CONSISTENCY OF DMAIC PHASES IMPLEMENTATION ON SIX SIGMA METHOD IN MANUFACTURING AND SERVICE INDUSTRY: A LITERATURE REVIEW

Abstract

High business competition demands business players to improve quality. The Six Sigma
with DMAIC phases is a strategy that has proven effective in improving product and service quality. This study aims to find the consistency of DMAIC phases implementation and analyze the objective value in Six Sigma research. By using a number of trusted article sources during 2005 until 2019, this research finds that 72% research in manufacturing industry consistently implemented DMAIC roadmap especially in case study research type for problem-solving, while service industry pointed out the fewer number (60%). The causes of variations and defective products in the manufacturing industry are largely caused by a 4M 1E factor, while in service industry are caused by human behavior, and it’s system poorness. Both manufacturing & service industry emphasized standardization & monitoring to control the process which aimed at enhancing process capability and organization performance to increase customer satisfaction.

Full text

Management and Production Engineering Review
Volume 11 •Number 4 •December 2020 •pp. 34–45
DOI: 10.24425/mper.2020.136118
CONSISTENCY OF DMAIC PHASES IMPLEMENTATION
ON SIX SIGMA METHOD IN MANUFACTURING
AND SERVICE INDUSTRY: A LITERATURE REVIEW
Aris Trimarjoko1, Humiras Hardi Purba1, Aina Nindiani2
1Master of Industrial Engineering Program, Mercu Buana University, Indonesia
2Industrial Engineering Program, Buana Perjuangan University, Indonesia
Corresponding author:
Aina Nindiani
Buana Perjuangan University
Jl. H.S. Ronggo Waluyo, Puseurjaya, Kec. Telukjambe Timur, Kab. Karawang, Jawa Barat 41361, Indonesia
phone: +62 02678403140
e-mail: aina.nindiani@gmail.com
Received: 8 July 2019 Abstract
Accepted: 20 July 2020 High business competition demands business players to improve quality. The Six Sigma
with DMAIC phases is a strategy that has proven effective in improving product and ser-
vice quality. This study aims to find the consistency of DMAIC phases implementation and
analyze the objective value in Six Sigma research. By using a number of trusted article
sources during 2005 until 2019, this research finds that 72% research in manufacturing in-
dustry consistently implemented DMAIC roadmap especially in case study research type
for problem-solving, while service industry pointed out the fewer number (60%). The causes
of variations and defective products in the manufacturing industry are largely caused by
a 4M 1E factor, while in service industry are caused by human behavior, and it’s system
poorness. Both manufacturing & service industry emphasized standardization & monitor-
ing to control the process which aimed at enhancing process capability and organization
performance to increase customer satisfaction.
Keywords
Six Sigma, DMAIC, manufacturing industry, service industry.
Introduction
The increasing competitions in the industrial sec-
tor worldwide affect business players to choose the
proper strategy. Providing quality products and ser-
vices is one strategy for staying ahead of that com-
petition [1]. Quality is important for business success
that can be achieved if a process has a good capa-
bility and meets the specified requirements. Good
capability is characterized by a process that can pro-
duce products with minor variations and defects. Ef-
forts are needed through structured steps to obtain
sustainable quality products. At the planning phase,
a quality planning procedure is required. In the im-
plementation phase, quality assurance is required. In
the evaluation phase, it is necessary to control the
quality [2]. A quality control system is needed with
an effective approach to get a good process capabil-
ity. Six Sigma is a proven approach to the world’s
largest companies in controlling the process in mak-
ing quality products.
Six Sigma which has a systematic and structured
method commonly known as DMAIC (Define, Mea-
sure, Analyze, Improve, Control) has been proven to
be effective in identifying, measuring, analyzing, im-
proving and controlling the process [3]. Six Sigma as
an effective management strategy has been applied
in some of the world’s largest companies to improve
the company’s performance [3–5].
Six Sigma is widely used in manufacturing and
services industries for more than one decade in reduc-
ing defects, variations, eliminating error to achieve
product excellence, exceed customer expectations
and gain company’s efficiency performance [1, 4–9].
The Six Sigma method provides substantial evidence
of success in reducing variations and defective prod-
34

Management and Production Engineering Review
ucts in manufacturing processes caused by the 4M 1E
(Man, Material, Method, Machinery, and the Envi-
ronment). While in the Six Sigma application service
sector, it can reduce human and system transactional
errors and also non-value added activities [10–12].
