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

Abstract

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.