Prediction and Analysis of Human Errors in Operators of Control Rooms at 400 kV Posts and the Effectiveness of the Proposed Measures

Background and Aims: Human being as the designer, programmer, and operator of systems, equipment and machineries plays a significant role in their safety at present time. In a sophisticated system, the operators’ behavior has the potential of errors that can influence the capability of the system. In the present study, human errors of 400 kV posts were identified, analyzed and their reduction due to the application of proposed control measures were predicted. Methods: After identification of key jobs affective on electric industry’s stability, the operator of 400 kV posts was selected as the sensitive and key joband analyzed using Hierarchical Task Analysis (HTA). The operator’s probable errors and their reduction were predicted using Systematic Human Error Reduction and Prediction (SHERPA). Results: The results revealed that in 107 predicted errors at 6 main tasks and 61 sub tasks of 400 kV posts, the most frequent type of error was action error and the maximum predicted error was related to maneuvering task. The results also showed that about 95% of identified risks from errors were at unacceptable and undesirable level. It was predicted that if the recommended control measures were applied the unacceptable and undesirable risks would be reduced to 0 and 7.5% respectively. Conclusion: It is possible to predict, identify and reduce the human errors in control rooms using SHERPA