Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework

Sachin S. Kamble, Angappa Gunasekaran, Harsh Parekh, Venkatesh Mani, Amine Belhadi, Rohit Sharma

Research output: Contribution to journalArticlepeer-review

115 Scopus citations

Abstract

A digital twin is an integration of virtual and physical systems using disruptive technologies. More precisely, it is a method of developing sustainable, intelligent manufacturing systems for attaining robust quality, reducing time, and customized products using real-time information throughout the product life cycle. This paper presents a systematic literature review of 98 research papers on various digital supply chain twin dimensions with sustainable performance objectives. The selected papers were reviewed and classified into three broad categories: components of the digital twin, applications in the manufacturing supply chain, and sustainability. Based on the review and future perspectives from the study, we suggest that advancements in technologies such as IoT, cloud computing, and blockchain have increased the potential of digital twin applications in the supply chain. The results indicate that a digital supply chain twin should include the things and humans from the entire supply chain and not be restricted to the local manufacturing systems. Based on our review findings, we present a sustainable digital twin implementation framework for supply chains. The proposed framework will guide future practitioners and researchers.

Original languageEnglish (US)
Article number121448
JournalTechnological Forecasting and Social Change
Volume176
DOIs
StatePublished - Mar 2022

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Applied Psychology
  • Management of Technology and Innovation

Fingerprint

Dive into the research topics of 'Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework'. Together they form a unique fingerprint.

Cite this