Abstract
To improve semiconductor industry manufacturing efficiency and order fill rate, we check the methods of production plan. Because the goals and constraints of different semiconductor supply chain stages are very different, each stage tends to schedule its own production plan and try to take into account the goals and constraints of other stages based on production planners’ past experiences. However, these experiences are often too vague to be a clear planning rules and the problem is too complicate for the planner to consider thoroughly. Also, it is hard for other planers to follow their methods. Even though some of the experiences can be documented and become clear scheduling rules, these rules are not necessary reasonable. In this research, we document production planner’s past experiences to identify and validate these planning rules. We construct a mathematic model by the planning rules to help the decision makers consider the whole supply chain relationship in a systemic way. On the other hand, we use linear programming software Gurobi to generate the results of plans automatically. We can get appropriate solutions for each plan and reduce the waste of time and labors. Besides, we have extension models to adjust the order situations when the demand of product is higher than the supply one. We make it possible to integrate between the market-end and manufacturing-end to avoid revising the plan repetitively.