Job shop scheduling under dynamic and stochastic manufacturing environment

In practice, manufacturing systems operate under dynamic and stochastic environment where unexpected events (or interruptions) occur continuously in the shop. Most of the scheduling literature deals with the schedule generation problem which is only one aspect of the scheduling decisions. The reactive scheduling and control aspect has scarcely been addressed. This study investigates the effects of the stochastic events on the s'stem performance and develops alternative reactive scheduling methods. In this thesis, we also study the single-pass and multi-pass scheduling heuristics in dynamic and stochastic job shop scheduling environment. We propose a simulation-based scheduling system for the multi-pass heuristics. Finally, we analyze the interactions among the operational strategies (i.e, lookahead window, scheduling period, method used for scheduling), the system conditions, and the unexpected events such as machine breakdowns and processing time variations.