach.
of the workpiece (see [7]). Superior grinding performances may
be achieved with CBN grinding wheel, super abrasive wheels,
which achieves long-term stable performance and long dressing
interval compared to the Aluminum oxide wheels currently
being used in the plant [22]. As an added benefit, CBN has a
positive impact on the aesthetics of the workpiece.
Energy effective improvement: Majority of the grinding en-
ergy goes into overcoming the friction between the workpiece
and grinding wheel [29]. A water-soluble coolant may be used
instead of an oil-based one to provide effective cooling at the
grinding zone of the reamer workpiece, which is ordinarily under
high temperature and pressure. Furthermore, using the CBN
wheel as mentioned earlier will provide performance grinding
by reducing energy associated with chip formation without
inducing excess strain or deformation.
Retrofit solution/modification: Fouling occurs when the
ground material moves into areas, where various adjustable
mechanisms are located or bearing areas, hence forcing the
operator to stop the grinding machine, disassemble, and clean.
A solution to this problem is to provide a suitable dispose vane
closely confronting the housing designed to direct material in
an outward direction under the direction of the outward flow of
air toward the discharge outlet.
Furthermore, the coolant used during operations may consist
of impurities. This can be mitigated with the use of coolant
filtration systems, one that is capable of automatically cleaning
out the contaminants from the filter itself, meaningless effort
from the operator’s side to clean the filter. The grinding process
carried out in the production line is done between centers.
Though, it is the most widely used work holding method, it has its
limitations, one of them being workpiece deflection, resulting in
diametrical inaccuracy. The proposed remedial action to address
the issue of cylindricity and low workpiece clamping stiffness
was to retrofit a rotation dog that connects to the headstock.
During the grinding process, this fixture would ensure that the
centers remain in solid contact with the center of the workpiece.
2) W-EDM: The PCD chipping off was a major concern.
Crack in the PCD would mean rejection of the workpiece and
a monetary loss for that workpiece. Various quality factors may
be associated with the EDM process; however, it was neces-
sary to prioritize them, considering the feasibilityof possible
breakthrough remedial action. The DEMATEL tool was used
for factor prioritization involved in the EDM process. Eight
quality factors were identified by process operators and quality
inspectors. The eight factors being—impurities in dielectric
fluid (V1), defective electrode (V2), wire tension (V3), wire
bending (V4), wire vibration (V5), rate of material removal (V6),
impurities from brazing (V7), PCD surface roughness (V8).
The steps iterated in Section III.A were followed and resulting
graphs generated [see Figs. 8 and 9]. V7 indicates maximum
cause with a D–R value of 1.110. Furthermore, V7 indicates the
highest prominence of 2.64. It was therefore concluded by the
team to address PCD chipping issue by remedying the issue of
V7—impurities from the brazing operation.
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2909
Fig. 8. Cause–effect classification of defects based on D–R values.
Fig. 9. Prominence graph for defects with D+R values.
3) Brazing: The brazing operation is conducted manually in
an open environment and is susceptible to human error. This
leaves the process exposed to minute dust particles that could
lead to defects/reworks in the later stages of the reamer produc-
tion. This can lead to the potential build-up of internal stresses
within the PCD resulting in its fracturing during processing in
the W-EDM. An equipment solution to this was to use an inert
atmosphere glove box system to avoid any chances of impurities
affecting the final quality of output from the brazing operation.
4) Operation Missing: Missing an operation is due to negli-
gence from the operators’ side. To remedy this issue, an approach
for quality improvement may be adopted to achieve improve-
ments. Poka-yoke, meaning “mistake-proofing” in Japanese,
has gained wide acceptance among many industry practitioners
because of its effectiveness (STEWART and GROUT 2009).
The philosophy of Poka-Yoke may be used in the reamer line
to ensure that the final product is of high quality. Each of the
steps needs to ensure first-time-right quality before being moved
to perform the next function. A fixed-value type poka-yoke is
implemented, whereby the color codes are fixed to a specific op-
eration indicating its completion. A warning technique may also
be introduced, whereby a black sticker of different shape may
be stuck after the sticker indicating completion of the previous
operation, to indicate that the current operation is incomplete
and requires further processing.
B. Postproject Sigma Level
The solutions were proposed to the management, and post
discussions were approved and implemented within the target
date. Postimplementation, 36 defects were recorded during
one month. Following similar calculations as in Table V, a
DPMO of 2521 was achieved, short-term and long-term sigma
values of 4.3 and 2.8, respectively. The manufacturing plant
was able to improve its overall production line sigma level
from 3.3 (preimplementation) to 4.3 (postimplementation) with
99.739% yielding by reducing the number of rejections/reworks
of reamers. The LSS framework was effectively implemented to
improve the performance of the reamer production line. It was
earlier mentioned that it takes an average of 20 d to manufacture
a single carbide-based reamer. Postimplementation, the
cycle-time reduced to an average of 17.6 d, indicating a 12%
reduction. Also, the goal of reducing reworks and ultimately
cycle time was achieved within the target time.
