An Intelligent Multi-objective Decision Support Model for Sustainable Remanufacturing

Remanufacturing offers small- and medium-sized enterprises (SMEs) viable pathways towards transitioning to a circular economy; however, intelligent decision-making systems are needed to accelerate its adoption. Balancing the economic, environmental, and social dimensions of sustainability requires the use of analytical tools that can handle multi-dimensional complexity. This study presents a multi-objective optimization model where remanufacturing tasks are allocated to machines in a factory on the basis of minimizing costs, emissions, and noise exposure. Tri-objective optimization has been carried out using the quadrant shrinking method, and Pareto optimal solutions are translated to an implementation framework that can equip SMEs with an intelligent tool for circular economy adoption. In addition to this, we propose an implementation framework for circular economy in manufacturing based on the DMAIC (define, measure, analyze, improve, and control) approach.