Rescheduling in Industrial Environments: Emerging Technologies and Forthcoming Trends

Abstract

The scheduling problems in Manufacturing Systems are characterized by a high degree of uncertainties arising from diverse factors such as stochastic environments and data incompleteness. However, traditionally the schedules generated for those environments are deterministic, or quasi-deterministic at the best, and only recently the approach static is being shifted for a stochastic approach. This paper highlights the uncertainty characteristics that should be taken into account to improve the schedule robustness.   In this research, selected cases from the last ten years of stochastic scheduling literature are reviewed, specially the ones relatives to  Semiconductor Factories. Another  important objective of our report is to bring the attention of researchers to emerging methodologies and technologies coming from the subject of Knowledge Representation and Reasoning.  These new methodologies and technologies are well suited to solve hard combinatorial problems with incomplete knowledge.