Development of a novel Electrical Industry Safety Risk Index (EISRI) in the electricity power distribution industry based on fuzzy analytic hierarchy process (FAHP).

Many workers are exposed to electrical energy during the fulfillment of their tasks. It is necessary to identify the potential risk factors for electrical damages. The present study aimed to develop a novel Electrical Industry Safety Risk Index (EISRI) in the electricity power distribution industry based on fuzzy analytic hierarchy process (FAHP). In this study several different safety risk assessment methods were analyzed. Then, common activities in the electricity distribution industry were classified into ten occupational groups. To identify the general structure of risk assessment and determine three main components, including personal, environmental, and organizational a three-stage Delphi study was conducted with the participation of 30 experts. The fuzzy analytic hierarchy process approach was used to weight the components and parameters in each job group. Finally, the results of the EISRI were compared with the failure mode and effect analysis (FMEA) method. The most effective component in determining the risk level was the personal component (PC), with a 0.537 weighted average. Cronbach's alpha values for each of the personal, environmental, and organizational components and the entire model were 0.90, 0.85, 0.82, and 0.86, respectively, and model reliability was confirmed. The results obtained from the EISRI method were compared with the FMEA method, the results of both methods were very close to each other (p < 0.05). The results of this study revealed that the highest weighted average was related to the personal component due to the high impact of the human factors in carrying out activities in various occupations. The EISRI can be applied as a substitute for general risk assessment methods due to the suitability of this method with the nature of activities in this industry. The present technique can be a practical step toward developing suitable risk management algorithm.

Application of a novel exposure limit approach for co-exposure of chemicals: a field study by in-vitro design.

This study has suggested an occupational exposure limit (OEL) based on the co-exposure approach in an iron-foundry industry. Respirable dust was collected in an iron casting industry using the NIOSH 0600 method. The DNA damage was obtained by comet assay. The lower confidence interval of the benchmark dose (BMDL) was employed for exposure limit evaluation. The estimated BMDL of the cell line was extrapolated to human subjects. Based on the Hill model, a BMDL 1.65 µg for chemical mixture has been estimated for the A549 cell line. According to uncertainty factors, permitted daily exposure (PDE) was predicted in humans. However, PDE of 3.9 µg/m3 was specified as the time-weighted average limit for toxic respirable dust in the casting industry. In this study, OEL for active respirable dust in the casting industry has been proposed. The industry-based standard for active respirable dust has been proposed for better management of co-exposure.