A production planning methodology for semiconductor manufacturing based on iterative simulation and linear programming calculations

Abstract

We introduce a methodology for automated production planning of semiconductor manufacturing based on iterative linear programming (LP) optimization and discrete-event simulation calculations. The LP formulation incorporates epoch dependent parameters for flow times from lot release up to each operation on each manufacturing route. LP-derived release schedules are used as input to the simulation model, from which statistics on flow times are collected and used to reformulate the LP model for a revised planning calculation. Iteration continues until satisfactory agreement between simulation and LP models is obtained. We demonstrate in experiments on an industry data set that a relatively small number of iterations is required to develop a production plan correctly characterizing future flow times as a function of factory load and product mix. The methodology makes possible automated production planning of semiconductor manufacturing on an engineering work station.