Leanness metric evaluation platform in fuzzy context
Abstract
Purpose
The purpose of this study is to provide an efficient index system for evaluating leanness extent of the organizational supply chain. 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 that are adapting this lean concept.
Design/methodology/approach
The present work exhibits an efficient fuzzy-based leanness assessment system using trapezoidal fuzzy numbers set.
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 toward 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 trapezoidal fuzzy numbers has been efficiently explored to facilitate this decision-making; and the appraisement index system has been extended with the capability to search ill-performing areas which require future progress.
Keywords
Acknowledgements
The authors are really grateful for receiving continuous encouragement and wholehearted support provided by Mrs Weaver, Editorial Assistant of the Journal of Modelling in Management. The authors sincerely express our heartiest thanks to the anonymous reviewers for their valuable comments and suggestions to make the paper a good contributor.
Citation
Matawale, C.R., Datta, S. and Mahapatra, S.S. (2015), "Leanness metric evaluation platform in fuzzy context", Journal of Modelling in Management, Vol. 10 No. 2, pp. 238-267. https://doi.org/10.1108/JM2-10-2013-0057
Publisher
:Emerald Group Publishing Limited
Copyright © 2015, Emerald Group Publishing Limited