The most fundamental thinking in implementing
Six Sigma is enhancing the process capability. In the
manufacturing industry, increasing the process capa-
bility can be focused more on controlling variation
and defective products [4, 9]. In the service indus-
try, improving the process capability can be focused
more on the improvement of human behavior in the
system by integrating Six Sigma with management
performance. Several service industries had success-
fully implemented Six Sigma as in the banking in-
dustry, education, hospitals, and transport services.
Performance in the service sector can be measured
on non-financial aspects such as employee satisfac-
tion, and ability to provide services that combine in-
ternal with external factors to increase the level of
consumer satisfaction [6], which become a success-
ful indicator of Six Sigma application in the service
industry.
This research is a Literature review that accom-
modates hundred Six Sigma articles from trusted
sources. In this paper, some literary sources come
from the best journal publishers in the world and
some randomly selected from reliable journals, name-
ly those that publish Six Sigma papers by discussing
useful and interesting Six Sigma topics. The research
question is that why the same method (Six Sigma
with the DMAIC phase) is different in implementa-
tion.
The purpose of this research is to find out the
consistency of DMAIC phases and obtaining objec-
tive values in applying Six Sigma in manufacturing
and services industries.
Literature review
Quality is an important requirement for business
success in both manufacturing and service industries.
Also, productivity is a business thought that is a ma-
jor factor in increasing the profit of the company
[1, 13]. Quality and productivity can be created when
the processes have good capabilities and can make
processes and products that meet the requirements
to satisfy customers [14].
Six Sigma is a method that emphasizes the pro-
cess execution based on customer focus, prevention,
commitment, and support from management [15, 16].
Six Sigma with DMAIC phases often use the quality
tools known as seven tools, but the Six Sigma flexi-
bility can also be combined with other tools such as
TQM, ISO 9000, Lean Management and TOC (The-
ory of Constraint), etc. [17, 18].
The Six Sigma method begins by recognizing crit-
ical elements of quality (critical to quality) of a pro-
cess to provide suggestions on improvements related
to defects that arise [19]. Six Sigma has measurable
improvement steps that will result in costs reduc-
tion and increased customer satisfaction to maintain
the sustainability of a company as a whole [1, 8,
20, 21].
The main goal of the Six Sigma is continuous im-
provement through a project. But the Six Sigma ap-
plication is not easy and is not detached with the
obstacles to be encountered; there are three major
obstacles that are often encountered in the imple-
mentation of Six Sigma methods: (1) lack of top
management commitment; (2) the implanted expen-
sive cost; (3) the culture of fear of change. But
it is not an excuse for not implementing the Six-
Sigma method with these obstacles, the high level
of dedication and responsibility of empowering hu-
man resources (HR) is the answer to the barriers
to applying the Six Sigma [8]. The top management
commitment is a fundamental factor for the success
of Six Sigma [15], with an adequate implementa-
tion strategy that focuses on customer and team,
and integrates investment plans in a safe-source re-
source that focuses on team training and work. In
addition, managers must have a reward program
that encourages motivation and acknowledges the
achievement of the human resources involved [22].
So that top management support and commitment
is one of the determinants of successful implementa-
tion of Six Sigma, which can result in the elimina-
tion of two other barriers (cost and culture of fear of
change).
The tools of Six Sigma are most often applied
within a simple performance improvement model
known as DMAIC which is used when a project’s
goal can be accomplished by improving an existing
product, process, or service [23]. The basic principle
of the approach is a structured step with the follow-
ing phases [24]:
1) Define phase, is the first phase of the process of
identification or defining problems, setting prob-
lem issues, and targets to be achieved [24]. This
phase is important and is considered not as easy as
the identification of the inadequate problem will
affect the analysis and the results to be obtained
[4, 25, 26].
2) Measure phase is the measurement of critical qual-
ity factors to follow-up performance measurement
that causes problems found in the define phase
[24].
Volume 11 •Number 4 •December 2020 35

Management and Production Engineering Review
3) Analyze phase is the phase of identification of
the current condition and identification of the
improvement opportunity [24]. By analyzing the
causal factors of the problem, then improvement
actions can be focused.
4) Improve phase is the election activities of the best-
acting alternative measures [24], which decompose
the occurrence from the analysis phase by con-
ducting the test of the action taken.
