Abstract ▼ AI-Helper

Various surveys and compilations have led to the conclusion that human error is a primary cause of most major accidents in complex man-machine systems such as nuclear power plants, chemical plants, airlines, railways, etc. For this reason, a modern probabilistic risk assessment technique, originally...

Various surveys and compilations have led to the conclusion that human error is a primary cause of most major accidents in complex man-machine systems such as nuclear power plants, chemical plants, airlines, railways, etc. For this reason, a modern probabilistic risk assessment technique, originally dealing only with failures of hardware components, requires human reliability estimates in order to yield more realistic analysis. In spite of this demand, the human error data that can be used in human reliability field are scarce. In order to solve this problem, we propose a quantification method of human error events in man-machine systems. This method is based on the subjective judgment of human reliability analyst. In this method, the ratio estimates of subjective human error probabilities(HEPs) obtained from paired comparisons are converted to a best set of relative human error quotients; and this subjective ratio scale is then converted into an objectified scale of probability using a known objective empirical (anchor) probabilities. Finally, this method is applied to a practical problem. When dependable estimates of HEPs are unavailable, the pairwise ratio estimation procedure gives an excellent means of integrating many experts' judgments. Another difficulty in human reliability analysis(HRA) is that human behavior is affected by many factors, i.e., performance shaping factors(PSFs) such as noise, motive, information load, task load, etc. In order to solve this problem, we propose a modification model of the nominal HEP of a task element in a specific task situation. Nominal HEP is the probability of a given human error when the effects of PSFs (or task situation) have not been considered. The basic rationale of this method is that the likelihood of a human error depends on the combined effects of a relatively small set of PSFs. The quality scores of individual PSFs are used in conjunction with the relative importance weights of PSFs on a task to compute a composite quality score. Also, a new mapping rule of the composite quality score of PSFs into a situation-specific basic HEP is proposed with a numerical example. This method can be used effectively in situation-specific HRA using HRA technique such as the technique for human error rate prediction(THERP).

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