Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0098-1354(03)00192-3
Title: Heuristic algorithms for scheduling an automated wet-etch station
Authors: Bhushan, S.
Karimi, I.A. 
Keywords: Multi-product plant
Resource-constrained scheduling
Simulated annealing
Tabu search
Wafer fabrication
Wet-etch station
Issue Date: 15-Mar-2004
Source: Bhushan, S.,Karimi, I.A. (2004-03-15). Heuristic algorithms for scheduling an automated wet-etch station. Computers and Chemical Engineering 28 (3) : 363-379. ScholarBank@NUS Repository. https://doi.org/10.1016/S0098-1354(03)00192-3
Abstract: Wet-etching is a key step in wafer fabrication. A wet-etch station is a chemical batch process involving a complex interplay of mixed intermediate storage (MIS) policies and a shared robot for wafer transfers. Its operation poses a challenging resource-constrained scheduling problem that is crucial for enhancing productivity, improving yield and minimizing contamination. In this paper, we develop three new algorithms for scheduling wafer jobs for a given sequence, which comfortably outperform a literature algorithm in terms of solution quality without requiring excessive effort. Furthermore, we propose a simulated annealing (SA) algorithm for sequencing the wafer jobs. Using this SA algorithm, an existing sequencing algorithm based on tabu search (TS), two job-scheduling algorithms and two algorithms for initial job sequence, we identify eight complete algorithms for scheduling operations in an automated wet-etch station (AWS). After a thorough numerical evaluation, we conclude that the TS sequencing strategy combined with two of our three job-scheduling algorithms is the best option that yields up to 25-30% lower makespans than a literature algorithm, and requires acceptable computing times for industrial-scale problems. © 2003 Elsevier Ltd. All rights reserved.
Source Title: Computers and Chemical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/64012
ISSN: 00981354
DOI: 10.1016/S0098-1354(03)00192-3
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