Sustainable Process Planning Strategies for Reconfigurable Manufacturing Systems in Industry 4.0

Reconfigurable manufacturing systems (RMS) have become increasingly popular in modern-day that quickly changing industrial landscape with the need for adaptable, effective, and sustainable production solutions. Traditional RMS planning has difficulties in adapting to modern manufacturing's dynamic nature, leading to inefficiencies in resource utilization, scheduling, and sustainability. This research explores sustainable process planning strategies for RMS in Industry 4.0 by integrating advanced optimization techniques with real-time, reducing environmental impact while maximizing production efficiency. A Fuzzy Proportional-Integral-Derivative (PID) control fused Dynamic Shuffled Shepherd Optimization (Fuzzy PID-DSSO) algorithm is proposed to identify optimal and eco-friendly manufacturing process plans. RMS efficiency data is obtained for the effective sustainable process. In production, the fuzzy PID controller is utilized for real-time control, improving the efficacy and stability of the system. The DSSO algorithm enhances process selection, sequencing, and reconfiguration, to maximize efficiency and minimize environmental effects. Findings show that the proposed model provides efficient outcomes in terms of optimal values of tool-changing (5) and setup-changing (5) in process planning for RMS in Industry 4.0. The results highlight that integrating Industry 4.0 technologies with sustainable planning strategies enhances eco-friendly manufacturing and adaptability in modern production environments.