Simulation of manufacturing operations: optimization of buffer sizes in assembly systems using intelligent techniques

摘要: When the systems under investigation are complex, analytical solutions to these become impossible. Because of complex stochastic characteristics systems, simulation can be used as an analysis tool predict performance existing system or a design test new varying circumstances. However, is extremely time consuming for most problems practical interest. As result, it impractical perform any parametric study performance, especially with large parameter space. One approach overcome this limitation develop simpler model explain relationship between inputs and outputs system. Simulation metamodels increasingly being in conjunction original simulation, improve understanding decision-making processes. In study, artificial neural networks (ANN) metamodel developed asynchronous assembly ANN together simulated annealing (SA) optimize buffer sizes