Production planning and performance optimization of reconfigurable manufacturing systems using genetic algorithm.

摘要: To stay competitive in the new dynamic market having large fluctuations product demand, manufacturing companies must use systems that not only produce their goods with high productivity but also allow for rapid response to changes. Reconfigurable system (RMS) is a paradigm enables respond quickly and cost effectively demand. In other words, RMS designed from outset, changes both hardware software components, order adjust its production capacity demand adapt functionality products. The effectiveness of an depends on implementing key characteristics capabilities design as well utilization stage. This paper focuses stage introduces methodology scalable capacities functionalities demands. It supposed arrival orders families follow Poisson distribution. are lost if they met immediately. Considering these assumptions, mixed integer nonlinear programming model developed determine optimum sequence tasks, corresponding configurations, batch sizes. A genetic algorithm-based procedure used solve model. applied make decision how improve performance RMS. Since there no practical RMS, numerical example validate results proposed solution procedure.