A joint model of production scheduling and predictive maintenance for minimizing job tardiness

As increasingly diverse tasks are being processed on single multi-functional machine, production scheduling has become a critical issue in the planning and management of manufacturing processes. However, the majority of production scheduling literature ignores machine availability and assumes that machine is available all the time. In reality, machines physically deteriorate with increased usage and time. Thus, there is an intense need for manufacturing industries to reduce unexpected breakdowns and remain competitive, and motivating maintenance operations should be integrated into production scheduling models. With the advancements in sensor and prognostic technologies, machine's condition can be monitored and assessed over time through conducting predictive maintenance. Hence, based on this scheme, this study proposes a single-machine-based scheduling model incorporating production scheduling and predictive maintenance. A machine's effective age and remaining maintenance life are introduced to describe machine degradation. Finally, a numerical example is given; the computational results show that this integrated scheduling model has better performance than those existing models, which proves its efficiency.