Workload control-based modeling of repair team load distribution in maintenance and repair planning at an industrial enterprise

The article highlights the importance of enhancing the efficiency of an enterprise’s equipment maintenance strategy. It provides an overview of maintenance and repair planning practices and examines the application of mixed-integer linear programming (MILP) in enterprises across various industries. The study identifies challenges related to the variability of maintenance schedules, the need to incorporate unplanned repair activities, and the complexities of task allocation and workload balancing among repair teams. A MILP-based model is proposed for the dynamic scheduling of maintenance and repair tasks under constraints. The primary focus is on optimizing work distribution among repair teams while considering capacity limitations, the sequential execution of tasks, penalties for delays and overtime, and the balance between planning flexibility through soft and hard deadlines. The results demonstrate that the proposed model effectively minimizes operational penalties, ensures a balanced workload distribution among teams, and improves schedule adaptability to changes. The article also discusses potential avenues for further model development, including the integration of machine learning methods and real-time implementation. In conclusion, it is stated that the developed approach enhances the productivity of repair teams and improves the preventive maintenance strategy.