Optimizing Multi-Technician Work Order Scheduling: A Dispatching Rule Algorithm Approach to Reduce Downtime

This study investigated the effectiveness of various dispatching rule algorithms in optimizing work-order scheduling involving paired technicians, with a focus on minimizing downtime in industrial maintenance operations. While efficient scheduling is essential for operational productivity, existing approaches often emphasize complex technician utilization analyses that can delay decision-making and exacerbate downtime. Through simulation-based evaluation of seven dispatching rules First Come First Serve (FCFS), Last Come First Serve (LCFS), Round Robin, Longest Processing Time (LPT), Shortest Processing Time (SPT), Weighted Longest Processing Time (WLPT), and Weighted Shortest Processing Time (WSPT), this study measures key performance indicators such as waiting time and repair time. The results reveal that FCFS consistently outperforms other algorithms in reducing downtime, highlighting that technician speed and scheduling responsiveness are more impactful than deep specialization in technician roles. By demonstrating the practical advantages of simpler, rule-based scheduling, this study contributes to the body of knowledge on maintenance optimization and offers actionable insights for industries seeking to streamline technician allocation. Future research should explore AI-based scheduling and dynamic team configurations to further enhance efficiency without introducing unnecessary complexity.