Risk assessment with the fuzzy Fine-Kinney method in a business operating in the metal industry.

Abstract

Occupational risk assessment involves examining and ranking the risks and hazards in a production or service facility, focusing on workplace health and safety. This study aims to address the deficiencies of traditional methods by applying a fuzzy logic approach to enhance occupational risk assessment in the metals sector. Unlike the Fine-Kinney method, the fuzzy model allows for intermediate values, reducing input uncertainties and yielding more realistic results. Probability, exposure and consequence serve as inputs, with the risk score as the output. The developed fuzzy Fine-Kinney model was tested for 252 situations and compared to the traditional Fine-Kinney method. Consistent outputs were found when using intermediate values, with risk score definitions in the fuzzy model aligning with those in Fine-Kinney. The fuzzy logic approach demonstrates an improvement in evaluating hazards by providing a more nuanced and accurate risk assessment, thereby contributing to better workplace safety management.