Neural network prognostics Model for Industrial Equipment Maintenance
This paper presents a new prognostics model based on neural network technique for supporting industrial maintenance decision. In this study, the probabilities of failure based on the real condition equipment are initially calculated by using logistic regression method. The failure probabilities ar...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/259/ http://eprints.utem.edu.my/id/eprint/259/1/HIS_P232.pdf |
| _version_ | 1848886915145662464 |
|---|---|
| author | Asmai, Siti Azirah Abd. Samad, Hasan Basari Shibghatullah, Abdul Samad Ibrahim Hussin, B. |
| author_facet | Asmai, Siti Azirah Abd. Samad, Hasan Basari Shibghatullah, Abdul Samad Ibrahim Hussin, B. |
| author_sort | Asmai, Siti Azirah |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | This paper presents a new prognostics model based
on neural network technique for supporting industrial
maintenance decision. In this study, the probabilities of failure based on the real condition equipment are initially calculated by using logistic regression method. The failure probabilities are subsequently utilized as input for prognostics model to predict the future value of failure condition and then used to estimate remaining useful lifetime of equipment. By having a time series of predicted failure probability, the failure distribution can be generated and used in the maintenance cost model to decide the optimal time to do maintenance. The proposed prognostic model is implemented in the industrial equipment known as autoclave burner. The result from the model reveals that it can give prior warnings and indication to the maintenance department to take an appropriate decision instead of dealing with the failures while the autoclave burner
is still operating. This significant contribution provides new insights into the maintenance strategy which enables the use of existing condition data from industrial equipment and prognostics approach. |
| first_indexed | 2025-11-15T19:46:04Z |
| format | Conference or Workshop Item |
| id | utem-259 |
| institution | Universiti Teknikal Malaysia Melaka |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T19:46:04Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utem-2592023-06-06T16:30:50Z http://eprints.utem.edu.my/id/eprint/259/ Neural network prognostics Model for Industrial Equipment Maintenance Asmai, Siti Azirah Abd. Samad, Hasan Basari Shibghatullah, Abdul Samad Ibrahim Hussin, B. Q Science (General) This paper presents a new prognostics model based on neural network technique for supporting industrial maintenance decision. In this study, the probabilities of failure based on the real condition equipment are initially calculated by using logistic regression method. The failure probabilities are subsequently utilized as input for prognostics model to predict the future value of failure condition and then used to estimate remaining useful lifetime of equipment. By having a time series of predicted failure probability, the failure distribution can be generated and used in the maintenance cost model to decide the optimal time to do maintenance. The proposed prognostic model is implemented in the industrial equipment known as autoclave burner. The result from the model reveals that it can give prior warnings and indication to the maintenance department to take an appropriate decision instead of dealing with the failures while the autoclave burner is still operating. This significant contribution provides new insights into the maintenance strategy which enables the use of existing condition data from industrial equipment and prognostics approach. 2011 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/259/1/HIS_P232.pdf Asmai, Siti Azirah and Abd. Samad, Hasan Basari and Shibghatullah, Abdul Samad and Ibrahim and Hussin, B. (2011) Neural network prognostics Model for Industrial Equipment Maintenance. In: 11th International Conference on Hybrid Intelligent Systems (HIS), 5 - 8 December 2011 , Melaka, Malaysia. |
| spellingShingle | Q Science (General) Asmai, Siti Azirah Abd. Samad, Hasan Basari Shibghatullah, Abdul Samad Ibrahim Hussin, B. Neural network prognostics Model for Industrial Equipment Maintenance |
| title | Neural network prognostics Model for Industrial Equipment Maintenance |
| title_full | Neural network prognostics Model for Industrial Equipment Maintenance |
| title_fullStr | Neural network prognostics Model for Industrial Equipment Maintenance |
| title_full_unstemmed | Neural network prognostics Model for Industrial Equipment Maintenance |
| title_short | Neural network prognostics Model for Industrial Equipment Maintenance |
| title_sort | neural network prognostics model for industrial equipment maintenance |
| topic | Q Science (General) |
| url | http://eprints.utem.edu.my/id/eprint/259/ http://eprints.utem.edu.my/id/eprint/259/1/HIS_P232.pdf |