FMS Optimisation using Discrete Event Simulation and Genetic Algorithm

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The industrial and manufacturing process automation has evolved rapidly and presently now it had gone through various phases of development. Advancement in the computer science and technology enable automation of sophisticated discrete event systems. FMS represents a class of system, which is configured to produce multiple products.


The production planning in the manufacturing systems are forecasted using Enterprise Resource Planning package recently. Since the market demand varies every now and then the process has to be driven based on that. Flexible manufacturing system functions by utilising these advancements and deliver multiple products of sufficient quantity as per the demand.
Genetic Algorithms are found to provide solutions for real-time problems in various operations. It has been used conveniently for researchers for various search and optimization problems. Owing to the problems associated with FMS optimization using Genetic algorithm and discrete simulation system this present project is initiated. Kazuhiro Saitou et al. (2002) presented a robust design of FMS using colored Petri nets and genetic algorithm. In their work it was found that the resource allocation and operation schedule were modelled as colored Petri nets. Their robust model designed minimized the production cost under multiple operation plan. It as able to handle large data sets conveniently as well as operates flexibly by using an genetic algorithm merged with shortest imminent operation time dispatching rule and automatically finds the optimal resource. ...
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