An integrated plant capacity and production planning model for high-tech manufacturing firms with economies of scale

This study developed a nonlinear mixed integer programming (MIP) model for high-tech manufacturer to determine the optimal supply chain network design. The impacts of economies of scale on the optimal capacity and the production amount are also explored. A heuristic solution approach, based on simulated annealing (SA), is developed to solve the optimal problem. An example of a wafer foundry company is provided to demonstrate the application of the model. Results show that when determining the production amount for multiple plants, a large-sized capacity plant with low capital costs and low production costs has a high priority for fulfilling the capacity due to not only having the higher capability to satisfy the customer demand but also the advantage of saving costs. The results show that the benefits brought about by centralized production are larger than the increased transportation cost. The results also show without using many small-sized capacity plants combined with high utilization, operating few larger-sized capacity plants with lower utilization is more cost effective for the manufacturer as long as the customer demand is large enough to offset the high capital cost.