DocumentCode :
962631
Title :
Levels of Capacity and Material Handling System Modeling for Factory Integration Decision Making in Semiconductor Wafer Fabs
Author :
Jimenez, Jesus A. ; Mackulak, Gerald T. ; Fowler, John W.
Author_Institution :
Ingram Sch. of Eng., Texas State Univ.-San Marcos, San Marcos, TX
Volume :
21
Issue :
4
fYear :
2008
Firstpage :
600
Lastpage :
613
Abstract :
As the costs of building a new wafer fab increase, a detailed simulation model representing the production operations, the tools, the automated material handling systems (AMHS), and the tool-AMHS interactions is needed for accurately planning the capacity of these facilities. The problem is that it currently takes too long to build, experiment, and analyze a sufficiently detailed model of a fab. The key for building accurate and computationally efficient fab models is to decide on the right amount of model details, specifically those details representing the equipment capacity and the AMHS. This paper identifies a method for classifying a fab model by the level of capacity detail, the level of AMHS detail, or the level of capacity/AMHS detail. Within the capacity/ AMHS modeling level, our method further differentiates between detailed integrated capacity/AMHS models and abstract coupled capacity/AMHS models. The proposed classification method serves as the basis of a framework that helps users select the system components to be modeled within a desired level of detail. This research also provides a review of past-published literature summarizing the work done at each of the proposed fab modeling levels. A case study comparing the performance between an integrated capacity/AMHS model and a coupled capacity/AMHS model is presented. The study demonstrates that the coupled model generates cycle time estimates that are not statistically different than those generated by the integrated model. This paper also shows that the coupled model can improve CPU time by approximately 98% in relation to the integrated model.
Keywords :
capacity planning (manufacturing); decision making; discrete event simulation; materials handling; semiconductor device manufacture; AMHS interactions; CPU time; abstract coupled capacity; automated material handling system modeling; capacity planning; classification method; cycle time estimation; discrete-event simulation; factory integration decision making; integrated capacity; semiconductor wafer fabrication; size 300 mm; Analytical models; Capacity planning; Costs; Decision making; Fabrication; Materials handling; Predictive models; Production facilities; Production systems; Semiconductor device modeling; Automated material handling systems (AMHS); capacity planning; discrete-event simulation; modeling; wafer fabrication;
fLanguage :
English
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
Publisher :
ieee
ISSN :
0894-6507
Type :
jour
DOI :
10.1109/TSM.2008.2005368
Filename :
4657428
Link To Document :
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