C. Application of the SDMMAICS–DEMATEL
Previous quality projects in the case organization indicated
that the scenarios, where the multicriteria analysis was required,
it posed as a threat for project stalling. This halt in project ac-
tivities is related to the wastage of time and increased expenses.
Based on prior knowledge and experience alone, practitioners
used Pareto analysis, where multiple criteria were observed to be
possible root causes. Under such a scenario, practitioners have
gone back and forth with brainstorming sessions, assessing each
criterion rather than selecting the most prominent cause factor.
Similarly, in the case organization indicated that such efforts
previously resulted in poor cost-benefit. Before, the multi-CTQ
issues were addressed without a standard approach for better
solutions, which ultimately turned out to be a costly affair.
However, in the case illustration, the LSS team provide a clear
analysis for multidimensions with the DEMATEL technique
embedded in the improve phase to identify a key cause. The
LSS team was then able to focus their attention on improving
the issues related to the brazing operation, which was exposed
to impurities. Moreover, the DEMATEL can choose the better
alternatives and is not influenced by the ineffective due to low-
frequency outputs and overcomes the biases and nonlinearity in
the relationship among the evaluated factors in terms of cause
and effect for better improvement initiatives.
The SDMMAICS model proved to be a significant improve-
ment to DMAIC previously followed in the case organization.
Previous efforts in continuous improvement under DMAIC
showed misalignment of the project to the organizational goals.
Projects failed before they started, meaning, projects were not
aligned with the shop floor workers leading to poor results.
Previous attempts at DMAIC did not insist on better manufac-
turing practices, due to restraining among the stakeholders for
the project initiation. Moreover, it was noted that LSS projects
previously deployed did not yield lasting results in organizations
and the LSS practitioners were focused on completing the project
and moving over to the next before ensuring outcomes are sus-
tained. The SDMMAICS framework perfectly addressed these
issues in our case study. It was foremost ensured project aligned
with the business goals in the sustain phase. The execution
of the LSS model included personnel from operations level to
management, thereby making the project a combined effort with
knowledge transfer during and postproject through the transfer
of project documents. Furthermore, previous studies in the orga-
nization have indicated that lack of training programs is a major
limitation. We, therefore, proposed a well-structured KAIZEN
model to make sure the LSS teams’ efforts were documented and
training manuals created and handed over to the management.
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2910 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, VOL. 69, NO. 6, DECEMBER 2022
For this case study, there was the involvement of a Black Belt,
Postgraduate student, professors, and the product line experts
from the manufacturing unit itself. This facilitated the industry–
academia collaboration that is otherwise lacking in the emerging
economies. We recommend further projects in industries be
conducted in collaboration with academia to overpass the gap be-
tween the education and industrial sector. The case methodology
was followed under the SDMMAICS framework with DEMA-
TEL embedded into the framework. The SDMMAICS model
was selected due to the ineffectiveness of DMAIC projects
executed previously by the case organization. The SDMMAICS
fits perfectly to address the DMAIC shortcomings faced previ-
ously. Furthermore, with the inclusion of DEMATEL, the LSS
team was able to analyze multiple CTQ dimensions, where
low-frequency outputs are observed. Its application enhanced
management of the project, resulting in the identification of a
key root cause based on which a crucial improvement effort was
made in the reamer line. In this article, we propose a KAIZEN
approach, further adding to the LSS toolbox along with DE-
MATEL. The KAIZEN element was introduced into the sustain
phase as it is good practiceto ensure long-term sustenance of
project outcome. The SDMMAICS–DEMATEL was applied in
the reamer line of the case organization. Excess reworks within
the production line resulted in a long cycle time of about 20 d,
resulting in only 70% adherence to on-time delivery of final
products. Therefore, the management approved deploying the
LSS continuous improvement initiative to improve the quality
of reamer production and ultimately improve customer satisfac-
tion.
VI. CONCLUSION
A. Research Implication
This article contributes to the LSS-based literature by de-
veloping a hybrid approach of SDMMAICS–DEMETAL for a
business process to prioritize the key dimension in the processes
and address the nonlinearity in the process activities. Further, the
project sustenance was buttressed using the KAIZEN approach
in the sustain phase. Adding to the literature and acts as a
reference for LSS practitioners who wish to forego the traditional
application of DMAIC by adding the “select,” “map,” and “sus-
tain” phases. This framework focused on both process and data-
oriented approaches unlike DMAIC, which made senior leaders
sustain interest levels throughout the LSS project. The case illus-
tration resulted in a reduction in defects and ultimately reduction
of cycle time. The improvement in efficiency translated to better
quality output in the improve phase by identifying the cause and
effect in the EDM process and evaluating the nonlinearity rela-
tionship among the process dimension of the brazing activities in
the improve phase. Further, the values of D–R obtained from the
DEMETAL, we classify the process dimension as cause factors,
and for those values below zero are effect factors. From, the
D+R values, we can understand the prominence of each factor
and its contribution to the process evaluation.
