Modeling demand driven with forecast regulation, safety stock setting and capacity analysis

High demand uncertainty has been a major challenge for production planning in assemble-to-order (ATO) environments. Regulating dealers' demand forecasts, determining appropriate safety stock levels and deciding required capacity levels are some of the typical problems solved by ATO firms. The main objective in this study is therefore to construct a mathematical model to deal with the aforementioned managerial problems under the consideration of product life cycle. According to the various cost and demand characteristics in different phases of a product life cycle, production managers may apply the proposed model to find a near optimal solution set of regulation factors for dealers' demand forecasts, appropriate levels of safety stocks and the number of key machines. Finally, an example is given to illustrate our model.