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.
All Science Journal Classification (ASJC) codes
- Computer Science(all)