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

Authors: Shwu-Min Horng, John W. Fowler, Jeffery K. Cochran

Addresses: Industrial Engineering, Arizona State University, Tempe AZ 85287-5906, USA. Industrial Engineering, Arizona State University, Tempe AZ 85287-5906, USA. Industrial Engineering, Arizona State University, Tempe AZ 85287-5906, USA

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.

Keywords: ion implantation; scheduling; sequence dependent set-ups; genetic algorithm.

DOI: 10.1504/IJMTM.2000.001339

International Journal of Manufacturing Technology and Management, 2000 Vol.1 No.2/3, pp.156-172

Published online: 02 Jul 2003 *

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