ReDS—A dynamic planning, scheduling, and control system for manufacturing

Abstract

Abstract Classical scheduling theory has not solved the practical needs of factory management. Management objectives are often many, ill-defined, and changing. Management is generally interested in decision support tools to facilitate specification of changed objectives, to react to shop floor changes, and to make short and long-term planning decisions. This paper describes a dynamic, intelligent, real-time factory scheduling system known as Requirements Driven Scheduling (ReDS). ReDS combines Artificial Intelligence (AI) and Operational Research (OR) techniques to find solutions that are not always optimal but are acceptable to the changing needs of management. ReDS uses a number of techniques such as least commitment planning and abstraction in order to make a plan. To optimize the allocation of resources, heuristics are applied from order and shop-floor points of view. ReDS works in time and event-driven modes of operation. ReDS uses real-time data for two purposes; short term feedback to reconfigure the current schedule, and long-term feedback to adjust heuristics. Using this feedback, ReDS can automatically conform the factory in which it operates. An essential partner for ReDS operation is a data collection and equipment monitoring system. The results of coupling ReDS to a real-time data collection system in a VLSI development line are encouraging. The data collection system receives data from and returns instructions to the shop floor.