A stochastic petri net-based approach for operational performance estimation of quay cranes
Reliability, availability, and maintainability (RAM) of quay cranes (QCs) are essential for an effective port operation. This study estimates operational RAM of QCs using the Stochastic Petri Net (SPN) modelling. Asset Performance Assessment (APA) was performed to conduct the study by a SPN model. B...
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my.utm.1066362024-07-11T03:11:20Z http://eprints.utm.my/106636/ A stochastic petri net-based approach for operational performance estimation of quay cranes Jalal, Mohd. Rajali Abd. Kader, Ab. Saman Abdul Hamid, Mohd. Foad Kang, Hooi Siang TJ Mechanical engineering and machinery Reliability, availability, and maintainability (RAM) of quay cranes (QCs) are essential for an effective port operation. This study estimates operational RAM of QCs using the Stochastic Petri Net (SPN) modelling. Asset Performance Assessment (APA) was performed to conduct the study by a SPN model. Based on the operation and maintenance data, probability distributions of Mean Time Between Failure (MTBF) and Mean Time to Repair (MTTR) is determined by Goodness of Fit Test of Anderson Darling. Subsequently, these distributions are applied in APA to determine the frequencies of failure/breakdowns, duration of downtimes, availability, and reliability with the assistance of the SPN model and Monte Carlo Simulation. The availability of the analysed QC is 0.97 or 97%. The results of this work are verified by the comparison with historical data. The outcomes of this paper contribute to reliability, availability, maintainability, and risk management of QCs. John Wiley and Sons Ltd 2023-07 Article PeerReviewed Jalal, Mohd. Rajali and Abd. Kader, Ab. Saman and Abdul Hamid, Mohd. Foad and Kang, Hooi Siang (2023) A stochastic petri net-based approach for operational performance estimation of quay cranes. Quality and Reliability Engineering International, 39 (5). pp. 1660-1680. ISSN 0748-8017 http://dx.doi.org/10.1002/qre.3272 DOI:10.1002/qre.3272 |
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TJ Mechanical engineering and machinery Jalal, Mohd. Rajali Abd. Kader, Ab. Saman Abdul Hamid, Mohd. Foad Kang, Hooi Siang A stochastic petri net-based approach for operational performance estimation of quay cranes |
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Reliability, availability, and maintainability (RAM) of quay cranes (QCs) are essential for an effective port operation. This study estimates operational RAM of QCs using the Stochastic Petri Net (SPN) modelling. Asset Performance Assessment (APA) was performed to conduct the study by a SPN model. Based on the operation and maintenance data, probability distributions of Mean Time Between Failure (MTBF) and Mean Time to Repair (MTTR) is determined by Goodness of Fit Test of Anderson Darling. Subsequently, these distributions are applied in APA to determine the frequencies of failure/breakdowns, duration of downtimes, availability, and reliability with the assistance of the SPN model and Monte Carlo Simulation. The availability of the analysed QC is 0.97 or 97%. The results of this work are verified by the comparison with historical data. The outcomes of this paper contribute to reliability, availability, maintainability, and risk management of QCs. |
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Article |
author |
Jalal, Mohd. Rajali Abd. Kader, Ab. Saman Abdul Hamid, Mohd. Foad Kang, Hooi Siang |
author_facet |
Jalal, Mohd. Rajali Abd. Kader, Ab. Saman Abdul Hamid, Mohd. Foad Kang, Hooi Siang |
author_sort |
Jalal, Mohd. Rajali |
title |
A stochastic petri net-based approach for operational performance estimation of quay cranes |
title_short |
A stochastic petri net-based approach for operational performance estimation of quay cranes |
title_full |
A stochastic petri net-based approach for operational performance estimation of quay cranes |
title_fullStr |
A stochastic petri net-based approach for operational performance estimation of quay cranes |
title_full_unstemmed |
A stochastic petri net-based approach for operational performance estimation of quay cranes |
title_sort |
stochastic petri net-based approach for operational performance estimation of quay cranes |
publisher |
John Wiley and Sons Ltd |
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2023 |
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http://eprints.utm.my/106636/ http://dx.doi.org/10.1002/qre.3272 |
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