Integrating Robot Assignment and Maintenance Management: A Multi-Agent Reinforcement Learning Approach for Holistic Control

Modern manufacturing requires effective integra- tion of production control and maintenance scheduling to improve productivity and quality. However, there have been few studies on this integrated control due to a lack of a comprehensive manufacturing system model. In response to this challenge, this paper presents a mathematical model framework for a mobile multi-skilled robot-operated manufacturing system that integrates three essential control aspects: robot assignment, maintenance scheduling, and product quality. Furthermore, an integrated control scheme is formulated in the Decentralized Partially Observable Markov Decision Process (Dec-POMDP) framework to showcase the proposed method’s efficacy in control. Results show that the proposed integrated model outperforms models that consider only system-level parameters, as well as those that only address maintenance scheduling and quality-related parameters.