Sigma Project Selection Research Articles

Six sigma project generation and selection: an action research study

PurposeThe purpose of this paper is to test and develop a method for generation and selection of six sigma projects. This is done by testing the use of the generation and selection method for six sigma projects (GSM_SSP) in a Brazilian manufacturing industry with the participation of managers, aiming to gather the user’s perspective and improvement opportunities for the approach itself.Design/methodology/approachThe work adopts the action research (AR) approach once the researchers were busily involved in the training, implementation and use of the GSM_SSP. The intervention was performed in on a series of 15 workshops, with a group of managers, during six months.FindingsThe application of the eight steps of the GSM_SSP approach assisted the company’s management team to generate nine project candidates and also to select three six sigma projects. This study also finds and discusses barriers and lessons learned used to improve the GSM_SSP.Research limitations/implicationsThis study presents an example of how six sigma project generation and selection has been applied to a manufacturing industry by adapting AR to the process using the eight steps of GSM_SSP, demonstrating how the management team was involved. This study should be replicated in different companies because AR is limited in its generalization.Originality/valueTo the best of the authors’ knowledge, this study represents the first use of AR methodology in six sigma project selection. This study contributes a method that can generate and select six sigma projects. In doing so, the research offers a simple approach that can be used by managers. In addition, the steps of the approach before selection were explored.

Six Sigma Project Prioritization and Selection Using AHP–CODAS Integration: A Case Study in Healthcare Industry

Given the complex nature of Six Sigma project (SSP) prioritization and selection processes, multicriteria decision-making (MCDM) methods may help organizations identify the most effective projects. Considering potential limitations of subjective methods and advantages of MCDM methods, this article proposes a model that integrates analytical hierarchy process (AHP) and combinative distance-based assessment (CODAS) in SSP prioritization and selection process. In the proposed approach, AHP is employed to assign criteria weights, and CODAS is performed to determine priorities of SSPs. CODAS was advanced in term of its threshold function. Differences between Euclidean distances of two alternatives were compared, based on the standard deviation of Euclidean distances of all alternatives to overcome the subjectivity. This is the first study that combines AHP and CODAS methods for SSP selection, and CODAS is used with objective threshold value computation, and developed for the healthcare industry. In this article, ten SSPs were evaluated for four key criteria groups as financial, operational, patient centric, and organizational main criteria groups. In total, 18 subcriteria were considered under these four main criteria groups. This article provides a support for executives who make implementation plans for the potential SSPs.

Efficiency analysis of Lean Six Sigma projects: insights for selection and prioritisation

The main purpose of this article is to identify the main characteristics of Lean Six Sigma projects executed by efficient companies. To do so, this article explores a large empirical database, with 112,421 projects, executed from 2001 to 2018 in 57 strategic business units from a heavy machinery producer, which is recognised as a worldwide reference in the use of Lean Six Sigma methodology. The research was conducted in two stages, first, the data was analysed with a Network Data Envelopment Analysis (DEA) model, which provided an efficiency ranking formed by the strategic business units. In the second stage, a Classification Tree (CHAID) method was used to identify the common characteristics of the projects accomplished by the most efficient ones. The findings show that these strategic business units are characterised by projects executed in departments closely related to senior management, especially Corporate Governance and Business Strategy. In addition, their projects usually focus on people, innovation, or cost reduction and are structured more frequently with the DMAIC cycle. These findings broaden the understanding of the criteria that should be considered in Lean Six Sigma project selection and prioritisation, by providing new insights (not identified in previous studies) to decision-makers and researchers, from projects associated with the efficient performance of Lean Six Sigma, which can be particularly valuable considering the multiple projects conducted in this initiative, that frequently compete for resources.

Sustainable Lean Six Sigma project selection in manufacturing environments using best-worst method

Manufacturing organizations have struggled with selecting right projects for sustainable LSS (SLSS) programs for operational excellence. This study is to propose a method for effective assessment of optimal SLSS projects. The importance weight of project selection criteria and prioritization of available projects are calculated using the novel best-worst-method (BWM) approach. The proposed methodology was authenticated through a real case example. The outcome reveals that out of five SLSS projects, P1 is the optimal project. Project P1 is the most significant production line for deploying the SLSS in case organization. The optimality in project ranking is tested through sensitivity analysis, the outcome noticed minimum sensitivity that claimed robust findings. This study is to be unique as there was very little evidence of prioritizing SLSS projects by utilizing a large set of criteria and applying the BWM approach. Further, BWM is the most suitable and reliable approach for prioritizing the alternatives when a large number of criteria are involved and it provides consistent outcomes with fewer inputs. The applied methodology will help top management to select the right project and opportunities in complex situations. Decision-makers and LSS consultants can also adopt the same approach for effective assessment of optimal SLSS projects for sustainable development.

