scholarly journals Prioritization of Six-Sigma project selection

2016 ◽  
Vol 23 (7) ◽  
pp. 1983-2003 ◽  
Author(s):  
Dotun Adebanjo ◽  
Premaratne Samaranayake ◽  
Fereshteh Mafakheri ◽  
Tritos Laosirihongthong
Keyword(s):  
Six Sigma ◽  
Performance Metrics ◽  
Resource Constraints ◽  
Relative Weight ◽  
Project Selection ◽  
Improvement Project ◽  
Content Type ◽  
Company Directors ◽  
National Organizations ◽  
Research Challenge

Purpose With increasing choice from a range of programs, improvement project selection within broader supply chain context and resource constraints has become a major research challenge. The purpose of this paper is to investigate the different criteria for selecting Six-Sigma (SS) projects based on previous studies. The study is supported by two grounded theories: resource-based view and institutional norms. The criteria include: first, business drivers for improvement and the common performance metrics deployed; second, the organization’s stakeholders needs; and third, process owner’s needs. Design/methodology/approach To determine the relative importance of influencing factors, opinions were collected from 30 experienced practitioners including SS champions/master black-belts, company directors, consultants, and process owners through a series of interviews in small, medium, and large organizations including multi-national organizations. The evaluation of criteria is based on analytical hierarchy process. Findings The results show that impact on customer, financial impacts, and impact on operational goals are the most significant factors in selecting SS improvement project. Originality/value This study is a first attempt to determine the relative weight among SS project selection criteria, which help the practitioner to allocate their limited resources in implementing SS project.

A framework for Six Sigma project selection in higher educational institutions, using a weighted scorecard approach

2015 ◽  
Vol 23 (1) ◽  
pp. 30-46 ◽  
Author(s):  
Monica C. Holmes ◽  
Lawrence O. Jenicke ◽  
Jessica L. Hempel
Keyword(s):  
Six Sigma ◽  
Selection Process ◽  
Educational Institution ◽  
Project Selection ◽  
Project Leader ◽  
Content Type ◽  
Help Desk ◽  
Use Of Time ◽  
Higher Educational ◽  
Six Sigma Approach

Purpose – This paper discusses the importance of the Six Sigma selection process, describes a Six Sigma project in a higher educational institution and presents a weighted scorecard approach for project selection. Design/methodology/approach – A case study of the Six Sigma approach being used to improve student support at a university computer help desk was used. An error related to the timeliness of service was defined and improved over the course of the project. Findings – The Six Sigma approach was useful for improving timely service, but a methodology for selecting the project was needed by the project leader. Using such a methodology would have ensured higher probability of project success. Practical implications – This framework provides directions for selecting a Six Sigma project in a higher educational setting. The weighted scorecard method is presented and may be used for selecting a project which would likely be the most efficient use of time and resources. Originality/value – While project selection methodologies have been published with regard to Six Sigma projects in business, this paper fills the need for selection criteria as they relate to higher educational settings.

Six Sigma project selections: a critical review

2017 ◽  
Vol 8 (2) ◽  
pp. 244-258 ◽  
Author(s):  
Ramakrushna Padhy
Keyword(s):  
Six Sigma ◽  
Project Selection ◽  
Future Research ◽  
Research Approach ◽  
Successful Implementation ◽  
Content Type ◽  
Research Opportunities ◽  
Process Framework ◽  
Framework Approach ◽  
Tools And Methods

Purpose The paper aims to review the literature on Six Sigma projects through a broad framework of Six Sigma project selection process. It proposes a process framework approach of six sigma project selection and enumerates various recent tools and methods required for each stage. The review aims to expand the domain of Six Sigma project selection by identifying the importance of project portfolio approach. Design/methodology/approach The study used a process framework approach and systematic literature review to identify and classify various literature pertaining six sigma projects and its associated tools and methods Findings The paper provides broad insights about the opportunity and direction to future research in the area of Six Sigma project. Emerging research opportunities exist in the area of Six Sigma project risk management and selecting portfolio of projects. Research limitations/implications The study has its own limitations because of its chosen research approach. The process framework developed for classification of literature is based on expert opinion. Further research can be carried out to validate it. Practical implications This study will benefit new researchers entering the field of Six Sigma to identify new research opportunities and issues for their research interest. Second, industry practitioners and consultants working in the area of Six Sigma may work towards more successful implementation of Six Sigma. Originality/value The paper fulfils an identified gap of review of Six Sigma project selection.

