A threshold- and priority-based dispatching rule for the simulation-based dynamic scheduling optimization in automated manufacturing systems

Efficient production planning is a critical and challenging task in Make-To-Order (MTO) Automated Manufacturing Systems (AMSs), requiring a flexible production process capable of managing large volumes of highly-customized orders while preventing resource contention. Considering the timing of customers’ needs and the availability of production resources, it becomes important to find an efficient order-dispatching sequence to optimize the coordination across multiple production units. To achieve this, a simulation model is essential to evaluate and validate the proposed algorithm’s performance prior to real-world implementation. In this study, a heuristic algorithm based on a Threshold- and Priority-Based Dispatching Rule (TPDR) is presented aimed at minimizing flow time while avoiding potential deadlocks and meeting key performance indicators (KPIs). The proposed heuristic is integrated into a discrete-event simulation (DES) framework, allowing for dynamic adjustments to the dispatching sequence of high-volume and highly-customized orders based on real-time system/machine performance. To assess its effectiveness, a case study of a Mail Order Pharmacy Automation (MOPA) system is conducted within three DES models, comparing the proposed TPDR-based heuristic with three widely used dispatching rules. The simulation results demonstrate that the TPDR-based heuristic algorithm significantly enhances productivity and eliminates production bottlenecks while maintaining throughput levels.