Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis Integrated with Markov Chain and Fuzzy Bayesian Networks
Author(s) -
Heidar Mohammadi,
Zohreh Fazli,
Hiro Kaleh,
Hamid Reza Azimi,
Saber Moradi Hanifi,
Nasrin Shafiee
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/6530541
Subject(s) - fault tree analysis , reliability engineering , markov chain , event tree , reliability (semiconductor) , event tree analysis , overhead (engineering) , bayesian network , fuzzy logic , engineering , event (particle physics) , markov model , ladle , fault (geology) , computer science , machine learning , artificial intelligence , mechanical engineering , power (physics) , physics , electrical engineering , quantum mechanics , seismology , geology
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.
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