Nonstationary signal analysis and support vector machine based classification for vibration based characterization and monitoring of slit valves in semiconductor manufacturing

M. Musselman, H. Xie and D. Djurdjanovic ()
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M. Musselman: Lam Research Corporation
H. Xie: University of Texas
D. Djurdjanovic: University of Texas

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 3, No 9, 1099-1110

Abstract: Abstract Slit valves play an important role in semiconductor manufacturing, enabling creation and maintaining of a vacuum environment required for wafer processing. Due to the high volume of production in the modern semiconductor industry, slit valves could experience severe degradation over their lifetime. If maintenance is not applied in due time, degraded valves may lead to defects in finished products due to pressure loss and particle generation. In this paper, we propose methods for signal processing and feature extraction for analysis of slit valve vibration signals. These methods are then used to demonstrate the ability to reliably, accurately and efficiently distinguish between vibration patterns of each individual valve via a multi-class classification procedure. Furthermore, instantaneous time–frequency entropy of valve vibrations enabled long term monitoring of a slit valve in production, in spite of variations in valve speed and operations.

Keywords: Slit valves; Semiconductor manufacturing; Vibrations based monitoring; Nonstationary signal analysis; Multi-class classification (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-017-1308-4

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