Abstract | ||
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Short Term Simulation (STS) that provides daily forecasts of work center performance has been deployed in Infineon Technologies for operational decision makings. To ensure good forecast accuracy, the STS requires high modeling fidelity, requiring good basic data quality for model building. Forecast accuracy is maintained through an Automatic Model Verification (AMV) engine. The AMV monitors and verifies discrepancies between simulation and reality for modeling elements such as process dedication, uptime, process time/throughput, sampling rate, and batch/stream size. It reports the verification results with a multi-layered view, at different levels of abstraction, and the gaps between simulation and reality are highlighted. The user can quickly identify gaps and make correction to the errors. In this paper, we give an insight to the complete workflow on how AMV helps to detect data issues, the options to resolve such issues and the positive effect to the simulation forecast quality.
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Year | DOI | Venue |
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2013 | 10.5555/2675983.2675876 | WSC '13: Winter Simulation Conference
Washington
D.C.
December, 2013 |
Field | DocType | ISSN |
Fidelity,Data quality,Abstraction,Computer science,Simulation,Sampling (signal processing),Semiconductor device fabrication,Model building,Throughput,Workflow | Conference | 0891-7736 |
ISBN | Citations | PageRank |
978-1-4799-2077-8 | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Boon-Ping Gan | 1 | 68 | 9.08 |
Peter Lendermann | 2 | 219 | 25.96 |
Wolfgang Scholl | 3 | 62 | 8.06 |
Marcin Mosinski | 4 | 1 | 0.70 |
Patrick Preuss | 5 | 12 | 4.16 |