A Two-Dimensional Fuzzy Risk Assessment Model for Occupational Health and Safety Evaluations

In working life, the danger in the environment and the risks arising from it are of great importance for the health and safety of the employees. In order for these pre-determined damaging factors to be evaluated correctly, an evaluation method suitable for that field of activity should be selected. Since real case risk assessment problems include many uncertainties, the fuzzy set theory (FST) that has a huge ability to model uncertainty has found a wide application area thanks to its easy and convenient solution approach to the solution of difficult and complex problems today. FST can be used to eliminate the uncertainties in classical risk analyzes in workplaces and to introduce new methods by applying different combinations. Combinations prepared using various methods make positive contributions to occupational health and safety (OHS) risk assessment processes. These combinations prepared using various methods. In this paper, one of fuzzy set extensions named Z-number has been integrated with the proposed methodology to improve ability that is modelling uncertainties. It ensures that the inadequacies in the existing risk assessment methods are eliminated. For this aim a new framework has been suggested. In the proposed model that we will propose in our study, the risks arising from the danger will be analyzed by using Fine Kinney Method that is one of the most widely used methods in OHS risk analysis. Grading of risks in the Fine Kinney method is obtained by multiplying the probability of occurrence of the risks, the frequency of exposure to the hazard and the numerical values of the effect it creates. Additionally, the proposed methodology consists of three MCDM methods such as DEMATEL, AHP or ANP and TOPSIS methodology. The DEMATEL method will be used to establish causality between hazards. The method AHP or ANP will be used to determine risk weights and the TOPSIS method will be used to determine hazards in order of priority. The proposed framework is also being constructed on Z-numbers and thus a new risk assessment methodology based on MCDM, and Fine-Kinney Methods is suggested. It will be advantageous to use Z-numbers to clarify the uncertainties. to ensure that risk assessments are more objective and to make its applicability even more possible. The proposed framework can be applied in a real case risk assessment problem to analyze its results.