Six sigma project prioritization and selection methods: a systematic literature review

PurposeGiven the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question: What types of project prioritization and selection methods have been used in Six Sigma research?Design/methodology/approachThe study implemented the systematic literature review (SLR) method to identify and review all relevant previous studies.FindingsThe study revealed that 59 articles focused on the topic used 111 methods, analytic hierarchy process appeared as the most frequently used method with 12 articles (20%) and one-third of the methods used in the current Six Sigma project selection literature contained multi-criteria decision-making methods. In total, 61% of 59 articles were not published in the journals ranked by the ABDC’s list. Only 17% of the articles reviewed in this study were published in journals ranked as B category and 12% of the articles were published in A category journals.Practical implicationsThe findings of this literature review may help Six Sigma practitioners and researchers accurately identify project prioritization and selection methods, considering that qualitative and quantitative scientific methods guarantee to make better decisions than “gut feelings” of the decision makers in this process.Originality/valueAlthough a variety of studies focused on the topic, an SLR is lacking in the area of Six Sigma project prioritization and selection. Therefore, this study was constructed using the SLR method to analyse the topic.

Lean Six Sigma Project Selection in a Manufacturing Environment Using Hybrid Methodology Based on Intuitionistic Fuzzy MADM Approach

Project selection has a critical role in the successful execution of the lean six sigma (LSS) program in any industry. The poor selection of LSS projects leads to limited results and diminishes the credibility of LSS initiatives. For this reason, in this article, we propose a method for the assessment and effective selection of LSS projects. Intuitionistic fuzzy sets based on the weighted average were adopted for aggregating individual suggestions of decision makers. The weights of selection criteria were computed using entropy measures and the available projects are prioritized using the multiattribute decision making approach, i.e., modified TOPSIS and VIKOR. The proposed methodology is validated through a case example of the LSS project selection in a manufacturing organization. The results of the case study reveal that out of eight LSS projects, the assembly section (A8) is the best LSS project. A8 is the ideal LSS project for swift gains and manufacturing sustainability. The robustness and reliability of the obtained results are checked through a sensitivity analysis. The proposed methodology will help manufacturing organizations in the selection of the best opportunities among complex situations, results in sustainable development. The engineering managers and LSS consultants can also adopt the proposed methodology for LSS project selections.

Prioritization of Lean Six Sigma project selection criteria using Best Worst Method

With the increase in competitiveness, demand for better products from customers, and call for higher rate of return, the manufacturing organizations are implementing “Lean Six Sigma (LSS)” methodology to improve process flow, increase customer satisfaction and improve the bottom-line results. LSS is the combination of Lean manufacturing that focuses on streamlining the process flow and Six Sigma that is applied to reduce the defects in the production. In this study, we provide a robust set of criteria for LSS project selection in an Indian automotive parts manufacturing organization. Our objective is to provide weight and prioritize these criteria for successful project selection. The set of criteria includes various dimensions and employs the principles of LSS to select 19 project selection criteria. A novel technique called “Best worst method” is used to determine the weights of the criteria and to rank them accordingly. The findings of this study provide insights on process feasibility being the most important dimension followed by customer development and financial status as are highest priority dimensions. The set of criteria chosen for the study can be employed in other manufacturing sectors for project selection.

Six sigma project prioritization and selection: a multi-criteria decision making approach in healthcare industry

