This paper presents a simulation-based method to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon. Given demand forecasts in future production periods, a multi-objective genetic algorithm searches for the optimal types and quantity of the production machines to be purchased during each period, which simultaneously maximize the product quality and minimize the production cost during the entire planning horizon. Case studies on automotive valvetrain production are presented as a demonstratio
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