The Role of Simulation in the Development of Intelligence for Flexible Manufacturing Systems

Discrete event simulation has been successfully employed as an analysis tool for predicting the effect changes have on existing and hypothetical systems. This insight allows for more informed appraisals of alternatives, greatly enhancing the planning function. Simulation modelling allows microscopic analysis of complex system dynamics giving the intimate understanding required to maximise the efficiency of such systems. As well as being used to predict the future and explain the operation of complex processes, simulation models are also used in real-time control systems to provide decision support for automated (intelligent) decision makers. Current research suggests that a combination of simulation and ‘meta-heuristic’ optimisation techniques applied to analytically intractable problems can yield optimal or near optimal solutions. This paper gives a brief review of the history of discrete event simulation and discusses the role of simulation modelling in the ever-changing manufacturing environment. It pays particular attention to the importance of simulation in intelligent, highly automated, flexible manufacturing systems. It details a case study in which a simulation model and an optimisation strategy are integrated as part of an intelligent decision maker. This application implements an adaptation of the Amherst – Karlsruhe model of an automated dynamic scheduling system.