Production planning and scheduling using a fuzzy decision system

In this paper short-range planning and scheduling problems are addressed using a nonclassical approach supported by fuzzy theory. The proposed methodology uses a hierarchical structure which includes three decision levels (higher, middle, lower), each responsible for a different production problem with a different time scale. The methodology approaches the tasks associated with each level using a heuristic formulation and solves the short-range planning and scheduling problems with a nonstationary policy. The higher decision level determines safety stock levels used to compensate for future resource failures. At the middle level, loading rates are computed. This is accomplished through a fuzzy controller that tends to minimize the error between the cumulative production and the cumulative demand while keeping the work in process below acceptable values. Finally, the lower level controls the flow of parts among the resources, using a modified version of the Yager's fuzzy decision method. This method has the ability to use several criteria to generate a decision. Simulation results reveal that the proposed system exhibits good performance, in terms of a high production percentage and a low WIP, under resource failures and demand variations.<
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