Top ten reasons for process improvement project failures

2019 ◽  
Vol 10 (1) ◽  
pp. 367-374 ◽  
Author(s):  
Jiju Antony ◽  
Sandeep Gupta
Keyword(s):  
Process Improvement ◽  
Six Sigma ◽  
Resistance To Change ◽  
Risk Mitigation ◽  
Recognition System ◽  
Lean Six Sigma ◽  
Mitigation Strategies ◽  
Monitoring And Control ◽  
Improvement Project ◽  
Content Type

Purpose The purpose of this paper is to provide the top ten reasons of process improvement projects termination or failure to Lean and Six Sigma professionals and researchers. Design/methodology/approach The top ten reasons of process improvement projects termination or failure are based on literature, interaction of authors with Lean Six Sigma Master Black Belts, consultants, practitioners and trainers on various topics of Lean, Six Sigma, general quality management and continuous improvement along several years’ experience of the authors. Findings The top ten reasons in our opinion include lack of commitment and support from top management; poor communication practices; incompetent team; inadequate training and learning; faulty selection of process improvement methodology and its associated tools/techniques; inappropriate rewards and recognition system/culture; scope creepiness; sub-optimal team size and composition; inconsistent monitoring and control; and resistance to change. Research limitations/implications The top ten reasons mentioned in this study are based on only literature and authors’ opinion. The authors of this paper have been pursuing a global study to critically evaluate the reasons behind process improvement projects failure based on a case-study approach. Originality/value The chief operations officers and senior executives of various businesses can use these top ten reasons to develop project failure risk mitigation strategies and save significant cash-savings associated with such project terminations or failures in some other cases.

An empirical analysis on Six Sigma implementation in service organisations

2013 ◽  
Vol 4 (2) ◽  
pp. 141-170 ◽  
Author(s):  
Ayon Chakraborty ◽  
Tan Kay Chuan
Keyword(s):  
Six Sigma ◽  
Large Scale ◽  
Success Factors ◽  
Performance Metrics ◽  
Academic Research ◽  
Service Industries ◽  
Service Organizations ◽  
Small Scale ◽  
Widespread Application ◽  
Content Type

PurposeSince its introduction by Motorola in the 1980s, Six Sigma and its philosophy have found widespread application in many manufacturing and service industries. It is felt that there is a need to take stock of the spread of Six Sigma implementation in service organisations. The purpose of this paper is to investigate five main themes which have emerged from literature and to draw on those themes to reflect on wider applicability of Six Sigma in services.Design/methodology/approachThe study involves two exploratory questionnaire surveys. The small‐scale survey is conducted in service organizations in Singapore. The large‐scale survey was web‐based and involved service organisations throughout the world. The objective is to explore and understand the issues highlighted by the service organisations during Six Sigma implementation.FindingsThe findings confirm the inclusion of critical success factors, critical‐to‐quality characteristics, and set of tools and techniques as observed from the literature. In the case of key performance indicators (KPIs), there are different interpretations about them in the literature and also by industry practitioners. Some literature explains KPIs as performance metrics whereas some feel they are key process input or output variables, which is similar to interpretations by practitioners of Six Sigma. The responses of “not relevant” and “unknown to us” as reasons for not implementing Six Sigma show the need for understanding specific requirements of service organizations.Research limitations/implicationsThe limited responses from the authors' surveys restrict the possibility of generalising the findings. Therefore, more extensive survey is required. The three‐phase approach with mixed method used in the overall study has been shown to be useful.Originality/valueAlthough much theoretical description is available about Six Sigma, there has been limited rigorous academic research on it. This gap is far more pronounced about Six Sigma implementation in service organizations, where the theory is not yet mature. Identifying this need, the paper contributes, by empirical research through surveys, to understand the issues involving Six Sigma implementation in service organizations.

