Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry - Kamble, Sachin S.; Gunasekaran, Angappa; Sharma, Rohit (Computers in industry, 2018)
•Potential adoption barriers of Industry 4.0 are identified from the literature.•Industry experts validated the identified barriers and developed contextual relationships between them.•Relationships established among the barriers using ISM and Fuzzy MICMAC analysis.•Driving and dependence power of barriers in Indian manufacturing industry context is developed.•The results reveal the direct and indirect effects of identified barriers in the Industry 4.0 adoption. The aim of this paper is the analysis of potential barriers which would hinder the manufacturing organizations from embracing Industry 4.0. This paper establishes relationships among the barriers using interpretive structural modeling (ISM) and finds out driving and dependence power of barriers, using fuzzy MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´e a´ un Classement) analysis. A group of experts from industry and academia was consulted and ISM methodology was used to develop the contextual relationship among the identified barriers to Industry 4.0 adoption. The results of ISM were used as input to fuzzy MICMAC analysis for determining the driving and dependence power of the Industry 4.0 adoption barriers. The results are helpful in identifying and classifying the significant barriers, revealing the direct and indirect effects of each identified barrier on the Industry 4.0 adoption. The findings will help the practitioners and the policymakers for a detailed understanding of the Industry 4.0 adoption process and the barriers hindering its implementation. They may utilize the framework and the driving-dependence power of the barriers to understanding the inter-relationship between the barriers to building a valid and operative digital manufacturing platform. The study is first of its kind to identify industry 4.0 adoption barriers and develop hierarchical relationships between them using ISM and fuzzy MICMAC methodology in the Indian manufacturing context.