5) Control phase is a phase for monitoring and stan-
dardizing the solution to assure the cause of the
problem is controlled and also obtain support from
management [15, 16, 24].
Six Sigma is a focused approach to reduce pro-
cess variation and reduce defective products to 3.4
DPMO (Defect per Milion Opportunity). The key
success is an approach with a database that is use-
ful for reducing personal bias. With steps starting
from data collected of defective and critical causes
of defects known to the proposed corrective action.
Furthermore, the proposal improvement was imple-
mented, and the results were then re-collected for
further identifying the outcome of the remedial ac-
tion taken.
Research methodology
The research is a study of Literature review on
the application of Six Sigma methods in the man-
ufacturing and services industries. This study was
conducted by reviewing the various scientific articles
from trusted sources. The methodology of this re-
search is described in the study framework (Fig. 1).
The DMAIC consistency means the Six Sigma
project is working on each stage of DMAIC with tools
at each stage. In this case, consistent is defined when
the Six Sigma project is performed by doing all phas-
es/stages of DMAIC, whereas inconsistent when the
Six Sigma project does not do at least one stage of
the DMAIC phases.
Fig. 1. Study framework.
Result and discussion
Six Sigma with structured stages known as DMA-
IC focuses on improving process capability. Various
research in Six Sigma implementation proved that
Six Sigma (DMAIC) can solve various problems ex-
perienced in manufacturing and services industries
such as: reducing the variation and defective prod-
ucts, decreasing production costs, reducing the er-
ror rate, lowering complain, increase productivity,
increase equipment lifetime, increase customer satis-
faction, improve performance and increase business
profits.
Six Sigma in the manufacturing industry
A number of articles have been obtained about
the application of the Six Sigma method in the man-
ufacturing industrial sector (Table 1). The DMAIC
consistency of Six Sigma articles in manufacturing
industry presented in Fig. 2.
Fig. 2. DMAIC consistency of Six Sigma articles in the manufacturing industry.
36 Volume 11 •Number 4 •December 2020

Management and Production Engineering Review
Table 1
Six Sigma articles in the manufacturing industry.
No Author (Year), Country Object Result
1 Raman & Basavaraj (2019), India [1] capacitor industry Identify the rejection during manufacturing & propose a solution
2 Rahman et al. (2018), Bangladesh [27] garment industry Achieve 2% desired defect rate
3 Rana & Kaushik (2018), India [24] automotive industry Defect reduction from 1550 to 100 PPM, COPQ reduction
4 Garc´ıa-Alcaraz et al. (2018), Mexico [22] various industries Quantify through statistical analysis to measure dependency
among variables
5 Requeijo et al. (2018), Portugal [28] various industries Six Sigma & BSC applied in maintenance assessment as collabo-
rative ecosystem
6 Rajashekharaiah (2016), India [29] various industries Application of Process capability analysis and benchmarked
against Six Sigma
7 Shokri et al. (2016), Germany [10] various industry Focus on human-related behavior factors associated with Lean
Six Sigma
8 Venkateswaran & Padmanaban (2018), India [6] manufacturing industry Focus on reducing defect turn around time (DTAT)
9 Adeyemi (2005), USA [8] various industries Analyze capacity small companies in implementing Six Sigma
10 Nonthaleerak (2008), Thailand [30] various industries Exploring weakness in six sigma implementations & key success
factor
11 Sardeshpan de & Khairnar (2014), India [31] automotive industry Improving the quality of four wheeler platform truck
12 Venkatesh & Sumangala (2018), India [32] various industries Investigating companies that have been benefitted to Six Sigma
implementation
13 Flifel et.al. (2017), Serbia [3] various industries Identification potential Six Sigma project & recommendation of
techniques and tools from the literature
14 Rathilall & Sigh (2018), South Africa [33] automotive industry Investigating the integration of Lean & Six Sigma tools in auto-
motive component manufacturing
15 Kumar & Naidu (2012), India [34] garment industry Absenteeism can be controlled by implementing LSS
16 More & Pawar (2011), India [17] textile industry Implementation of Six Sigma QMS with ISO resulted in compet-
itiveness & performance improvement
17 Ganguly (2012), India [35] aluminum industry Addressing the problem in the aluminum industry by applying
