Estimation of human error rate in underground coal mines through retrospective analysis of mining accident reports and some error reduction strategies

Human error is one of the leading causes of workplace accidents and a pressing threat to system safety. The management and control of human errors need their identification in the system activities and prioritisation of errors. Knowledge of error rates or probabilities is essential for their prioritisation and is a prerequisite for designing control measures of human error to enhance system safety. Traditional approaches estimate the human error rate based on experts' opinion, which suffers from the inherent uncertainty of human judgments. This research proposes a methodology for estimation of human error rate from a retrospective analysis of accident reports using fuzzy mathematical concepts. The proposed approach uses accident reports of underground coal mines for assessing the human error rates of essential mining activities, identifying the critical activities and error types. It also suggests some error reduction strategies for devising an intervention to accidents.