PurposeThe purpose of this study is to develop a methodology in which alternate Six Sigma projects are prioritized and selected using appropriate multi-criteria decision-making (MCDM) methods in healthcare organizations. This study addresses a particular gap in implementing a systematic methodology for Six Sigma project prioritization and selection in the healthcare industry.Design/methodology/approachThis study develops a methodology in which alternate Six Sigma projects are prioritized and selected using a modified Kemeny median indicator rank accordance (KEMIRA-M), an MCDM method based on a case study in healthcare organizations. The case study was hypothetically developed in the healthcare industry and presented to demonstrate the proposed framework’s applicability and validity for future decision-makers who will take place in Six Sigma project selection processes.FindingsThe study reveals that the Six Sigma project prioritized by KEMIRA-M assign the highest ranks to patient satisfaction, revenue enhancement and sigma level benefit criteria, while resource utilization and process cycle time receive the lowest rank.Practical implicationsThe methodology developed in this paper proposes an MCDM-based approach for practitioners to prioritize and select Six Sigma projects in the healthcare industry. The findings regarding patient satisfaction and revenue enhancement mesh with the current trends that dominate and regulate the industry. KEMIRA-M provides flexibility for Six Sigma project selection and uses multiple criteria in two-criteria groups, simultaneously. In this study, a more objective KEMIRA-M method was suggested by implementing two different ranking-based weighting approaches.Originality/valueThis is the first study that implements KEMIRA-M in Six Sigma project prioritization and selection process in the healthcare industry. To overcome previous KEMIRA-M shortcomings, two ranking based weighting approaches were proposed to form a weighting procedure of KEMIRA-M. As the first implementation of the KEMIRA-M weighting procedure, the criteria weighting procedure of the KEMIRA-M method was developed using two different weighting methods based on ranking. The study provides decision-makers with a methodology that considers both benefit and cost type criteria for alternates and gives importance to experts’ rankings related to criteria and the performance values of alternates for criteria.

Six sigma project generation and selection: literature review and feature based method proposition

The benefits of the Six Sigma approach are recognised since the 1990s and Six Sigma project selection is pointed out as being a key success factor in its implementation. Six Sigma project selection approaches have been proposed without exhausting the research. This study contributes in that direction, aiming to propose a method to carry out the generation and selection of Six Sigma projects. The methodological procedure used was systematic review of the literature. Research gap related to Six Sigma project selection were identified. The novelty of this paper is to present a review of literature not only about six sigma project approaches but also about six sigma project selection features. Additionally, this paper proposes an innovative method by the fact that it meets all the eight Six Sigma project selection approach recurring features found in literature. In doing so, this feature based method can assist management teams in charge of leading a Six Sigma initiative.

Six Sigma Application in Healthcare Logistics: A Framework and A Case Study.

Six Sigma is used heavily in various industrial sectors, yet no noticeable applications are seen in healthcare logistics. This paper reveals the special case of healthcare logistics where cost reduction is not the only factor considered in project selection; performance and criticality of each item in the logistics system are of high importance as well. This paper provides a proposed framework to apply Six Sigma in the area of healthcare logistics. It also presents a case study implementing the proposed framework at a Jordanian hospital. In the case study, the paper reveals how the modifications of the define phase to take into consideration the criticality, cost, and performance of items make typical Six Sigma methodology very beneficial for healthcare logistics. In addition, it shows how the Six Sigma project selection can be done to deal effectively with healthcare logistics issues. This paper paves the road for research to elaborate on ways to use Six Sigma in the area of improving healthcare logistics.

Selecting Six Sigma project: a comparative study of DEA and LDA techniques

PurposeNowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? The purpose of this study is to proposing a methodology to to answer this question that: How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks.Design/methodology/approachFirst, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, a new data envelopment analysis (DEA) model is proposed for project selection process. A real example is resolved by the presented model. Finally, the authors use linear discriminate analysis (LDA) to examine the validity of obtained results from the proposed model.FindingsThe results show that the proposed model is a suitable tool for selecting Six Sigma Projects. The findings demonstrate that the selected projects by suggested integrated DEA model are those confirmed by LDA.Originality/valueThe paper, using a real case study, provides a mathematical model to enhance decision quality in Six Sigma project selection. Applying the specific DEA model is remarkable itself, which joined to a pioneering procedure to use LDA to validity evaluation of the results.

Six Sigma project selection using fuzzy multiple attribute decision-making method

In recent year, Six Sigma has been known as a framework for quality improvement. An appropriate Six Sigma project can increase benefits and customer satisfaction and reduce cost of poor quality and unnecessary waste. This paper presents a comprehensive fuzzy framework for combining objective ratings obtained from quantitative data and subjective ratings obtained from qualitative analysis to select adequate Six Sigma projects. The framework systematically constructs the objectives of Six Sigma project selection to support the business goals and strategies. These objectives can be used to develop tailor-made attributes and a consistent evaluation standard. A fuzzy multiple attribute decision-making method (FMADM) is adopted to resolve the ambiguities involved in assessing Six Sigma projects and aggregating the linguistic evaluation descriptions and weights. The proposed framework can facilitate the complex Six Sigma project selection process, echo company requirements, and consolidate efforts to enhance group decision-making process. An actual example demonstrates the feasibility and of effectiveness applying the proposed framework.

