Investigation reveals that a high percentage of incident causes are ascribed to some forms of human error. To effectively prevent incidents from happening, Human Reliability Analysis (HRA), as a structured way to represent unintentional operator contribution to system reliability, is a critical issue. Human Error Reduction and Assessment Technique (HEART) as a famous HRA technique, provides a straightforward method to estimate probabilities of human error based on the analysis of tasks. However, it faces varying levels of uncertainty in assigning of weights to each error producing condition (EPC), denoted as assessed proportion of affect (APOA), by experts. To overcome this limitation and consider the confidence level (reliability or credibility) of the experts, the current study aimed at proposing a composite HEART methodology for human error probability (HEP) assessment, which integrates HEART and Z-numbers short for, Z-HEART. The applicability and effectiveness of the Z-HEART has been illustrated in the de-energization power line as a case study. Furthermore, a sensitivity analysis is fulfilled to investigate the validity of the proposed methodology. It can be concluded that Z-HEART is feasible for assessing human error, and despite the methodological contributions, it offers many advantages for electricity distribution companies.

Exposure to extremely low frequency magnetic fields (ELF-MF) and electric shocks occurs in many workplaces and occupations but it is unclear whether any of these exposures cause Amyotrophic lateral sclerosis (ALS). The aim of this systematic review and meta-analysis is to explore whether occupational exposure to ELF-MF and/or electric shocks are risk factor for ALS. We searched PubMed, Embase, and Web of Science databases up to the end of 2019. Pooled risk estimates were calculated using random-effects meta-analysis including exploration of the sources of heterogeneity between studies and publication bias. Twenty-seven publications fulfilled the inclusion criteria. We found a weak, significant, association between occupational exposure to ELF-MF and the risk of ALS (RRPooled estimate: 1.20; 95%CI: 1.05, 1.38) with moderate to high heterogeneity (I2=66.3%) and indication of publication bias (PEgger’s test=0.03). No association was observed between occupational exposure to electric shocks and risk of ALS (RRPooled estimate: 0.97; 95%CI: 0.80, 1.17) with high heterogeneity (I2=80.5%), and little indication for publication bias (PEgger’s test=0.24). The findings indicate that occupational exposure to ELF-MF, but not electric shocks, might be a risk factor for ALS. However, given the moderate to high heterogeneity and potential publication bias, the results should be interpreted with caution.

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