Continuous improvement project within Kaizen: critical success factors in hospitals

2018 ◽  
Vol 30 (4) ◽  
pp. 335-355 ◽  
Author(s):  
Fernando Gonzalez-Aleu ◽  
Eileen M. Van Aken ◽  
Jennifer Cross ◽  
Wiljeana J. Glover
Keyword(s):  
Continuous Improvement ◽  
Six Sigma ◽  
Critical Success Factors ◽  
Success Factors ◽  
Future Research ◽  
Improvement Project ◽  
Content Type ◽  
Critical Success ◽  
The Impact ◽  
Level Of Importance

Purpose Evidence suggests that hospitals are having problems achieving continuous improvement project (CIP) goals or sustaining their results. Therefore, the purpose of this paper is to identify those critical success factors (CSFs) most strongly related to CIP success in hospitals (Lean-Kaizen project, Lean Six Sigma project, Six Sigma projects, and Quality Improvement projects). Design/methodology/approach A retrospective survey was applied to any CIP leaders/facilitators from hospitals that conducted at least one CIP during the last two years. Findings Three main findings were obtained from the 116 valid responses. First, the level of importance of 47 out of 53 CSFs to achieve CIPs success in hospitals was assessed as very important or higher (4 or higher on a six-point scale). Second, there are important differences between the CSFs to achieve CIP success in hospitals in this research and previous investigations. Third, the type of CIP affects the level of importance of 16 out of 53 CSFs to achieve CIP success in hospitals. Originality/value Practitioners involved with CIPs activities in hospitals could use the knowledge extracted from this investigation to improve the impact of their CIPs. Future research should continue in two lines: test if the 53 CSFs for CIPs measure a unique factor and identify the main relationships or paths between CSFs for CIPs and CIP outcomes.

Model of the port performance metrics in ports by integration six sigma and system dynamics

2018 ◽  
Vol 35 (1) ◽  
pp. 82-108 ◽  
Author(s):  
Asep Ridwan ◽  
Bernd Noche
Keyword(s):  
Complex System ◽  
System Dynamics ◽  
Six Sigma ◽  
Performance Metrics ◽  
Poor Quality ◽  
Content Type ◽  
Cargo Handling ◽  
Entire Flow ◽  
The Cost ◽  
Metrics Model

Purpose The purpose of this paper is to design a model of the port performance metrics for improving the quality in ports by integration of six sigma and system dynamics (SD) approach. Design/methodology/approach The port performance is measured by the sigma value (SV), the process capability indices (PCIs), and the cost of poor quality (COPQ) as the performance metrics. A port is a complex system that requires SD as an appropriate tool to simulate the model dynamically. The performance metrics focus on measuring the port performance in the entire flow of material in the cargo handling process. Findings With this model, the changing of the SV, the PCIs, and the COPQ can be identified and analyzed the results to improve the performance in ports. These metrics are utilized to eliminate “waste” in the cargo handling process at ports. This waste consists of lost and damaged cargo, equipment and transporter breakdown, and equipment and transporter delay time. The port performance metrics model can assess the causal relationships in ports as a complex system. Originality/value Studies on integration between the six sigma model and SD in ports are few and relatively limited. The port’s performance can be measured directly using the SV, the PCIs, and the COPQ in the simulation. The port performance metrics model will give the decision makers to make some scenarios to contribute for the optimization of performance in ports.

Six Sigma improvement project in a concrete block plant

2016 ◽  
Vol 16 (4) ◽  
pp. 526-544 ◽  
Author(s):  
Salvador Noriega Morales ◽  
Adán Valles Ch. ◽  
Vianey Torres-Argüelles ◽  
Erwin Martínez G. ◽  
Andrés Hernández G.
Keyword(s):  
Customer Service ◽  
Six Sigma ◽  
Control Process ◽  
Concrete Block ◽  
Service Level ◽  
Improvement Project ◽  
Content Type ◽  
Customer Service Level ◽  
Concrete Blocks ◽  
Six Sigma Methodology

