Application of multi-grade fuzzy and ANFIS approaches for performance analysis of Lean Six Sigma system with sustainable considerations. (24th June 2019)

• Record Type: Journal Article
• Authors: Ruben, R. Ben; Vinodh, S.; Asokan, P.
• Is Part Of: International journal of services and operations management. Volume 33:Number 2(2019)
• Page Start: 239
• Page End: 261
• Publication Date: 2019-06-24
• Subjects: Lean Six Sigma -- LSS -- sustainable manufacturing -- performance evaluation -- multi grade fuzzy -- MGF -- adaptive neuro fuzzy inference system -- ANFIS; Production management -- Periodicals; 658.5005
• Languages: English
• ISSNs: 1744-2370

Abstract

Lean Six Sigma (LSS) is a manufacturing strategy that aims at improving the firm's competitiveness and operational performance through waste reduction and process variation. Sustainable manufacturing aims at creating manufactured products with minimal negative environmental impacts. In order to facilitate zero defects and improve their sustainable performance, manufacturing firms have started to adopt both LSS and sustainable manufacturing strategies to attain integrated benefits. This article reports a research carried out to analyse the performance of LSS system integrated with sustainability considerations using multi grade fuzzy (MGF) and adaptive neuro fuzzy inference system (ANFIS) approaches. During this research, a performance assessment model was designed. The score based on MGF approach is found to be 6.74 and that of ANFIS approach is 6.51. Based on computation, the case organisation was found to possess 'strong LSS performance with sustainability considerations'. The study could facilitate improvement in LSS performance incorporated with sustainability aspects.