Efficient FDC based on Hierarchical Tool Condition Monitoring Scheme

Abstract : Tool condition evaluation and prognosis has been an arduous challenge in modern semiconductor manufacturing environment, especially for the foundry and analog companies with high product-mix and complicated technology nodes. More and more embedded and external sensors are installed to capture the genuine tool status for tool fault identification and, thus, tool condition analysis based on real-time equipment data becomes promising but also much more complex with the rapidly-increased number of sensors. In this paper, the feasibility of Generalized Moving Variance (GMV) technique is validated to consolidate the pure variations within tool Fault Detection and Classification (FDC) data into one indicator. Based on GMV, a hierarchical tool condition monitor scheme is developed by analyzing the GMV within functional clusters of sensors. With the introduction of this hierarchy, abnormal tool condition can be diagnosed and drilled down into sensor level for an efficient root cause analysis.
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Conference papers
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https://hal-emse.ccsd.cnrs.fr/emse-00742452
Contributor : Jakey Blue <>
Submitted on : Tuesday, October 16, 2012 - 2:37:54 PM
Last modification on : Tuesday, October 23, 2018 - 2:36:10 PM

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  • HAL Id : emse-00742452, version 1

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Jakey Blue, Alexis Thieullen, Agnès Roussy, Jacques Pinaton. Efficient FDC based on Hierarchical Tool Condition Monitoring Scheme. Advanced Semiconductor Manufacturing Conference 2012, May 2012, Saratoga Springs, New York, United States. pp.359-364. ⟨emse-00742452⟩

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