Unlocking factors of digital twins for smart manufacturing: a case of emerging economy

Bhaskar B. Gardas, Angappa Gunasekaran, Vaibhav S. Narwane

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The Industry 4.0/smart manufacturing paradigm has significantly changed the activities and processes of organizations. Emergent smart manufacturing technology called a ‘Digital Twin’ (DT) aids organizations in enhancing overall performance by creating a virtual prototype of a real system. However, DT technology adoption in emerging economies is in the nascent stage. This research aims to identify the determinants affecting the adoption of DT technology in Indian manufacturing firms. Based on an extensive literature survey and experts’ opinions, 14 determinants were identified, and these determinants were analyzed using a hybrid multi-attribute decision-making approach to understand the contextual relationship and to identify the cause–effect relationship amongst them. Based on these results, the most critical determinants were explored, namely ‘Real-time system operations and tracking’, ‘Integration, the convergence of systems, processes & resources and enterprise collaboration’, ‘Information and Data management within or between the systems’. The manufacturing organizations of emerging economies need to consider these determinants for the effective adoption of DT technology, and policymakers can use the findings of this study to develop appropriate strategies.

Original languageEnglish (US)
JournalInternational Journal of Computer Integrated Manufacturing
DOIs
StateAccepted/In press - 2023

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this