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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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 |
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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. |
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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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1809136656231432192 |
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13.211869 |