Prediction of product layer cycle time using data mining

Michael Hassoun

doi:10.1109/WSC.2013.6721749

Prediction of product layer cycle time using data mining

Michael Hassoun

Department of Industrial Engineering and Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Based on a simulated non volatile memory (NVM) fab, we show that forecasting the steady state cycle time of process segments is possible using certain segment characteristics. We also show that the cycle time predictability is highly dependent on the choice of the segmentation, with the more efficient segmentation corresponding to the product layers.

Original language	English
Title of host publication	Proceedings of the 2013 Winter Simulation Conference - Simulation
Subtitle of host publication	Making Decisions in a Complex World, WSC 2013
Publisher	IEEE Computer Society
Pages	3905-3911
Number of pages	7
ISBN (Print)	9781479939503
DOIs	https://doi.org/10.1109/WSC.2013.6721749
State	Published - 2013
Event	43rd Winter Simulation Conference , WSC 2013 - Washington, DC, United States Duration: 8 Dec 2013 → 11 Dec 2013

Publication series

Name	Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
ISSN (Electronic)	0891-7736

Conference

Conference	43rd Winter Simulation Conference , WSC 2013
Country/Territory	United States
City	Washington, DC
Period	8/12/13 → 11/12/13

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10.1109/WSC.2013.6721749

Cite this

Hassoun, M. (2013). Prediction of product layer cycle time using data mining. In Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 (pp. 3905-3911). Article 6721749 (Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013). IEEE Computer Society. https://doi.org/10.1109/WSC.2013.6721749

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title = "Prediction of product layer cycle time using data mining",

abstract = "Based on a simulated non volatile memory (NVM) fab, we show that forecasting the steady state cycle time of process segments is possible using certain segment characteristics. We also show that the cycle time predictability is highly dependent on the choice of the segmentation, with the more efficient segmentation corresponding to the product layers.",

author = "Michael Hassoun",

year = "2013",

doi = "10.1109/WSC.2013.6721749",

language = "אנגלית",

isbn = "9781479939503",

series = "Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013",

publisher = "IEEE Computer Society",

pages = "3905--3911",

booktitle = "Proceedings of the 2013 Winter Simulation Conference - Simulation",

address = "ארצות הברית",

note = "43rd Winter Simulation Conference , WSC 2013 ; Conference date: 08-12-2013 Through 11-12-2013",

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Hassoun, M 2013, Prediction of product layer cycle time using data mining. in Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013., 6721749, Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013, IEEE Computer Society, pp. 3905-3911, 43rd Winter Simulation Conference , WSC 2013, Washington, DC, United States, 8/12/13. https://doi.org/10.1109/WSC.2013.6721749

Prediction of product layer cycle time using data mining. / Hassoun, Michael.
Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013. IEEE Computer Society, 2013. p. 3905-3911 6721749 (Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Hassoun M. Prediction of product layer cycle time using data mining. In Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013. IEEE Computer Society. 2013. p. 3905-3911. 6721749. (Proceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013). doi: 10.1109/WSC.2013.6721749

Prediction of product layer cycle time using data mining

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