Abstract:
Photolithography plays a key role in semiconductor manufacturing systems. In this paper, we address the capacity allocation problem in the photolithography area (CAPPA) s...Show MoreMetadata
Abstract:
Photolithography plays a key role in semiconductor manufacturing systems. In this paper, we address the capacity allocation problem in the photolithography area (CAPPA) subject to machine dedication and tool capability constraints. After proposing the mathematical model of the considered problem, we present a new genetic algorithm named RGA which was derived from a psychological concept called Reference Group in society. Finally, to evaluate the efficiency of the algorithm, we solve a real case study problem from a semiconductor manufacturing company in Ireland and compare the results with one of the genetic algorithms proposed in the literature. Results show the effectiveness and efficiency of RGA to solve CAPPA in a reasonable time.
Published in: 2018 Winter Simulation Conference (WSC)
Date of Conference: 09-12 December 2018
Date Added to IEEE Xplore: 03 February 2019
ISBN Information: