Predictable scheduling of a single machine with breakdowns and sensitive jobs

Abstract

Production schedules released to the shop floor have two important functions: allocating shop resources to different jobs to optimize some measure of shop performance and serving as a basis for planning external activities such as material procurement, preventive maintenance and delivery of orders to customers. Schedule modification may delay or render infeasible the execution of external activities planned on the basis of the predictive schedule. Thus it is of interest to develop predictive schedules that can absorb disruptions without affecting planned external activities while maintaining high shop performance. We present a predictable scheduling approach, that inserts additional idle time into the schedule to absorb the impacts of breakdowns. The effects of disruptions on planned support activities are measured by the deviations of job completion times in the realized schedule from those in the predictive schedule. We apply our approach to minimizing total tardiness on a single machine with stochastic machine failures. We then extend the procedure to consider the case where job processing times are affected by machine breakdowns, and provide specialized rescheduling heuristics. Extensive computational experiments show that this approach provides high predictability with minor sacrifices in shop performance.