six sigma principles
18 Syafwiratama et al. (2017), Indonesia [36] fiber industry Reducing NC products in polyester short cut production & in-
crease capability from 2.2 to 3.1 sigma
19 Malek & Desai (2015), India [37] casting industry Focus on providing a path for initiating six sigma
20 Naidu (2011), India [38] steel industry Reducing down time machines by obtaining optimum preventive
maintenance frequency
21 Gandhi et al. (2019), India [39] automotive industry Identification of blowholes occurrence & defect reduction from
28,111 to 9,708 PPM
22 Kosieradzka & Ciechańska (2018), Poland [40] industrial automation enter-
prise
Assessing the readiness of the organization (company maturity
level) using Six Sigma implementation
23 Kumar et al. (2017), India [41] process industry (thermal
power plant)
Identification of capacity waste
24 Choi et al. (2011), Korea [42] electronic industry Sig Sigma based management in improving competitiveness
25 John & Areshankar (2018), India [43] automotive industry Focus on reducing the bearing end plate reworks due to variation
in thickness & diameter
26 Chabukswar et al. (2011), India [44] pharmaceutical industry Improvement of process capability from sigma level 1.5 to 4, and
reduce defect to 50%
27 Zasadzień (2017), Poland [45] pipe industry Presents an implementation of Six Sigma in production processes
connected with maintenance
28 Jaffal et al. (2017), Turkey [15] carpet industry Determining key success factor & investigating obstacles in im-
plementing Six Sigma
29 Indrawati & Ridwansyah (2015), Indonesia [46] mining industry Improving the process capability of Iron ores manufacturing
30 Barbosa et al. (2017), Portugal [47] automotive industry Improving performance & product quality rate in bead APEX
production process
31 Morales et al. (2016), Mexico [48] concrete blocks industry Eliminating machine downtime & reduction of scrap from 18 to
2 percent
32 Zhan (2008), USA [49] electrical industry Identification & deduction of variation in the average motor
speed
33 Gajbhiye et al. (2016), India [50] casting industry Reduction in the number of accidents in the manufacturing in-
dustry using Lean Six Sigma
34 Chang& Wang (2007), China [9] various industry Collaborative planning, of Six Sigma with forecasting & replen-
ishment (CPFR) can decrease variances
35 Chang et al. (2012), China [5] chip industry Simulating Six Sigma to improve performance of production plan-
ning procedure
36 Rahman&Talapatra (2015), Bangladesh [51] casting industry Defect reduction in the casting process
37 Srinivasan et al. (2016), USA [7] furnace industry Increasing sigma level from 3.31 to 3.67 in the case of drilling a
hole in a ‘furnace nozzle’ component
38 Khawale et al. (2017), India [14] automotive industry Defect reduction of piston rod & increased productivity
39 Purnama et al. (2019), Indonesia [18] manufacturing industry Improvement by DMAIC in implementation of ISO 14001
40 El Hassani et al. (2017), Morocco [52] sugar industry Decrease Co efficient of Variation (CV) which varies in the range
of [38% -45%] to 22.51%
41 Soković et al. (2006), Croatia [53] automotive industry Reduction in production time, control time, material & internal
scrap
42 Anand at al. (2006), India [13] automotive industry Improvement at deep drawing operations by minimizing punch
load & variation in sidewall thickness
43 Kausik & Khanduja (2008), India [19] thermal power industry Reducing DM water consumption in thermal power plant using
Six Sigma
44 Hassan (2013), Egypt [54] wire industry Improving the quality of manufactured welding wires using Lean
Six Sigma
45 Meteab (2018), Iraq [21] cement industry Identification of Six Sigma impact in improving total quality
management
46 Gerger & Firuzan (2016), Turkey [20] aerospace industry Significant progress has been achieved with the alkaline cleaning
process by employing Six Sigma
47 More et al. (2017), India [55] gear box industry Minimizing the Dent defect using DMAIC control strategy
48 Sławik et al. (2010), Poland [56] automotive industry Six Sigma method can achieve product continuous improvement
& aeration model identification
49 Prashar (2018), India [57] engineering equipment indus-
try
An exploratory study to conceptualize & validate Lean Six Sigma
deployment for manufacturing SMEs
50 Hussain et al. (2014), Pakistan [58] textile industry Sigma level was improved from 2.2 to 3.
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Management and Production Engineering Review
Table 2
Six Sigma articles in the service industry.
