Abstract
This paper introduces a novel design scheme which utilizes a programmable logic controller (PLC) network-based, computer distributed control system for the automation of a practical manufacturing process. Part of this system is modelled as a multi-product batching processing machine(BPM) which can process a batch of jobs simultaneously with a known and fixed number of jobs and their ready time. The optimal scheduling objective is that the different jobs are dispatched and sequenced in order to minimize the makespan and maximize the utilization of the BPM, it leads to a NP-hard combinatorial optimization problem. We apply genetic algorithms to solve this scheduling problem, and an optimal solution is obtained for a practical case study. The genetic algorithms approach demons (rates effectiveness, efficiency and robustness. The paper thus shows that computer distributed control plus evolutionary scheduling algorithms make the manufacturing system more 'intelligent' and 'flexible'.
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