Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/2637
Title: Improved Z-number based fuzzy fault tree approach to analyze health and safety risks in surface mines
Authors: Jiskani, Izhar Mithal
Yaşlı, Fatma
Hosseini, Shahab
Rehman, Atta Ur
Uddin, Salah
Keywords: Fault tree
Mine health and safety
Mining industry
Risk analysis
Z-number
Occupational-Safety
Coal-Mines
Gas
Explosion
Accidents
Model
Probability
Reliability
Management
Injuries
Issue Date: 2022
Publisher: Elsevier Sci Ltd
Abstract: Surface mining is vulnerable and subject to a wide range of risks, requiring extensive risk analysis to ensure mine health and safety (MHS). Fault tree analysis (FTA) is a graphic representation tool for conducting safety and reliability analyses by modeling causal chains that lead to failures. However, conventional FTA cannot deal with uncertain and imprecise information. Therefore, in order to handle the uncertainty arising from lack of complete information and to enhance the reliability of qualitative judgment of experts, the concepts of Z-numbers and fuzzy theory are combined with FTA. The proposed approach used expert elicitation to comprehensively analyze MHS risks related to machine/equipment, environment, and workplace. Through causal inquiries of the FTA, 8 undesired events and 65 underlying basic events are explored and analyzed, taking into account the probability of occurrence of all basic events. Further, a sensitivity analysis is performed using Fussell-Vesely Importance and Risk Reduction Worth Methods to verify the model and examine how each of the basic events contributes to the occurrence of any undesirable incident. Results reveal that issues associated with blasting, dust, and explosive fumes are the most probable incidents to occur among the undesired events. The main basic events causing MHS risks result from non-implementation of regulations, staff incompetence, improper safety perimeter setting, and explosive calculations. This study assists practitioners in making risk management decisions and implementing corrective measures. The proposed approach can also be applied to investigate similar risk factors in different industries.
URI: https://doi.org/10.1016/j.resourpol.2022.102591
https://hdl.handle.net/20.500.13087/2637
ISSN: 0301-4207
1873-7641
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

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