Leanness estimation procedural hierarchy using interval-valued fuzzy sets (IVFS)
Abstract
Purpose
Lean manufacturing is an operational strategy oriented toward achieving the shortest possible cycle time by eliminating waste. It is derived from the Toyota Production System and its key thrust is to increase the value-added work by eliminating waste and reducing incidental work. In today's competitive global marketplace, the concept of lean manufacturing has gained vital consciousness to all manufacturing sectors, their supply chains, and hence a logical measurement index system is indeed required in implementing leanness in practice. Such leanness estimation can help the enterprises to assess their existing leanness level and can compare different industries who are adapting this lean concept. The paper aims to discuss these issues.
Design/methodology/approach
The present work exhibits an efficient fuzzy-based leanness assessment system using generalized interval-valued (IV) trapezoidal fuzzy numbers set. The concept of “degree of similarity” between two IV fuzzy numbers has been explored here to identify ill-performing areas towards lean achievement.
Findings
The methodology described here has been found fruitful while applying for a particular industry, in India, as a case study. Apart from estimating overall lean performance metric, the model presented here can identify ill-performing areas towards lean achievement.
Originality/value
The major contributions of this work have been summarized as follows: development and implementation of an efficient decision-making procedural hierarchy to support leanness extent evaluation. An overall lean performance index evaluation platform has been introduced. Concept of generalized IV trapezoidal fuzzy numbers has been efficiently explored to facilitate this decision-making. The appraisement index system has been extended with the capability to search ill-performing areas which require future progress.
Keywords
Acknowledgements
The authors gratefully acknowledge the support rendered by Prof. A. Gunasekaran, Editor-in-Chief, of the esteemed Benchmarking, An International Journal. Special thanks to the anonymous reviewers for their valuable constructive comments and suggestions to prepare the paper a good contributor.
Citation
Ram Matawale, C., Datta, S. and Sankar Mahapatra, S. (2014), "Leanness estimation procedural hierarchy using interval-valued fuzzy sets (IVFS)", Benchmarking: An International Journal, Vol. 21 No. 2, pp. 150-183. https://doi.org/10.1108/BIJ-03-2012-0020
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited