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 forecas ts, determining appropriate safety stock levels and deciding required capac ity levels are some of the typical problems solved by ATO firms. The main o bjective in this study is therefore to construct a mathematical model to de al with the aforementioned managerial, problems under the consideration of product life cycle. According to the various cost and demand characteristic s in different phases of a product life cycle, production managers may appl y the proposed model to find a near optimal solution set of regulation fact ors for dealers' demand forecasts, appropriate levels of safety stocks and the number of key machines. Finally, an example is given to illustrate our model. Significance: This paper presents a linear programming model that integrate s the activities of forecasting adjustment, material preparation and key ma chine quantity determination in an ATO environment. The proposed model refl ects the phenomena of a product life cycle passing through the different ap pearances of the demand and cost in distinct phases.