Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

This study proposes a three-layer assessment model to evaluate the performance of a green-manufacturing system (GMS) and identify the key success factors of its real-world implementation. The top layer of the model includes three dimensions – green design, green-manufacturing process and green packaging. The second and third layers include ten strategic subjects and 74 assessment factors, respectively. The weights in each layer are collected via a questionnaire and calculated using the analytical network process (ANP). Based on the ANP, the five key success factors for implementing the GMS in a company are proportion of non-toxic materials, compliance with eco-ordinances, proportion of biodegradable materials, environmental pollution per product and extent of process pollution. The practicality of the proposed model is demonstrated by evaluating three companies that produce similar products and share similar business models. The proposed model provides a valuable reference for real-world implementation of...

Key success factors when implementing a green-manufacturing system

In this contribution, we aim to prioritise the indicators to enhance the organisational supply chain’s (SC) effectiveness from an industrial perspective It will help industries to develop strategi

Prioritising indicators in improving supply chain performance using fuzzy AHP: insights from the case example of four Indian manufacturing companies

Many organisations have implemented Six Sigma, but successful Six Sigma implementation has not been fully investigated. The purpose of this study is to explore the process of implementing Six Sigma in a manufacturing plant using qualitative case study methodology. Data were collected through in-depth interviews and analysed using grounded theory to identify the main factors that emerged from the interview data and the relationships between them. Consistent with previous studies, the findings emphasise the role of executive commitment, Six Sigma Champions, and training in successful implementation of Six Sigma projects. Furthermore, the study underlines the role of effective project selection and the coexistence of other management initiatives (e.g. lean manufacturing and continuous improvement) on successful implementations of Six Sigma projects. Our findings also suggest that Six Sigma implementation leads to higher levels of customer focus. The study contributes to the existing body of knowledge in effe...

Six Sigma implementation: a qualitative case study using grounded theory

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 stu...

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

Six Sigma is viewed as a systematic, scientific, statistical and smarter approach for management of innovation and focuses on establishing world class business performance. The main identifiers and supreme features of Six Sigma amongst other improvement techniques are: its rich ground which covers many customer oriented and problem solving techniques and its scientific methodology which is based on statistics. One of the most important factors of achieving success is selection of the right Six Sigma projects. This article presents a case study in which both Six Sigma project is selected and Six Sigma methodology is adopted to reduce the energy cost by the optimisation of material transferring heat loss in an automotive supplier industry. To cope with ambiguity and vagueness in the Six Sigma project selection problem, the Fuzzy Analytic Hierarchy Process has been used. This article also describes how various tools and techniques are employed in the different phases within the Six Sigma methodology and how ...

Project selection through fuzzy analytic hierarchy process and a case study on Six Sigma implementation in an automotive industry

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Project selection through fuzzy analytic hierarchy process and a case study on Six Sigma implementation in an automotive industry