ArticleHeliyon2023
Development of a novel Electrical Industry Safety Risk Index (EISRI) in the electricity power distribution industry based on fuzzy analytic hierarchy process (FAHP).
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 26 citations in OpenAlex.
- A hybrid intelligent model that performs product evaluation via semantic mining and optimized decision processing.Scientific reports · 2026Article
- An integrated hybrid HAZOP and fuzzy analytic hierarchy process framework for enhanced safety risk prioritization in process industries.Scientific reports · 2026Article
- Development and empirical validation of a multi-criteria decision-making model for the assessment of noise-induced hearing loss (NIHL) in high-exposure industrial settings.BMC public health · 2026Article
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- Introducing FMEA plus method for comprehensive safety risk assessment in the steel industry.PloS one · 2025Article
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- Why is the risk of industrial non-routine activities high and how can it be evaluated? An integrated approach.Heliyon · 2024Article
- Process accident prediction using Bayesian network based on IT2Fs and Z-number: A case study of spherical tanks.PloS one · 2024Article
- Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment.Heliyon · 2023Article
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Authors and funding
9 authors at 7 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
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.
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