No Author (Year), Country Object Result
1 Deniz & C¸ imen (2018), Turkey [59] healthcare industry Identifying the reason behind not using six sigma in healthcare
organizations
2 Narula & Grover (2015), India [60] various industries After dividing the process into three phases and mean service
resolution time was reduced from 10,7 to 7.6 hours
3 Manchosu et al.(2018), Italy [61] healthcare industry Applying Lean Six Sigma in radiotherapy
4 Sahbaz et al. (2014), Turkey [62] healthcare industry Six Sigma was applied to reduce complications during & after
intravitreal injections
5 Zhuo (2019), China [63] banking industry Designing a bank’s Six Sigma service process based on empirical
analysis
6 Omar & Mustafa (2014), Malaysia [64] various industry Six Sigma is a systematic approach to gain financial benefits,
productivity, and customer satisfaction
7 Patton (2005), USA [12] various industry Six Sigma integration with orientation in behaviorally perfor-
mance management can address the whole system
8 Vijay (2013), India [65] educational services Bringing a new innovative student-driven Quality rating system
for the Higher Education Institutions
9 Al Kuwaiti (2016), Saudi Arabia [66] healthcare industry Reducing medication errors from 56.000 PPM to 5000 PPM and
improving sigma level from 3.09 to 4.08
10 Vijay (2014), India [67] healthcare industry 61% cycle time reduction of the patient’s discharge process
11 Al Kuwaiti & Subbarayalu (2017), Saudi Arabia [68] healthcare industry Decreasing pre-intervention falls rate from 6.57 to 1.93 (70.93
percent reduction)
12 Laureani et al. (2012), Ireland [69] healthcare industry Presenting a case study of Lean Six Sigma implementation tech-
niques through a series of students projects
13 Elbireer et al. (2011), UK [70] laboratory service Reduction in data entry errors from 423 to 166 errors/month over
12 months
14 Ekinci et al. (2015), Uganda [71] healthcare industry Evaluating the complications occurred during and after
hemodialysis session
15 Gijo et al. (2012), UK [72] healthcare industry Reducing patient waiting time from 24 to 11 minutes
16 Tetteh (2014), Ghana [73] educational services Identifying attributes of the lecturer to improve student’s prior
knowledge by using Six Sigma
17 Kim (2010), Korea [74] educational services Describing Six Sigma implementation in the university library
18 Taner et al. (2011), Turkey [75] healthcare industry Improving workflow by eliminating failure causes in the medical
imaging department
19 Southard et al. (2011), USA [76] healthcare industry Eliminating NVA of locating supplies/equipment, and the ‘re-
turn’ loop of preventable post operative infections
20 Chow & Downing (2014), USA [77] educational services Improving retention of first-year college students in an academic
institution
21 Cunha & Dominguez (2015), Portuguese [78] car dealer Improving the warranty billing process using Six Sigma
22 Ur Rehman et al. (2012), Pakistan [79] telecom industry Implementation of Six Sigma made saving US$ 0.45 million
23 Nagi & Charmonman (2010), Thailand [4] educational services Focusing on the reduction of variation & defects of learnig
24 Chakraborty &Tan. (2006), Singapore [80] various industry Focus on the application of six-sigma to a wider range of services
which depends on the identification of KPI)
25 De Koning et al. (2008), Netherland [26] financial services Facilitating the process of defining LSS projects in finance
26 Kalra & Kopargaonkar (2016), Canada [81] healthcare industry Provides an opportunity for major improvements in delivering
error-free & timely clinical diagnostic lab services
27 Guti´errez-Guti´errez et al. (2012), Spain [82] educational services Investigating the effect of Six Sigma teamwork & process man-
agement on absorptive capacity
28 Chakraborty, & Tan (2012), Australia [25] various industry Exploring Six Sigma implementation on identifying critical suc-
cess factor, CTQ, tools, techniques & KPIs
29 Nar & Emekli, (2017), Turkey [83] healthcare industry Evaluating the analytical performance of the laboratory by cal-
culating process sigma values
30 Le Mahieu et al. (2017), USA [11] educational services Demonstrating application of Six Sigma in a school-community
partnership in Milwaukee
31 Almasarweh & Rawashdeh (2016), Jordan [16] healthcare industry Analyzing the effect of using the Six Sigma method on the quality
of healthcare services in Prince Hashem hospital
32 Gunawan & Karimah (2017), Indonesia [84] accounting services Exploring the implementation of Six Sigma in improving account-
ing information systems performance
33 Kukreja et al. (2009), Louisiana [85] educational services Improving curriculum using Six Sigma in the accounting section
of the Educational Testing Service (ETS)
34 Zhang et al. (2016), Singapore [86] logistic industry Practical implications – Lean and Six Sigma are applicable for
improving logistics operations.
