The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.

Intelligent data-driven health performance of manufacturing tools is the key element in reducing costs and establishing the right maintenance schedule. With the correct instruments to monitor the reduction in performance of manufacturing tools, companies can plan maintenance work systematically. Thi...

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Main Authors: Noor Fawazi, Noor Fawazi, Azraei, Amirul, Wan Muhammad Haziq, Wan Muhammad Haziq, Muhammad Hakimi, Muhammad Hakimi
Format: Conference or Workshop Item
Published: 2023
Subjects:
Online Access:http://eprints.utm.my/107311/
http://dx.doi.org/10.1063/5.0154235
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spelling my.utm.1073112024-09-01T07:03:19Z http://eprints.utm.my/107311/ The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring. Noor Fawazi, Noor Fawazi Azraei, Amirul Wan Muhammad Haziq, Wan Muhammad Haziq Muhammad Hakimi, Muhammad Hakimi TA Engineering (General). Civil engineering (General) Intelligent data-driven health performance of manufacturing tools is the key element in reducing costs and establishing the right maintenance schedule. With the correct instruments to monitor the reduction in performance of manufacturing tools, companies can plan maintenance work systematically. This paper examines measured vibration signals for the health monitoring of dried vacuum pumps. In semiconductor industries, monitoring of the performance of the dried vacuum pump is very critical, not only for early maintenance work before catastrophic failures, but also for systematic pumping switch operations. Statistical time domain and Short-time Fourier transform (STFT) parameters are used for the identification of the vacuum pump condition in this paper. 2023-07-25 Conference or Workshop Item PeerReviewed Noor Fawazi, Noor Fawazi and Azraei, Amirul and Wan Muhammad Haziq, Wan Muhammad Haziq and Muhammad Hakimi, Muhammad Hakimi (2023) The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring. In: International Conference Of SNIKOM 2021, 18 September 2021, Medan, Indonesia. http://dx.doi.org/10.1063/5.0154235
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Noor Fawazi, Noor Fawazi
Azraei, Amirul
Wan Muhammad Haziq, Wan Muhammad Haziq
Muhammad Hakimi, Muhammad Hakimi
The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
description Intelligent data-driven health performance of manufacturing tools is the key element in reducing costs and establishing the right maintenance schedule. With the correct instruments to monitor the reduction in performance of manufacturing tools, companies can plan maintenance work systematically. This paper examines measured vibration signals for the health monitoring of dried vacuum pumps. In semiconductor industries, monitoring of the performance of the dried vacuum pump is very critical, not only for early maintenance work before catastrophic failures, but also for systematic pumping switch operations. Statistical time domain and Short-time Fourier transform (STFT) parameters are used for the identification of the vacuum pump condition in this paper.
format Conference or Workshop Item
author Noor Fawazi, Noor Fawazi
Azraei, Amirul
Wan Muhammad Haziq, Wan Muhammad Haziq
Muhammad Hakimi, Muhammad Hakimi
author_facet Noor Fawazi, Noor Fawazi
Azraei, Amirul
Wan Muhammad Haziq, Wan Muhammad Haziq
Muhammad Hakimi, Muhammad Hakimi
author_sort Noor Fawazi, Noor Fawazi
title The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
title_short The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
title_full The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
title_fullStr The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
title_full_unstemmed The performance degradation of a dried vacuum pump utilizing statistical time domain parameters and STFT vibration signal monitoring.
title_sort performance degradation of a dried vacuum pump utilizing statistical time domain parameters and stft vibration signal monitoring.
publishDate 2023
url http://eprints.utm.my/107311/
http://dx.doi.org/10.1063/5.0154235
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score 13.211869