Multi-period capacity planning for integrated product-process design

This paper presents an optimization-based method to aid capacity planning decisions by quantifying the trade-off between the capital and operating costs of a production facility and the quality of finished products. Given forecasted market demands during multiple production periods, multi-objective optimization selects the quantity and the types of production machines to be purchased during each period, which simultaneously maximize the quality of the finished products and minimize the total production cost during the periods. The product quality is estimated as the statistical variation from the performance targets obtained from the output tolerances of the machines that manufacture the components, via Monte Carlo simulation. The production cost is estimated as the annual equivalent cost of owning and operating a production facility during the production periods, obtained from the price of each machine and a discrete event simulation of production process. A case study with an automotive valvetrain is presented to illustrate the method.