Purpose This paper aims to describe the application of several Six Sigma tools to explain the improvement changes needed in a company that manufactures concrete blocks. The paper explains the methodology and the tools of the Six Sigma system, their use in the project, the application of the DMAIC (Define, Measure, Analyse, Improve and Control) process for the identification and definition of the problems, the related performance variables and the results obtained. Design/methodology/approach The paper reports the research made to improve the production of concrete blocks, specifically, the application of the DMAIC process, which is part of the Six Sigma methodologies; DMAIC stands for Definition of the problem, Measurement of the performance, Analysis using specific statistical methods and tools, Improvement the factors that cause the problem and Control the processes to ensure that the problem will not occur again. Each of those steps is explained in detail in the paper, which also presents the application of other improvement techniques. Findings The results show the adaptability and relevance of Six Sigma for the improvement of production operations. It is clearly demonstrated that it leads to benefits such as the elimination of machine downtime, reduction of scrap from 18 to 2 per cent and the improvements made in plant layout and production facilities to increase the productivity. Research limitations/implications In improvement projects, the differential between the initial and final conditions varies, depending on the magnitude of the problems or potential opportunities. Although this paper describes only the application of Six Sigma, the methodology has a wide potential application in most manufacturing industries. Practical implications With the Six Sigma and DMAIC tools’ application and the improvement process, the agility obtained is driving a more mechanized perspective of production operations. The customer service level was increased, through fast deliveries of complete orders. This project shows that the application of the Six Sigma methodology is feasible and produces attractive financial and operational results in this segment of the construction industry. Originality/value The companies dedicated to the production of concrete blocks commonly reproduce the systems and standards of the industry, which are commonly designed around civil engineering and technical issues. Thus, the application of improvement tools is exceptional in manufacturing environments. Although this paper is just one application of the methodology, it explains in detail the DMAIC use for companies that are committed to the development of new competencies to increase their competitiveness.

Six Sigma quality evaluation of life test data based on Weibull distribution

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Niveditha A ◽  
Ravichandran Joghee
Keyword(s):  
Weibull Distribution ◽  
Test Data ◽  
Six Sigma ◽  
Performance Metrics ◽  
Normal Process ◽  
Life Test ◽  
Content Type ◽  
Life Tests ◽  
Two Parameter ◽  
Theoretical Procedure

PurposeWhile Six Sigma metrics have been studied by researchers in detail for normal distribution-based data, in this paper, we have attempted to study the Six Sigma metrics for two-parameter Weibull distribution that is useful in many life test data analyses.Design/methodology/approachIn the theory of Six Sigma, most of the processes are assumed normal and Six Sigma metrics are determined for such a process of interest. In reliability studies non-normal distributions are more appropriate for life tests. In this paper, a theoretical procedure is developed for determining Six Sigma metrics when the underlying process follows two-parameter Weibull distribution. Numerical evaluations are also considered to study the proposed method.FindingsIn this paper, by matching the probabilities under different normal process-based sigma quality levels (SQLs), we first determined the Six Sigma specification limits (Lower and Upper Six Sigma Limits- LSSL and USSL) for the two-parameter Weibull distribution by setting different values for the shape parameter and the scaling parameter. Then, the lower SQL (LSQL) and upper SQL (USQL) values are obtained for the Weibull distribution with centered and shifted cases. We presented numerical results for Six Sigma metrics of Weibull distribution with different parameter settings. We also simulated a set of 1,000 values from this Weibull distribution for both centered and shifted cases to evaluate the Six Sigma performance metrics. It is found that the SQLs under two-parameter Weibull distribution are slightly lesser than those when the process is assumed normal.Originality/valueThe theoretical approach proposed for determining Six Sigma metrics for Weibull distribution is new to the Six Sigma Quality practitioners who commonly deal with normal process or normal approximation to non-normal processes. The procedure developed here is, in fact, used to first determine LSSL and USSL followed by which LSQL and USQL are obtained. This in turn has helped to compute the Six Sigma metrics such as defects per million opportunities (DPMOs) and the parts that are extremely good per million opportunities (EGPMOs) under two-parameter Weibull distribution for lower-the-better (LTB) and higher-the-better (HTB) quality characteristics. We believe that this approach is quite new to the practitioners, and it is not only useful to the practitioners but will also serve to motivate the researchers to do more work in this field of research.

