A new method for estimating human error probabilities: AHP-SLIM

Abstract Accidents in industrial settings are mainly a result of human errors (HEs); relevant fields that consider HEs have recently increased in number. For this reason, numerous methods to quantitatively estimate what is known as the HE probability (HEP) have been developed. However, it is difficult to obtain empirical data, which forces a heavy reliance on the judgment of experts in the field. During the process of judgments by experts, subjectivity plays an important role, causing difficulties in assuring consistency. To overcome this problem and to obtain a more accurate estimation, this study suggests a new and simple method. This method is referred to as AHP–SLIM, a type of HEP estimation using an analytic hierarchy process (AHP), which quantifies the subjective judgment and confirms the consistency of collected data. This new method also uses the process of expert judgment within the success likelihood index method (SLIM).

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