Repository of Research and Investigative Information

Repository of Research and Investigative Information

Larestan University of Medical Sciences

Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis Integrated with Markov Chain and Fuzzy Bayesian Networks

(2021) Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis Integrated with Markov Chain and Fuzzy Bayesian Networks. Mathematical Problems in Engineering. p. 17. ISSN 1024-123X

[img]
Preview
Text
Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis.pdf

Download (2MB) | Preview

Official URL: http://apps.webofknowledge.com/InboundService.do?F...

Abstract

Establishing an adequate level of reliability in the overhead crane operations is an important and vital principle to avoid undesirable consequences. To do this, it is appropriate to have a comprehensive approach for risk and reliability assessment of the most probable failure scenarios during overhead crane operations. In this study, fault tree analysis (FTA) in combination with fuzzy set theory, Bayesian network (BN), and Markov chain was used to evaluate the probability of top event and reliability of overhead cranes. A total of 47 basic events were identified for ladle fall in overhead cranes. The results showed that the probability of the ladle fall in the FT approach is equal to 0.0523035 and in the BN approach in the prior event is equal to 0.0273394 which is less than the FT method. Based on the values predicted by Markov chain, the reliability of the system decreases over time by 67.9 after 60 months. This study showed that the plan for ladle fall prevention should consider all influencing parameters identified by proper risk assessment methodologies.

Item Type: Article
Keywords: process systems oil model ahp fta Engineering Mathematics
Divisions: Education Vice-Chancellor Department > Faculty of Health > Department of Occupational Health
Page Range: p. 17
Journal or Publication Title: Mathematical Problems in Engineering
Journal Index: ISI
Volume: 2021
Identification Number: https://doi.org/10.1155/2021/6530541
ISSN: 1024-123X
Depositing User: مهندس مهدی شریفی
URI: http://eprints.larums.ac.ir/id/eprint/412

Actions (login required)

View Item View Item