Multistage semiconductor memory inventory model based on survival analysis

Inventory management is challenging and critical problem in the semiconductor memory manufacturing industry. Rapid technological development and short product life cycle cause a high risk of product obsolescence. However, manufacturers must still hold a reasonable level of inventory to satisfy the needs of customers when demand is uncertain and lead times are long. In this study, the needs and constraints of this semiconductor manufacturing problem based on inventory days were considered and a linear programming model was constructed with the objective of determining a weighted minimal cost for resolving the problem of multistage inventory management. This study applied the concept of material requirement planning for calculating the inventory information of various stages. In addition, the shortage problem, excessive or inadequate safety stock levels, and capacity balance of technology were considered. Finally, a numerical study was conducted for evaluating the performance of the inventory model, and the results showed that the model can assist decision makers in early preparation of inventories. Under the same condition of demand fulfillment, the proposed model can be used to reduce the unnecessary inventory of downstream banks and avoid the risk of future inventory obsolescence, thereby enhancing competitiveness.