Issue: 2027/Vol.37/No.1, Pages 1
A DECISION SUPPORT MODEL TO ENHANCE RECONFIGURABLE MANUFACTURING SYSTEM PERFORMANCE THROUGH INTEGRATION OF INDUSTRY 4.0 AND CIRCULAR ECONOMY PRACTICES
Pansare Rajesh
, Nagare Madhukar , Yadav Gunjan
This is not yet the definitive version of the paper. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article.
Cite as: P. Rajesh, N. Madhukar, Y. Gunjan. A decision support model to enhance reconfigurable manufacturing system performance through integration of Industry 4.0 and circular economy practices. Operations Research and Decisions 2027: 37(1). DOI 10.37190/ord/236166
Abstract
The COVID-19 pandemic, volatile market conditions, shorter lifecycles, and cost-effective goods confront the reconfigurable manufacturing system (RMS). The RMS needs Industry 4.0 and circular economy technologies to boost performance. However, present literature does not integrate these technology and methods. This paper proposes a framework for adopting these technologies and practices. The SWARA method determines relative weights of specified practices, Pythagorean fuzzy COCOSO ranks performance indicators based on expert opinion, along with sensitivity analysis. The important performance metrics in key criteria practices are production lead time, advanced technology usage, and machine utilization rate, according to the report. Waste reduction and production costs are also important to experts. Managers can use the framework to increase RMS performance and handle COVID-19. It enables practitioners use sophisticated technology and CE practices and evaluate their success using metrics.
Keywords: Reconfigurable manufacturing system, SWARA, COCOSO, performance evaluation, Industry 4.0, Circular economy
Received: 20 February 2026 Accepted: 8 September 2026
Published online: 8 September 2026