Projecting on-time performance for deterministic schedules in dynamic environments

Abstract

Manufacturing in a world class environment demands a high level of customer service. The production control department is responsible for achieving this high level of service through accurate planning and scheduling. The ability to achieve such a high level of customer service is limited by the scheduling tools currently available. Production planning is typically performed using MRP infinite capacity, fixed lead-time, backward scheduling. The work in each MRP time-bucket is then sequenced to develop a schedule. The production floor however, is not a static environment. Dynamic events, that cannot be scheduled, degrade production performance relative to the projected schedule. In this paper the relationship between dynamic events and schedule degradation is examined. Common approaches to production scheduling underestimate the effect of capacity loading relative to unplanned events and schedule achievability. These dynamic events exhaust capacity previously allocated to production orders. To hedge against such known, but unscheduled events, production control can schedule resources to a level less than full capacity. The size of the capacity hedge and the duration of the unplanned event dictate the time to recover from the backlog created by these dynamic events. A performance metric is developed to measure the ability to achieve customer promise dates. A machine loading policy is also presented to achieve the optimal capacity hedge point that will maximize this performance measure. The results are compared to simulated failures to examine the accuracy of the predicted performance degradation. The results suggest a trade-off of throughput for improved performance to customer promise date.