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: A multiproduct, multiperiod, multistage network model is presented for the planning of ord release and production scheduling in a flexible manufacturing system environment under the existence alternate routings. It is assumed that premanufacturing decisions such as machine grouping and tool loading have been made, so that setup costs and setup times are negligible and can be included in th processing times. The decision process addressed by the model is the disaggregation of weekly produc requirements to daily production requirements, the determination of production batch sizes for each operation of each part type, and the daily assignment of each batch to machine groups given the flexibility of alternate routings. The model also provides the interface and linkage between an MRP component planning system and the shop scheduling system. The model is solved using a price-directiv decomposition technique with column generation. Experimentation is performed with the model for varying problem sizes to determine the impact of shop flexibility on total cost, inventory levels, e of bottlenecks, shop utilization, and the number of setups and split lot production. The results ind important cost-benefit trade-off implications for system design and acquisition. For example, if in setup costs and times are nonnegligible, then it is shown that increasing the routing flexibility of without a parallel decrease in setup costs and times is unlikely to reap significant benefits., A multiproduct, multiperiod, multistage network model can enhance routing flexibility and production scheduling in a flexible manufacturing system. Assuming the existence of altrnate routings and no setup time considerations, this model breaks down weekly production requirements to daily total production needs, sets the daily production quota for each operation of each part type and allocates the production quotas to machine groups given the flexibility of alternate routings.

Rapid changes in technology and intense competition have led to shorter product life cycles in both high-technology industries and industries not commonly regarded as high-technology. As a result of short product life cycles, firms are faced with the challenge of planning for facilities whose useful lives are much longer than the life cycle of any individual product it manufactures. This paper develops a model to analyze the critical trade-offs associated with determining the best level of flexibility for a facility that manufactures a series of high-volume products, sequentially over each product's life cycle. Our analysis considers the benefits associated with more flexible facilities including reduced changeover costs and earlier market entry, versus the higher initial investment and higher production costs typically encountered. Keywords: Capacity planning flexibility; product life cycle, Increasingly shorter production life cycles have reached the point where the life cycles are shorter than the manufacturing facility life cycle. This requires that manufacturing facilities be endowed with the capability to produce other products with the minimum of modifications or costs. A model was developed for the evaluation of the optimum level of production machinery flexibility based on the product life cycle. The model considers other factors such as product values, average production costs, changeover costs and discount rates.