Abstract
In manufacturing environments with complex product structures and multiple production stages, material requirements planning (MRP) systems are the most commonly used for production planning and material supply decision making. However, in practice diverse difficulties arise, such as uncertainty in market demand, resources with limited available capacities, uncertainty in capacity data or uncertain costs. Likewise, classical procedures of resolution applied in MRP environments do not optimize production decisions. This paper provides a new linear programming model for medium term production planning in a capacity constrained MRP, multi-product, multi-level and multi-period manufacturing environment. Then, this model is transformed into three fuzzy models with flexibility in the objective function, in the market demand and in the available capacity of resources. The main goal is to determine the master production schedule, the MRP for each raw component in each period, stock levels, delayed demand, and capacity usage levels over a given planning horizon in such a way as to hedge against uncertainty. Finally, the model is tested using real data from an automobile seat manufacturer.
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