A novel risk analysis approach for occupational safety using Bayesian Network and interval type-2 fuzzy sets: the case of underground mining

YAŞLI F., Bolat B.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, vol.42, no.1, pp.265-282, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 42 Issue: 1
  • Publication Date: 2022
  • Doi Number: 10.3233/jifs-219191
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.265-282
  • Keywords: Bayesian Network, interval type-2 fuzzy sets, occupational safety, risk analysis, underground mining, PROBABILITY ELICITATION, OPERATIONAL RISK, BELIEF NETWORK, TREE ANALYSIS, ACCIDENTS, SYSTEMS, MODEL, OIL, SELECTION
  • Anadolu University Affiliated: Yes


Occupational safety problems are no longer acceptable for any industrial environment. Lack of comprehensive and reliable evaluations for occupational safety causes many undesired events and harm to employees during the industrial process. In this study, it is aimed to develop an applicable risk analysis methodology for evaluating the undesired occupational events that occurred in the multi-process system where no historical accident records. The difficulty in obtaining and analyzing the data required for the determination of the occupational safety risks especially in the manually executed processes has been overcome with the Bayesian Network and interval type-2 fuzzy sets by using the expert judgments. While BN enables to development of a comprehensive reasoning approach about the occurrence of the events, interval type-2 fuzzy sets better represent the ambiguity in the judgments by covering the uncertainty in a wider mathematical range with less computational effort according to other fuzzy sets. During multi-processes in industrial activity, various occupational undesired events may occur, including rare events with very serious consequences or frequent events with very low severity consequences. To able to consider all kinds of events occurring in an industrial environment from a holistic risk perspective, a novel fuzzy scale for specifying the probability and consequence of the events are proposed by the interval type-2 fuzzy numbers. Therefore, all undesired events regardless the probability and consequence which may occur during the multi-processes in a system and the main root causes of these events can be observed within the proposed methodology. A case study is used to emphasize the effect of the proposed methodology for risk analysis of occupational safety in underground mining The results have indicated that occupational safety education is the most contributing factor to occurring the undesired occupational events in underground mining We believe that this study could help evaluate the safety risk of the multi-process systems comprehensively and holistically and proposing strategic planning for mitigating the occupational safety risks.