he primary motivation of this study is to provide an easily implementable and cost-effective solution for reducing energy expenses, improving slurry quality, mitigating system instability due to random breakdowns, and minimizing maintenance frequencies in the ball mills of the tile industry. To achieve this goal, a two-step framework is proposed which can also be applied to parallel machines in make-to-order environments. The first step integrates the usage-based maintenance and production scheduling under time-of-use (TOU) electricity prices and involves a mixed integer linear programming (MILP) model with buffer time insertion to handle unpredictable machine unavailability. The second step suggests a combination of model-based and manual reactive policies for rescheduling. Compared to its non-energy-aware counterpart, the proposed model shows a 22% improvement in energy costs and a 4% increase in energy savings. Additionally, the usage-based mainte- nance strategy reduces maintenance frequencies by more than 50% compared to the time-based one. By inte- grating TOU-based production scheduling with usage-based maintenance scheduling, we offer three advantages for energy-intensive industries: 1) increased scheduling flexibility to shift production to low-tariff periods, 2) the ability to schedule maintenance operations during idle time resulting from production shifts, and 3) reduced maintenance frequencies for machines with extended idle times through a usage-based maintenance strategy. The proposed approach performs best when machines exhibit significant differences in energy consumption rates and have high total idle times. However, implementing it for bottleneck machines does not lead to notable improvements in energy-related indicators.

Keywords