35 Nayeri & Rostami (2016), Iran [87] bank industry Investigating the effectiveness of Six Sigma through balanced
scorecard aspects
36 Vouzas, et al. (2104), Greece [88] various industries Exploring the critical factors related to Lean Six Sigma applica-
tion
37 Hung et al. (2015), Taiwan [89] healthcare industry Make model integrating VSM & HFMEA into the DMAIC
38 Khaidir et al., (2013), Malaysia [90] healthcare industry Review structural analysis of Six Sigma and organizational p er-
formance
39 Bhale et al. (2017), India [91] hospitality industry Integrating discrete event simulation & Taguchi method along
with Six Sigma
40 Arcidiacono & Pieroni (2018), Italy [92] healthcare industry Applying Lean Six Sigma 4.0 to reduce costs, improving at the
same time the QoE perceived by the patient
41 Guti´errez-Guti´errez et al. (2016), Netherland [93] logistic industry Improving performance in logistic service environment using Lean
Six Sigma
42 Sethi et al. (2018), India [94] healthcare industry Assessing Six Sigma between private & government healthcare
43 Ongy (2018), Philipina [95] educational services Identification of the problem in enrollment processing & develop
improvement measures
44 Rehman & Sharma (2014), India [96] healthcare industry Reducing total holding time by 14000 seconds & improving call
operation process by 21.8%
45 Furterer (2018), USA [97] healthcare industry Improving throughput by reducing the patient’s length of stay by
30% in 3 months
46 Pandey (2016), India [98] bank industry Exploring Six Sigma applicability for training design & delivery
operationally efficient & strategically effective
47 Psychogios et al. (2012), Greece [99] Telecommunication in-
dustry
Exploring the critical success factors that affect Leas Six Sigma
implementation
48 Prasad et al. (2016), India [100] various industries Problem identification & measurement of initial Six Sigma level
49 Dave (2017), India [101] various industries Presenting the potential area where Six Sigma could be exploited
in service functions
50 George et al., (2018), India [102] healthcare industry Increasing Sigma values by utilizing strategies against medication
errors
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Management and Production Engineering Review
Fig. 3. DMAIC consistency of Six Sigma articles in the service industry.
Based on the 50 journal articles of Six Sigma
implementation in manufacturing industries, 72% of
articles consistently implemented complete DMAIC
phases, especially in case study research type. It is
because, in the case study research, DMAIC phas-
es are needed to maintain the stability of variations
and defective products & will not happen again in
the future. In contrast to explanatory research, which
usually has the purpose of scientific development, its
implementation only comparing several different in-
dustries to get new knowledge and do not need im-
provement and controlling step. Thus in explanato-
ry research often only carry out the D-M-A phases
without implementing the I-C phases.
Statistical tools become imperative in implemen-
tation of DMAIC phases, but no rules in each phase
should use a definite tool. In general, the tools used
are customizable with the respective descriptions of
the phases:
1) Define phase: Voice of customers (VOC), Voice of
Business (VOB), brainstorming, historical of da-
ta, collecting of data, SIPOC diagrams, processing
maps, flow diagrams. The tools identify all current
problems to obtain critical to quality (CTQ) that
indicate the problems that will be corrected.
2) Measure phase: capability analysis (sigma level),
Pareto diagram, Gauge R & R measurements, con-
trol charts, Anova, VOP (voice of process). The
tools reflect the measured baseline performance
organization before improvement.
3) Analyze phase: Cause & effect diagram (CED),
Pareto diagrams, VA & NVA analysis, regres-
sion, and correlation analysis, RCA, 5W analysis,
FMEA. The tools can generate the cause of the
problem as in the define phase, then improvements
are planned.
4) Improve phase: DOE (design of experiment), sim-
ulation, Anova, p-chart, SEM (structural equation
modeling), risk matrix, FMEA, 5W 1H, boxplot
diagram. The tools are corrective actions that can
eliminate the problem.
5) Control phase: standardization, documentation,
WI, control plans, control charts, SPC, Compar-
ative data. The tools aim to control processes for
better variation & product defects level.
Six Sigma in the service industry
A number of articles have been obtained about
the Six Sigma aplication in the industrial service sec-
tor (Table 2). The DMAIC consistency of Six Sigma
articles in service industry presented in Fig. 3.
