Evaluation of Occupational Safety Risk in Underground Mining Using Fuzzy Bayesian Network

Yaşlı F., Bolat B.

International Conference on Intelligent and Fuzzy Systems, INFUS 2020, İstanbul, Turkey, 21 - 23 July 2020, vol.1197 AISC, pp.1363-1372 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 1197 AISC
  • Doi Number: 10.1007/978-3-030-51156-2_159
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.1363-1372
  • Keywords: Fuzzy Bayesian Network, Occupational safety, Risk analysis, Underground mining
  • Anadolu University Affiliated: Yes


© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.Underground mining includes multi processes that are performed in labor-intensive way. This study analyses the occupational safety issues surrounding these processes using a fuzzy set approach and Bayesian Network. In order to reduce safety risk, it is necessary to specify, investigate, and measure the risk comprehensively. In the absence of recorded data about the events, fault tree approach has played an effective role to reveal the causes of the events and Fuzzy Bayesian Network provides a causative and probabilistic approach for the events with their importance. The analysis is performed on 13 undesired events that stemmed from equipment injury to explosion occurred during the processes of the mining. Results show that the main factors of occupational safety are not employee error, on the contrary, the managerial approach to the education, planning, and inspection related to occupational health and safety. We believe that this study could be helpful for evaluating the safety risk of the multi-process systems comprehensively and proposing strategic planning for mitigating the risks.