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Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system

Assets failure is widely considered as one of the main causes of major accidents in chemical industries such as fires, explosions, and toxic gas releases. Assets criticality analysis is vital to prevent such accidents. Risk-based maintenance (RBM) is among the most advanced comprehensive risk assessm...

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Main Authors: Jaderi, Fereshteh, Ibrahim, Zelina Zaiton, Zahiri, Mohammad Reza
Format: Article
Language:English
Published: Elsevier 2019
Online Access:http://psasir.upm.edu.my/id/eprint/81050/1/FUZZY.pdf
http://psasir.upm.edu.my/id/eprint/81050/
https://www.sciencedirect.com/science/article/pii/S0957582018304622
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spelling my.upm.eprints.810502020-10-14T05:57:31Z http://psasir.upm.edu.my/id/eprint/81050/ Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system Jaderi, Fereshteh Ibrahim, Zelina Zaiton Zahiri, Mohammad Reza Assets failure is widely considered as one of the main causes of major accidents in chemical industries such as fires, explosions, and toxic gas releases. Assets criticality analysis is vital to prevent such accidents. Risk-based maintenance (RBM) is among the most advanced comprehensive risk assessment methodologies for the criticality analysis of assets. The present study applies both traditional RBM and Fuzzy RBM (FRBM) methods for the risk analysis of petrochemical assets failure. Four consequence factors comprising operational impact, operational flexibility, maintenance cost, and impact on safety and environment are considered for the risk evaluation of assets failure. Moreover, frequency and risk factor scales are localized for both traditional RBM and Fuzzy RBM methods using an expert panel. The results of the case study show suitability of the FRBM model. Fuzzy numbers show that out of 107 assets, 10 are at the semi-critical level, and the remaining 97 are at the non-critical level. The highest fuzzy risk numbers were obtained for two blowers, where the assets failure value was 99.145. The criticality evaluation results show that the plant in the case study is at the semi-critical level. Given this, it is recommended that risk managers of the plant should customize and prioritise their maintenance planning according to the FRBM value for each asset failure. To this end, maintenance-related recommendations are offered to facilitate and assist decision-makers. Elsevier 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/81050/1/FUZZY.pdf Jaderi, Fereshteh and Ibrahim, Zelina Zaiton and Zahiri, Mohammad Reza (2019) Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system. Process Safety and Environmental Protection, 121. pp. 312-325. ISSN 0957-5820 https://www.sciencedirect.com/science/article/pii/S0957582018304622 10.1016/j.psep.2018.11.005
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Assets failure is widely considered as one of the main causes of major accidents in chemical industries such as fires, explosions, and toxic gas releases. Assets criticality analysis is vital to prevent such accidents. Risk-based maintenance (RBM) is among the most advanced comprehensive risk assessment methodologies for the criticality analysis of assets. The present study applies both traditional RBM and Fuzzy RBM (FRBM) methods for the risk analysis of petrochemical assets failure. Four consequence factors comprising operational impact, operational flexibility, maintenance cost, and impact on safety and environment are considered for the risk evaluation of assets failure. Moreover, frequency and risk factor scales are localized for both traditional RBM and Fuzzy RBM methods using an expert panel. The results of the case study show suitability of the FRBM model. Fuzzy numbers show that out of 107 assets, 10 are at the semi-critical level, and the remaining 97 are at the non-critical level. The highest fuzzy risk numbers were obtained for two blowers, where the assets failure value was 99.145. The criticality evaluation results show that the plant in the case study is at the semi-critical level. Given this, it is recommended that risk managers of the plant should customize and prioritise their maintenance planning according to the FRBM value for each asset failure. To this end, maintenance-related recommendations are offered to facilitate and assist decision-makers.
format Article
author Jaderi, Fereshteh
Ibrahim, Zelina Zaiton
Zahiri, Mohammad Reza
spellingShingle Jaderi, Fereshteh
Ibrahim, Zelina Zaiton
Zahiri, Mohammad Reza
Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
author_facet Jaderi, Fereshteh
Ibrahim, Zelina Zaiton
Zahiri, Mohammad Reza
author_sort Jaderi, Fereshteh
title Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
title_short Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
title_full Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
title_fullStr Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
title_full_unstemmed Criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
title_sort criticality analysis of petrochemical assets using risk based maintenance and the fuzzy inference system
publisher Elsevier
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/81050/1/FUZZY.pdf
http://psasir.upm.edu.my/id/eprint/81050/
https://www.sciencedirect.com/science/article/pii/S0957582018304622
_version_ 1681490843681161216
score 13.211869

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