Compared to the Six Sigma implemented in the
manufacturing industry, lesser research of case study
applied problem solving (60%) in the service indus-
try. There is more explanatory research compare to
case study research in the service industry because
many processes in service industries are intangible
and difficult to measure. Six Sigma applied in the ser-
vice industry often emphasized finding the key suc-
cess factors. Several tools that can be utilized in the
service industry are:
1) Define phase: data collection, questionnaire, VOC,
SIPOC.
1. Measure phase: Likert scale, Cronbach’s alpha,
sigma level, data stratification.
2) Analyze phase: regression and correlation, factor
analysis, CED (cause and effect diagram).
3) Improve phase: corrective action, redesign, DOE,
FMEA, risk, and sensitivity analysis.
4) Improve phase: standardization, training, control
plan, SOP.
The objective value
of Six Sigma (DMAIC)
method used in manufacturing
and service industries
From the articles in manufacturing industries, it
can be described that based on the country of study:
Asia 64%, Europe 20%, America 10%, and Africa 6%.
The research objects are classified: automotive 20%,
various 18%, garment/textile 8%, casting 6%, and
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Management and Production Engineering Review
Table 3
The objective value of Six Sigma (DMAIC) in manufacturing and service industries.
Industry
Manufacturing Service
Main problem •Low-performance organization
•Low capability process
•The defect caused by 4M 1E
•Low-performance organization
•Defect caused by wrong human transaction or wrong system
Universal needs •Product quality improvement
•Quality management improvement
•Explanatory science improvement
•Service quality improvement
•Explanatory science improvement
Measure/Analyze •Quantitative data
•Parametric statistics
(t-test, Anova, DOE, etc.)
•Qualitative data
•Non & parametric statistics (corelation & regression, etc.)
Objective found •Reduce defect
•Increase performance organization
•Increase the capability process
•Reduce complain
•Increase performance organization
•Increase customer satisfaction
Control •Documentation
•Standardization
•Monitoring
•Training
•Standardization
•Monitoring
the rest are mixed (power plant, electronic, pharma-
ceutical, electrical, etc.). Besides, the investigation
in service industries based on country of study: Asia
50%, Europe 30%, America 14%, Africa 4% and Aus-
tralia 2%. The research objects are classified: health-
care 42%, educational services 18%, various 16%,
banking 6%, and the rest are mixed (telecom, logis-
tic, etc.).
The objective values of Six Sigma in manufac-
turing & service industries are described in Ta-
ble 3.
Conclusion
Implementation of Six Sigma (DMAIC roadmap
for problem-solving) in the manufacturing and ser-
vices industries from a number of research articles
can be concluded that there is a consistency of all
DMAIC phases, especially in case study research.
But in the explanatory research, not all DMAIC
phases are implemented.
In the manufacturing industry, the problems
(variation or defect) are often caused by a 4M 1E fac-
tor. It has more quantitative data and can be mea-
sured by a statistic measuring device (DPMO/Cp,
Histogram, Pareto diagram, etc.), then analyzed
with parametric statistics (Anova, t-test, R & R mea-
surements, etc.) and improved with FMEA, 5W1H,
DOE. Thus the capability process can be improved,
which is characterized by the decline in defects oc-
currence and increase organizational performance. In
the Control phase that aimed to prevent problems
from occurring later in the future, a better capability
process achieved should be maintained by standard-
ization, documentation, and monitoring using con-
trol chart, SPC, etc.
In the service industry, problems often arise due
to transactional errors caused by human error or
the poor system itself. Therefore, the analysis con-
ducted with qualitative data obtained from data col-
lection through interviews, questionnaires, then uti-
lized nonparametric statistics (regression & correla-
tion). Improvements were performed to make the
correction and action plans (redesigning, FMEA,
etc.), aimed at reducing customer errors or com-
plaints to improve customer satisfaction. In the Con-
trol phase, standardization, training & monitoring
are performed to gain organizational performance to
enhance customer satisfaction.
This study’s limitation is that this paper does not
correlate with the specific tools used in each stage of
DMAIC. The recommendation for further research is
that in applying Six Sigma methods in the industry,
the teams involved in the projects should have an
adequate understanding of the application of tools
for each phase of DMAIC. Therefore the results ob-
tained are purely based on Six Sigma as indicated by
changes in sigma level.
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