DocumentCode :
3273238
Title :
An optimization approach for parallel machine problems with dedication constraints: Combining simulation and capacity planning
Author :
Klemmt, Andreas ; Weigert, Gerald
Author_Institution :
Electron. Packaging Lab., Tech. Univ. Dresden, Dresden, Germany
fYear :
2011
fDate :
11-14 Dec. 2011
Firstpage :
1981
Lastpage :
1993
Abstract :
The main idea of the presented new approach is to join a discrete event simulation (DES) and mathematical programming techniques (i.e. mixed integer programming, MIP) for optimization of complex manufacturing processes. Thereby, a DES model allows a detailed problem description. For a target oriented optimization several capacity allocation problems are solved by a MIP solver, reducing the degrees of freedom in the DES model. As an example a typical parallel machine scheduling problem arising in semiconductor industry was chosen. Different process constraints like machine dedications, setups, auxiliary resources and processing time dependences are discussed - advantages and disadvantages of simulation-based and exact scheduling approaches are drafted. The investigated optimization goals comprise the reduction of total tardiness and setups efforts as well as a balanced machine utilization. Based on real manufacturing data of a wafer test area this approach is evaluated.
Keywords :
capacity planning (manufacturing); discrete event simulation; manufacturing processes; mathematical programming; parallel machines; semiconductor industry; DES; capacity planning; complex manufacturing process; dedication constraints; discrete event simulation; mathematical programming; optimization; parallel machine problems; semiconductor industry; Dispatching; Job shop scheduling; Mathematical model; Optimization; Parallel machines; Resource management; Schedules;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2011 Winter
Conference_Location :
Phoenix, AZ
ISSN :
0891-7736
Print_ISBN :
978-1-4577-2108-3
Electronic_ISBN :
0891-7736
Type :
conf
DOI :
10.1109/WSC.2011.6147912
Filename :
6147912
Link To Document :
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