Human factors risk assessment and management: Process safety in engineering

Abstract

Abstract Human factors are the primary factors leading to accidents. Therefore, managing human factors is an important way to prevent accidents. This paper aims to introduce a new method to assess and manage human factors. First, the accident causation model was improved based on Reason’s “Swiss-cheese” model, which was then combined with the Human Factor Analysis and Classification System (HFACS) to establish the human factors risk assessment model. The evaluation model includes 5 levels (organization influence, unsafe supervision, preconditions for unsafe acts, unsafe acts, and emergency influence) and 25 human factors. In the risk assessment process, the set pair analysis method was used to calculate the connection number and the partial connection number of each factor, level and whole system. The safety score and risk development interval were calculated by using the connection number, and the risk grade is determined. Thus, the dynamic quantitative evaluation of human risk is realized. By using the partial connection number, the risk development trend of each factor is predicted. Due to the lack of human managed enterprises, the safety status of people is approximately discrete. Therefore, this paper establishes the SPA–Markov chain risk prediction model to predict human risk. The verification results show that the prediction error is less than 2%. This indicates that the prediction model can be applied in practice. To reduce human risk, ABC analysis and the “S-O-R” model were used for human risk management. The application results show that this method has a significant effect on improving human safety factors. Finally, this paper summarizes 12 common unsafe factors and their effective safety “stimulus” measure, researching the accident path. According to the organizational level and individual level of human factors, different kinds of human factors management methods are suggested.