A Decision Investment Model to Design Manufacturing Systems based on a genetic algorithm and Monte-Carlo simulation

The flexibility of manufacturing systems is one of the key factors to stay competitive when the companies face increasingly frequent market changes due to the rapid introduction of new products and constantly varying product demand. Flexible manufacturing systems are characterised by high investment costs, and often offer more flexibility that what is really needed. The emergent paradigm of Focused Flexible Manufacturing System concerns hybrid systems composed both of general purpose and dedicated resources. The research proposed in this paper concerns a genetic algorithm to design hybrid manufacturing systems composed of dedicated, general purpose (flexible) and reconfigurable machines. It has been considered a production mix with the customer demand, and the manufacturing operations required. The proposed model determines the machines to acquire among dedicated, flexible and reconfigurable machines and the production allocation over the planning horizon. Moreover, the combination of the genetic algorithm with the Monte Carlo simulation allows to include the market uncertainty in the decision model. A simulation environment has been developed to integrate the genetic algorithm and Monte Carlo approach.

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