B. Practical Implications
The use of SDMMAICS–DEMETAL in this article is a sys-
tematic hybrid approach for LSS project deployment in both
the manufacturing and service sectors. Moreover, the hybrid
approach has changed the way organizations handle problems
related to processes carried out within the firm. In the manufac-
turing sector, LSS leads to tangible improvements in products
being made and reduces costs associated with manufacturing.
The overall quality of manufacturing lines can be improved
through the application of LSS tools and techniques. The study
presented is an example of how applying LSS using the SDM-
MAICS methodology incorporated with an MCDM technique
can change the process and mindset of management and front-
end operators. The inclusion of DEMATEL was an effort to
analyze a case where multiple CTQs were involved and the non-
linearity in their relationship was to be determined. Practitioners
may incorporate DEMATEL to reduce time in deciding the
appropriate approach to multicriteria situations. This technique
is scientifically approved to solve such problems. The successful
implementation of LSS was achieved along with an improved
mindset by reducing reworks within the reamer production line.
This led to improved quality of reamers manufactured and higher
satisfaction at the customers’ end. The study first reviewed the
literature of lean and six sigma philosophies. The SDMMAICS–
DEMATEL framework was deployed in the reamer line of a
tool manufacturer in India. The application of LSS resulted
in several proposals for implementation within the production
line. Further, breaking the project only perspective, in the LSS
project focus on specific output for the project success. However,
adequate attention should be given to the side effect of the project
too. In this article, defect reduction was the main focus of the LSS
project, however, to improve the issues related to the EDM was
clearly evaluated using the DEMETAL approach, to understand
the cause and effect among the factors.
Hence, the LSS project was carefully evaluated and parallelly
the issue related to the EDM processes were analyzed to choose
the key dimension in the EDM process. This scenario proves
the LSS team had a broad view and understanding of all the
perspectives of the LSS project and breaking the narrow focus
for project metrics alone in the case evaluation. The postim-
plementation sigma level was calculated, and it was found to
have improved from 3.3 to 4.3. The cycle time for PCD reamer
production was improved by 12% allowing for faster delivery
of the finished product to the client. A KAIZEN approach was
further introduced to ensure project results sustain and improve
over time. During the conduct of this project, ideas across
different levels of the organization were encouraged for analysis.
Further, the SDDMAICS–DEMETAL for LSS projects allowed
to solve business problems at the strategic and operational level
to promote continuous improvement. Further, the LSS team
was formed to promote employee engagement, which is crucial
for continuous improvement. Furthermore, the participation of
the line manager, engineers and operators, and experts from
academia promoting idea creation promoting people perspec-
tive. For, instance, employee inputs were instrumental in the
force-field analysis for the project selection. Followed by the
expert’s input for process evaluation in the improve phase
empowering the employees and making them realize the use
of the hybrid approach. Further, the study exhibit, the total
participation of stakeholders, continuous improvement, and the
participant leadership are the three important enablers for the
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2911
successful LSS project [52]. So, we can say that organization
leaders are vital in deploying LSS [56], right from strategy
building to realizing benefits. The changes that can be expe-
rienced internally because of LSS are the transfer of knowledge
from the project to the company know-how and organizational
culture. Also, the users of this methodology can benchmark their
results with other quality initiatives in other organizations, to
enhance competitive advantage and result in better customer
satisfaction.
C. Limitations and Future Scope
This article was limited due to the unavailability of data to
measure the financial gains achieved through the SDMMAICS–
DEMATEL model and the short-time frame for study offered
LSS study under this framework only in the reamer line. This
article could go further into doing a cost analysis, however,
due to the discretion of the company in providing data related
to cost, a cost analysis was not done. This meant that it was
not possible to identify the monetary benefits of this project.
Furthermore, the process parameters were evaluated in the mea-
sure phase. However, there is a need to reduce the noise factor
in the process and choose the optimum setting for the reamer
production. Therefore, the future researchers can use design of
experiments to develop the optimal setting for the machining
process. Moreover, the nonlinearity in the EDM process was
identified in the improve phase and was addressed by the LSS
team. Still, the nonlinearity is a challenging entity that needs
to be evaluated further with the S-curve theory and also, the
researchers can address the pattern (Inverted U shape or S shape)
of the nonlinearity among the process dimensions, which can in-
crease the project deliverables significantly. As the future scope
of the study, two-dimensional outcomes need attention—First,
to test and validate the hybrid model in the service sector; And
second, exploring unique methods from various disciples to
expand LSS application for process excellence. Furthermore,
the proposed methodology could be expanded in the fuzzy and
grey environment.
APPENDIX
Steps in DEMATEL
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DEMATEL Data
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KRISHNAN et al.: DEVELOPING A HYBRID APPROACH FOR LEAN SIX SIGMA PROJECT MANAGEMENT 2913
ACKNOWLEDGMENT
The authors would like to thank Prof. T. Daim (Editor), three
excellent reviewers for their inputs and suggestions in refining
the work to achieve publishing standards. Also, the authors
would like to thank Prof. E. Kongar (Departmental Editor) for
her unconditional support in the review activities during the
COVID crisis.
Disclosure statement: The authors declare that they have no
conflict of interest.
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