Predictive Modeling of Occupational Safety Risks Associated with Railway Workers Using Hybrid Fuzzy Modeling Approach

Abstract Diagnosis, reporting and proper analysis of occupational diseases among railway workers and crew remain unsatisfactory so far. This paper focus on utilizing the concepts of human factors and ergonomics (HFE) for improving the quality of care provided to railway workers, in particular, railway transportation crews. The high level of morbidity in this category of workers makes it important to search for new methods and innovative approach for improve the quality of decision-making related to the risks of the development of occupational diseases in railway crews. The paper aims to develop a method for the prediction and diagnoses of occupational diseases of railway crew workers, this will allow gathering decision rules necessary for improving the quality of medical care provided to crew and preventive strategies based on best practices. The decision rules obtained in the work take into account various risk factors associated with the design and working conditions in the cab of a locomotive in combination with other factors that may increase the risk of the occurrence and development of occupational diseases for workers of locomotive crews that is caused by poor or inappropriate working conditions. The authors investigated the various risks causing occupational diseases, and extrapolate the relationships revealed to railway workers in order to forecast high risk of occupational diseases among railway crew.