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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wagner, Thomas Gellrich, Andre Schwenke, Clemens Kabitzsch, Klaus Schneider, Germar |
| Copyright Year | 2014 |
| Description | Author affiliation: Infineon Technologies Dresden GmbH, Königsbrücker Strasse 180, D-01099, GERMANY (Schneider, Germar) || Technische Universität Dresden, Nöthnitzer Strasse 46, D-01187, GERMANY (Wagner, Thomas; Gellrich, Andre; Schwenke, Clemens; Kabitzsch, Klaus) |
| Abstract | To successfully manufacture logic and power semiconductors in existing high mix semiconductor factories, fast ramp up phases and frequent product changes are necessary. Especially for power semiconductor production, new manufacturing and automation concepts are required, e.g. regarding the use of other substrates than silicon wafers. To allow a judgment on how an existing automated material handling system (AMHS) can cope with the new challenges or which alterations are required, a material flow simulation is essential. However, the planning and creation of such simulation experiments is difficult because of the systems complexity, the large amount of boundary conditions and the effort of manually modifying and testing many different variants, partially using currently unforeseen automation concepts. In order to assist in this process, the authors suggest a method for rapidly creating valid simulation experiments using an ontology that allows for the reuse of previous experiments and system experts knowledge. |
| Starting Page | 2628 |
| Ending Page | 2639 |
| File Size | 747024 |
| Page Count | 12 |
| File Format | |
| e-ISBN | 9781479974863 |
| DOI | 10.1109/WSC.2014.7020107 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-12-07 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Ontologies Manufacturing Production Semiconductor device modeling Adaptation models Analytical models Knowledge based systems |
| Content Type | Text |
| Resource Type | Article |
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