A Fuzzy Logic Approach in the Definition of Risk Acceptance Boundaries in Occupational Safety and Health

Organizations need to make decisions about risk acceptance, in order to decide about the need of risk-reducing measures. In this process, the personal judgments of Occupational Safety & Health (OSH) practitioners have a great importance. If on one hand they have the technical knowledge about risk, on the other hand the decisions can be dependent on their level of risk acceptance. This paper analyzes judgments of OSH practitioners about the level of risk acceptance, using Fuzzy logic approach. A questionnaire to analyze the reported level of risk acceptance was applied. The questionnaire included 79 risk scenarios, each accounted for the frequency of an accident with more lost workdays than a given magnitude. Through the two-step cluster analysis three groups of OSH practitioners were identified: Unacceptable, Tolerable and Realistic groups. A further analysis of the realistic group judgments about risk was performed, using the Fuzzy logic approach. The fuzzy sets of inputs and output variables were determined and the relationship between the variables was mapped through fuzzy rules. After that, the Min–Max fuzzy inference method was used. The obtained results show that the risk level is acceptable when input variables are at the lowest value and unacceptable when the risk level is high. The obtained results allow to better understand the modeling of OSH practitioners’ judgments about risk acceptance, being noted the uncertainty related to these judgments.