Journal of Health and Safety at Work

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Introduction: Nowadays, using multi attribute decision making (MADM) techniques in HSE hazard rating have been widely increased. On the other hand, Analytical Network process (ANP) methods has a high flexibility and accuracy in decision ranking. Therefore, the combination of the two mentioned approaches can provide a more precise prioritization for HSE hazards. Using ANP techniques, in this research a method for accurate rating of HSE hazards in the construction procedure of combined cycle power plant was presented.

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Material and Method: In this study, first, the overall structure and components of ANP method were identified and the connections between its components were determined. Then, the determined structure and components were modeled, using super decision software. In the next stage, pair companions were performed between an criteria and sub-criteria with respect to HSE experts opinions, Finally, selected HSE hazards were prioritized and compared according to the presented ANP method and the common available method.

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Result: According to the results, common risk assessment method is not able to prioritized risk accurately. While the current method classified the ten main identified hazards in 4 general categories, the presented method in this study could prioritized then in 7 categories.

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Conclusion: The suggested ANP model could provide a more accurate prioritization for hazards in comparison with current methods because of considering five qualitative indices. This allows an optimal allocation of organizational resources for controlling hazards.

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Introduction: Hazard Identification, risk assessment and management have an important role in reducing potential risks in industrial settings. This research was done with the aim of identifying the hazard and evaluating HSE risks and providing a HSE management program for the Urea Unit of Shiraz Petrochemical Complex.
Method: Firstly, hazard identification and qualitative risk assessment was done using FMEA technique and risky units were identified. Then, main events were identified and analysed as inputs of the Bow-Tie method. By identifying the strength, weakness, opportunity and threat factors, ranking and weighting them using the ANP method and Super Decisions software, a SWOT matrix was prepared and HSE management strategies were extracted.
Findings: The results showed that chemical leakage, falling from height and slipping were the most important incidents, and defect of control equipment, lack of attention to instructions, non-compliance with safety principles and human error were causes of these events. Also, ranking of weaknesses, strengths, opportunities and threats were 0.58, 0.2, 0.16 and 0.05, respectively.
Conclusion: Organizational opportunities with a weight of 0.124 were 4.8% higher than threats with a weight of 0.076. This shows that the company had a good situation in terms of achieving its goals.

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Introduction: The main purpose of this study was to identify and evaluate environmental problems and their ranking and to determine the conceptual model of environmental impact assessment (EIA) in industrial parks. Accordingly.
Material and Methods: In this study, environmental infrastructure issues were classified into five sections. The decision-making trial and evaluation laboratory (DEMATEL) technique was also employed to establish the relationships between the criteria. Moreover, the analytic network process (ANP) was utilized to determine their weight.
Results: Examining the internal relationships between the variables correspondingly revealed that cultural and economic criteria were the most influential. On the other hand, the biological criterion was very effective. The ANP results also showed that the “low share of environmental investment” as an indicator was an economic criterion with a normal weight of 0.80, which was of utmost importance among the other defined cases.
Conclusion: It was concluded that the definition of conceptual models in EIA processes can make it possible to examine and analyze the criteria and indicators affecting evaluation processes.