Paper Info
Title
A multiple criteria decision for trading capacity between two semiconductor fabs
Abstract
This paper presents a multiple criteria decision approach for trading weekly tool capacity between two semiconductor fabs. Due to the high-cost characteristics of tools, a semiconductor company with multiple fabs (factories) may weekly trade their tool capacities. That is, a lowly utilized workstation in one fab may sell capacity to its highly utilized counterpart in the other fab. Wu and Chang [Wu, M. C., & Chang, W. J. (2007). A short-term capacity trading method for semiconductor fabs with partnership. Expert Systems with Application, 33(2), 476-483] have proposed a method for making weekly trading decisions between two wafer fabs. Compared with no trading, their method could effectively increase the two fabs' throughput for a longer period such as 8weeks. However, their trading decision-making is based on a single criterion-number of weekly produced operations, which may still leave a space for improving. We therefore proposed a multiple criteria trading decision approach in order to further increase the two fabs' throughput. The three decision criteria are: number of operations, number of layers, and number of wafers. This research developed a method to find an optimal weighting vector for the three criteria. The method firstly used NN+GA (neural network+genetic algorithm) to find an optimal trading decision in each week, and then used DOE+RSM (design of experiment+response surface method) to find an optimal weighting vector for a longer period, say 10weeks. Experiments indicated that the multiple criteria approach indeed outperformed the previous method in terms the fabs' long-term throughput.
Year
DOI
Venue
2008
10.1016/j.eswa.2007.08.002
Expert Syst. Appl.
Keywords
Field
DocType
response surface method,optimal weighting vector,semiconductor fabs,trading capacity,multiple criteria decision,short-term capacity trading method,multiple fabs,previous method,optimal trading decision,multiple criteria trading decision,longer period,method firstly,neural network,expert system,design of experiment,genetic algorithm,semiconductor
Weighting,Multiple-criteria decision analysis,Computer science,Expert system,Operations research,Workstation,Throughput,Artificial neural network,Genetic algorithm,Design of experiments
Journal
Volume
Issue
ISSN
35
3
Expert Systems With Applications
Citations 
PageRank 
References 
4
0.44
7
Authors
2
Name
Order
Citations
PageRank
Muh-Cherng Wu122716.58
Wen-Jen Chang2141.59