Development of new production simulator for complex production systems design

Recently, many production systems with complicated structures such as parallel, reworks, feed-forward, etc. Are widely used in high volume industries. This article formulates a new optimal design problem of a complex production system (CPS). The type of the machine tools and the buffer size are included to achieve a greater production rate of the CPS. Machine tools with different performances are selected from a list of products available in the market. The buffers are characterized by their cost and size. The machine tools are characterized by their cost, failure rate, repair rate and processing time. The optimal design problem is formulated as a combinatorial optimization one where the decision variables are buffers and types of machine tools. In order to find the optimal design of CPS, we propose a new production simulator system (PSS) in conjunction with genetic algorithm (GA) heuristics. PSS consists of a GA and a discrete simulator. PSS optimizes the design of the CPS by repeating discrete production simulations and utilizing the GA. The GA is used to generate an efficient solution maximizing the CPS production efficiency and minimizing the CPS production cost .In order to efficient use of the GA, we also propose a new gene arrangement called as Multi-vector Multi-group Method (MMM).