Search results

1 – 1 of 1
Article
Publication date: 13 September 2022

Abhishek Kashyap, Amarendra Kumar Yadav, Omkar Nandan Vatsa, Trivedh Naidu Chandaka and Om Ji Shukla

The purpose of this paper is to develop an interpretive structural modeling (ISM) model to investigate the critical success factors (CSF) and the extent of CSF's influence in the…

Abstract

Purpose

The purpose of this paper is to develop an interpretive structural modeling (ISM) model to investigate the critical success factors (CSF) and the extent of CSF's influence in the implementation of lean industry 4.0 in manufacturing supply chain.

Design/methodology/approach

The study has been carried out with the help of the latest literature followed by brainstorming sessions with experts. The experts were the managers from the industries, assistant professors, and research scholars from academia working in this domain. Finally, a structured model is formed using ISM methodology for the analysis of the CSFs followed by matrice d'impacts croisés multiplication appliquée á un classment (MIAMAC) Analysis for the validation of the model.

Findings

The study identifies robotics, virtual and augmented reality and cloud computing as the main CSFs which are responsible to drive all the identified CSFs. However the CSF professional training and development (PTD) has been identified as the weakest driver but having the highest dependent power.

Research limitations/implications

The study has included nine CSFs and the contextual relationships between the CSFs are based on the knowledge and experience of the experts, which may be biased. Moreover, the paper has covered the ISM approach, and the same thing can be validated using the fuzzy-ISM and other multi-criteria decision-making (MCDM) techniques.

Originality/value

This investigation of the CSFs in the lean industry 4.0 is original and the identified CSFs are the result of the literature reviews and an extensive discussion from the experts. The paper uses the complete experience of the respective experts to make this work more effective and original.

Details

Management of Environmental Quality: An International Journal, vol. 34 no. 4
Type: Research Article
ISSN: 1477-7835

Keywords

1 – 1 of 1