A genetic algorithm approach to manage ion implantation processes in wafer fabrication

Abstract

The management of ion implantation processes is one of several challenging problems in scheduling wafer fabrication facilities. A complicating factor is the fact that there are sequence dependent set-ups (e.g. species changes). Because of the set-ups, it is sometimes desirable to leave an implanter idle (if another lot requiring this species will arrive soon) rather than to change the set-up. We study the use of a genetic algorithm (GA) to assign the jobs to machines where the First In-First Out (FIFO) dispatching rule is used to schedule the individual machines. This approach is compared to the use of a commonly used dispatching policy-set-up avoidance. The parameters of the genetic algorithm (population size, crossover probability, and mutation probability) are analysed using response surface techniques to find combinations that allow the algorithm to determine a relatively good solution in a short CPU time.