Science and Technology Production
Book Chapter
Authorship
A. Aguirre
;
C.A. Méndez
;
C. De Prada
Date
2012
Publishing House and Editing Place
IFAC
Book
IFAC Proceedings Volumes
(pp. 780-785)
IFAC
IFAC
ISBN
978-390282305-2
Summary
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SIGEVA
Automated Wet-Etch Station (AWS) is a complex flow shop operation process in Semiconductor Manufacturing Systems. In this station, automated material-handling robots are used to move wafer lots across a lineal configuration of chemical and water baths. In every bath, limited processing times and complex storage policies must be assured. In this work, an optimization-based framework is developed to improve the operations of AWS. To do this, a sequential procedure based on mixed-integer linear pr...
Automated Wet-Etch Station (AWS) is a complex flow shop operation process in Semiconductor Manufacturing Systems. In this station, automated material-handling robots are used to move wafer lots across a lineal configuration of chemical and water baths. In every bath, limited processing times and complex storage policies must be assured. In this work, an optimization-based framework is developed to improve the operations of AWS. To do this, a sequential procedure based on mixed-integer linear programming (MILP) formulations is proposed. The aim of this work is to provide a robust approach to generate near-optimal results to industrial AWS scheduling problems with modest CPU time.
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Key Words
OPTIMIZATIONMILP APPROACHSEMICONDUCTOR INDUSTRY