Open AccessModeling and Analysis of Lean Manufacturing Strategies Using ISM-Fuzzy MICMAC Approach
Author(s) -
Mohit Tyagi,
Dilbagh Panchal,
Deepak Kumar,
R. S. Walia
Publication year - 2021
Publication title -
operational research in engineering sciences: theory and applications/operational research in engineering sciences: theory and applications.
Language(s) - English
Resource type - Journals
eISSN - 2620-1747
pISSN - 2620-1607
DOI - 10.31181/oresta2040123t
Subject(s) - lean manufacturing , identification (biology) , fuzzy logic , computer science , artificial intelligence , engineering , manufacturing engineering , botany , biology
The current research work deals with an identification of different lean strategies and extraction to relevant strategies after discussion with experts and gives the answer of a question “how lean manufacturing strategies can help the organization to enhance the efficiency of the organization with great effectiveness?” In this research work, thirty-six lean strategies have been identified and out of which thirteen lean strategies were filtered in respect of highly importance value by factor analysis using software SPSS 21. Further, to identify and analyze the inter-relationship among filtered strategies, an Interpretive Structural Modeling (ISM) with Fuzzy Matriced’ Impacts Croise´s Multiplication Applique´e a UN Classement (MICMAC) approach has been used. Fuzzy MICMAC help to understand the dependence and driver’s power of the lean strategies. The mutual importance of extracted strategies has been discussed through developing the ISM model and the individual assessment of each strategy with each of the other strategies has been derived using the Fuzzy MICMAC approach.