Joint Production and Maintenance Scheduling for Total Cost and Machine Overload Reduction in Manufacturing: A Genetic Algorithm Approach

The European manufactory sector has been greatly impacted in recent times by the COVID-19 pandemic and Russo-Ukrainian conflict, which have made energy prices soar to all-time highs reducing companies’ competitiveness global market. To remain competitive these crises, manufacturing companies need start optimizing not only their costs but also maintenance-derived costs, better planning maintenance activities, through joint production scheduling, improving machine longevity way of overload single machines. Accordingly, premise present paper is propose an intelligent scheduling system minimize total that is, as well single-machine balancing tasks between machines, while allowing for imposed constraints schedule. This achieved a Genetic Algorithm solve problem flexible job shop layouts. reduce retailer price volatility, generated renewable resources availability surplus selling, stipulated hours are considered benefited from much possible. Overload machines reduced minimizing occupation rate standard deviation A baseline scenario with real-production data work literature used validate proposed system. Obtained results show able reliably 11.3% up 15.4%, 32.3% 52.7%.