Abstract
This paper proposes an integrated Genetic Algorithms and Fuzzy Systems method in choosing alternative machines for process planning and scheduling of an Agile manufacturing system. A case study carried out in an agile company based in the production of automobile parts. Instead of choosing alternative machines randomly, machines are being selected based on the machines reliability. The MTTF values are input in a fuzzy inference mechanism, which outputs the machine reliability. The machine is then being penalized based on the fuzzy output. The most reliable machine will have the higher priority to be chosen. In order to overcome the problem of un-utilization machines, sometimes faced by unreliable machine, the Genetic Algorithms have been used to balance the load for all the machines. Some Results shows in integrating production capability and load balancing during scheduling activity.
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