Optimal Scheduling-Maintenance Strategy via Dynamic Processing Time for Serial-Parallel Flow Shop

System reliability and production efficiency are two important indicators in manufacturing. However, they cannot be optimized simultaneously. In reality, high production efficiency means the accelerated degradation of equipment, leading to an increase in maintenance frequency, which in turn restricts production. Therefore, production and scheduling are two interactive influencing factors in manufacturing. Existing studies ignore the influence of this interaction on the system. To solve these problems, this paper proposes a joint optimization model for scheduling and maintenance in series-parallel flow shop, and constructs an equipment degradation model considering dynamic processing time and job allocation to reflect the mutual influence between scheduling and maintenance. Aiming at the joint optimization problem, a twostage adaptive maintenance strategy is proposed and the corresponding genetic algorithm is designed. Finally, the effectiveness of the proposed algorithm was verified through numerical experiments.