An Integrated Multi-Period Layout Planning and Scheduling Model for Sustainable Reconfigurable Manufacturing Systems

In a dynamic production environment, not only the customer’s needs change with time, but the economic aspects of that environment, such as energy pricing, also change. Reconfigurable Manufacturing Systems (RMSs) are designed to respond to such changes by reconfiguring system components efficiently. This paper presents a novel mathematical model to maximize energy sustainability of RMS. The novelty aspect of the model is the consideration of energy sustainability concurrently with system configuration and scheduling decisions in each period of the planning horizon. The objective of this mixed integer linear model is to minimize the total cost of energy consumption, system reconfiguration, and part transportation between machines, depending on fluctuations of energy pricing and demand during different periods. Several case studies are solved by GAMS Software to illustrate the performance of the presented model and analyze its sensitivity to the volatility of energy pricing and demand to show their effect on system changeability. An efficient genetic algorithm (GA) has been developed to solve the model in larger scale due to its NP-hardness and compared to GAMS for validation. Results show that the presented GA finds near-optimal solutions in 70% shorter time than GAMS on average.