scholarly journals A study into the reasons for process improvement project failures: results from a pilot survey

2019 ◽  
Vol 36 (10) ◽  
pp. 1699-1720 ◽  
Author(s):  
Jiju Antony ◽  
Fabiane Letícia Lizarelli ◽  
Marcelo Machado Fernandes ◽  
Mary Dempsey ◽  
Attracta Brennan ◽  
...  
Keyword(s):  
Process Improvement ◽  
Six Sigma ◽  
Lean Six Sigma ◽  
Successful Implementation ◽  
Manufacturing Companies ◽  
Improvement Project ◽  
Content Type ◽  
Pilot Survey ◽  
Project Failures ◽  
The Impact

Purpose Process improvement initiatives, such as Lean, Six Sigma and Lean Six Sigma, typically have common characteristics that are carried through projects. Whilst a project’s performance is an important determinant of the successful implementation of continuous improvement (CI) initiatives, its failure can undermine the impact of any CI initiative on business performance. As a result, an understanding of the reasons of process improvement project failures is crucial. The purpose of this paper is to present the results of a pilot survey highlighting the most common reasons for process improvement project failures. Design/methodology/approach This paper presents a pilot survey of 42 Brazilian manufacturing specialists who have been involved in process improvement projects. The participants of this survey were Six Sigma Master Black Belts, Black Belts, Green Belts and Six Sigma champions from manufacturing companies in Brazil. The survey questionnaire was piloted with five experts in the field in order to ensure that the questions were valid and technically sound. Findings The execution of Six Sigma projects in organizations results in a moderate rate of project failures. These failures can cost organizations several millions of dollars especially within the context of larger organizations. The main reasons for project failure, as cited by the specialists include: resistance to change, lack of commitment and support from top management and incompetent teams. Research limitations/implications The authors report the findings from a pilot survey having a limited sample size. Moreover, the data have been collected from one country and primarily from large manufacturing companies. Originality/value To the best of the authors’ knowledge, this is the first empirical study looking into the reasons for process improvement project failures. The authors argue that if the top reasons for such failures are understood, a framework can be developed in the future that can mitigate the chance of project failures during project execution. This could potentially lead to significant savings to the bottom-line of many organizations.

Lean Six Sigma project selection using hybrid approach based on fuzzy DEMATEL–ANP–TOPSIS

2015 ◽  
Vol 6 (4) ◽  
pp. 313-338 ◽  
Author(s):  
S Vinodh ◽  
Vikas Swarnakar
Keyword(s):  
Decision Making ◽  
Six Sigma ◽  
Hybrid Approach ◽  
Project Selection ◽  
Lean Six Sigma ◽  
Automotive Component ◽  
Content Type ◽  
Industrial Sectors ◽  
Component Manufacturing ◽  
Manufacturing Organization

Purpose – The purpose of this paper is to select the optimal Lean Six Sigma (LSS) project using hybrid fuzzy-based Multi-Criteria Decision-Making (MCDM) approach for an automotive component manufacturing organization. Design/methodology/approach – The LSS project selection has been formulated as the MCDM problem. Hybrid MCDM method based on Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to select the optimal LSS project. The methodology enabled the practitioners to systematically prioritize LSS projects. Findings – The finding of this study is that, out of five LSS projects, project P3 is the best LSS project. P3 is the optimal LSS project with reduced failure risk, and efforts are being taken to implement the selected project. Research limitations/implications – The problem formulation and methodology has been tested for a single study. In future, more number of studies could be conducted using the hybrid approach. This method is presently applied for an automotive component manufacturing organization; in future, the approach could be applied in different industrial sectors for improving its effectiveness. Practical implications – The case study has been conducted in a real-time industrial problem. The practitioners expressed the usefulness of the methodology for prioritizing LSS projects Hence, the inferences derived are found to possess practical relevance. Originality/value – The original contribution of the study is the selection of optimal LSS project using hybrid MCDM technique.

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