DocumentCode :
1479818
Title :
Optimal Scheduling of Multicluster Tools With Constant Robot Moving Times, Part II: Tree-Like Topology Configurations
Author :
Chan, Wai Kin Victor ; Ding, Shengwei ; Yi, Jingang ; Song, Dezhen
Author_Institution :
Dept. of Ind. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
Volume :
8
Issue :
1
fYear :
2011
Firstpage :
17
Lastpage :
28
Abstract :
In this paper, we analyze optimal scheduling of a tree-like multicluster tool with single-blade robots and constant robot moving times. We present a recursive minimal cycle time algorithm to reveal a multi-unit resource cycle for multicluster tools under a given robot schedule. For a serial-cluster tool, we provide a closed-form formulation for the minimal cycle time. The formulation explicitly provides the interaction relationship among clusters. We further present decomposition conditions under which the optimal scheduling of multicluster becomes much easier and straightforward. Optimality conditions for the widely used robot pull schedule are also provided. An example from industry production is used to illustrate the analytical results. The decomposition and optimality conditions for the robot pull schedule are also illustrated by Monte Carlo simulation for the industrial example.
Keywords :
Monte Carlo methods; industrial robots; mobile robots; pattern clustering; scheduling; trees (mathematics); Monte Carlo simulation; closed form formulation; constant robot moving times; multicluster tool; optimal scheduling; serial cluster tool; single blade robot; tree topology; Chemical analysis; Clustering algorithms; Industrial relations; Job shop scheduling; Optimal scheduling; Planarization; Processor scheduling; Scheduling algorithm; Service robots; Topology; Cluster tools; multiple machines; performance/ productivity; scheduling; semiconductor manufacturing;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2010.2046893
Filename :
5454420
Link To Document :
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