Six Sigma project selections: a critical review

PurposeThe 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/approachThe 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 methodsFindingsThe 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/implicationsThe 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 implicationsThis 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/valueThe paper fulfils an identified gap of review of Six Sigma project selection.

Selecting Six Sigma projects: MCDM or DEA?

Purpose – Nowadays, most of the organizations have focused through the world on Six Sigma to reduce the costs, improve the productivity and enhance concerned individuals’ satisfaction, especially customers’ satisfaction. Annually, these organizations define and execute thousands of Six Sigma projects which involve a great deal of investments. But are all of these projects successful and do the organizations benefit from the above advantages? How can we reduce the risk of failure in Six Sigma projects? The first step to reduce the risk of failure in Six Sigma projects is selecting optimal ones which have the most profits and the least expected risks. Design/methodology/approach – In this paper, the effective criteria are recognized and defined in selecting Six Sigma projects. Then, the analytic hierarchy process (AHP) is used to rank the results. Then, a real example is resolved by two important techniques in decision-making process, that is the AHP and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), as well as data envelopment analysis (DEA). The results from the above three methods are compared. Findings – The results of this paper show that by using fewer criteria, the results from AHP and TOPSIS are very similar. Also, the results from these techniques vary from DEA’s ones in many aspects. So regarding the different results and the importance of criteria in selecting the Six Sigma projects, multi-criteria decision-making (MCDM) techniques are more reliable in comparison with DEA, because decision-maker’s point of view is more effective in MCDM techniques. Originality/value – The paper, using a real case study, provides important new tools to enhance decision quality in Six Sigma project selection.

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

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.

A framework for Six Sigma project selection in higher educational institutions, using a weighted scorecard 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 Selection Using Fuzzy TOPSIS Decision Making Approach

Six Sigma is considered as a logical business strategy that attempts to identify and eliminate the defects or failures for improving the quality of product and processes. A decision on project selection in Six Sigma is always very critical; it plays a key role in successful implementation of Six Sigma. Selection of a right Six Sigma project is essentially important for an automotive company because it greatly influences the manufacturing costs. This paper discusses an approach for right Six Sigma project selection at an automotive industry using fuzzy logic based TOPSIS method. The fuzzy TOPSIS is a well recognized tool to undertake the fuzziness of the data involved in choosing the right preferences. In this context, evaluation criteria have been designed for selection of best alternative. The weights of evaluation criteria are calculated by using the MDL (modified digital logic) method and final ranking is calculated through priority index obtained by using fuzzy TOPSIS method. In the selected case study, this approach has rightly helped to identify the right project for implementing Six Sigma for achieving improvement in productivity.

Selecting the Six Sigma Project: A Multi Data Envelopment Analysis Unified Scoring Framework

The importance of the project selection phase in any six sigma initiative cannot be emphasized enough. The successfulness of the six sigma initiative is affected by successful project selection. Recently, Data Envelopment Analysis (DEA) has been proposed as a six sigma project selection tool. However, there exist a number of different DEA formulations which may affect the selection process and the wining project being selected. This work initially applies nine different DEA formulations to several case studies and concludes that different DEA formulations select different wining projects. Also in this work, a Multi-DEA Unified Scoring Framework is proposed to overcome this problem. This framework is applied to several case studies and proved to successfully select the six sigma project with the best performance. The framework is also successful in filtering out some of the projects that have “selective” excellent performance, i.e. projects with excellent performance in some of the DEA formulations and worse performance in others. It is also successful in selecting stable projects; these are projects that perform well in the majority of the DEA formulations, even if it has not been selected as a wining project by any of the DEA formulations.

Applying a Hybrid MCDM Model for Six Sigma Project Selection

Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS) is a type of multiple criteria decision making (MCDM) problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

Literature snapshot on Six Sigma project selection for future research

Six Sigma is regarded as a well-structured methodology for improving the quality of processes and products. It helps achieve the company’s strategic goal through the effective use of project-driven approach. As Six Sigma is a project-driven methodology, it is essential to prioritise projects which provide maximum financial benefits to the organisation. Generating and prioritising the critical Six Sigma projects, however, are real challenges in practice. A detailed literature review on Six Sigma research reveals that project selection is an area of extreme importance for assuring success of Six Sigma implementation, but that has been less researched in the past. This paper provides both academics and practitioners with a useful framework for pursuing rigorous Six Sigma project selection research through snapshot review of published literatures.