Journal of Health and Safety at Work

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Introduction: Electrical industries are among high risk industries. The present study aimed to assess safety risk in electricity distribution processes using  ET&BA technique and also to compare with both VIKOR & TOPSIS methods in fuzzy environments.
 

Material and Methods: The present research is a descriptive study and ET&BA worksheet is the main data collection tool. Both Fuzzy TOPSIS and Fuzzy VIKOR methods were used for the worksheet analysis.
 

Result: Findings revealed that overhead low and medium voltage power distribution networks had the highest risk among the other network types of transmission and distribution of electricity. Also, it was found that TOPSIS and VIKOR methods are appropriate to rank the safety risks with somehow similar results.
 

Conclusion: The height and electricity are of the main causes of accidents in electricity transmission and distribution industry which caused the overhead power networks to be ranked as high risk. Application of decision-making models in fuzzy environment minimizes the judgment of assessors in the risk assessment process.

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Introduction: Heat stress is one of the harmful risks in casting and die casting industries, which can not only cause work-related diseases but also can impair the performance and safety of workers. Since the indicators that are used to evaluate heat stress are very different, it is very difficult to choose a suitable index. The aim of this study was to determine the optimum heat stress index in foundry, die-cast, and road construction industries using FAHP and Topsis methods.

Material and Method: In order to determine optimum heat stress index in foundry, die-cast, and road construction industries, first, the prioritization criteria were defined by experts (including ease of measurement, measurement accuracy, comprehensiveness, time, cost, and correlation). Then, considering these criteria, the best heat stress index was determined based on experts’ opinions and using FAHP and Topsis methods.

Result: The results of this study suggest that given the current conditions and criteria, WBGT and P4SR is the best indices for foundry, die casting and construction.

Conclusion: The results showed that according to comprehensiveness, accuracy and correlation criteria, the WBGT index is considered as the best indicator of heat stress assessment in foundry, die-cast and road construction industries. Moreover, the HSI ranked in the last place due to the complexity and cost of its calculation.

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Introduction: Safety in construction needs not only operating the executive laws and instructions but also the safety culture of all the workers in workshops. Safety culture is a factor by which all the workers are committed to having a positive share in the safety of their coworkers and themselves. Therefore, the aim of this study is identification of safety culture factors and ranking occupations in jobsites in order to improve the safety condition and promote the safety culture of high-rise projects.

Material and Method: In this descriptive-analytical study, first, safety culture criteria in construction projects are identified by a literature review. Then, 8 factors of safety culture are weighted using fuzzy analytic hierarchy process. Finally, 10 different occupations in high-rise workshops are ranked from the point of view of safety culture using fuzzy TOPSIS method.  

Result: Results of ranking the criteria show that the most important criteria are safety attitude, supervision, policy of organization and safety training. Moreover, in high-rise construction the site superintendent and supervisor occupations have the highest and laborers have the lowest safety culture.

Conclusion: In this study, after evaluating different construction occupations by hybrid FTOPSIS-FAHP method, the results are compared with the results of previous researches. Here, it was found that the findings are consistent with previous studies. On the other hand, low level of safety culture of construction laborers among the investigated occupations shows weakness in safety training and attitude; hence, the factors such as more safety supervision and training must be considered in order to create a positive safety culture for the workers.

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Introduction: Resilience engineering is a novel approache to risk management and is the inherent ability of a system to adapt their work before, during and after the changes and adverse events in such a way that maintain the system performance under predictable and unpredictable conditions. The aim of this study was to identify indicators of organizational resilience of refineries and ranking them using fuzzy TOPSIS technique.  

Material and Method: A qualitative study was done to identify organizational resilience indicators of refinery complex. The main method of data collection was semi-structured interviews. Indicators were determined using qualitative content analysis and literature review. Weighting and ranking identified indicators was performed using fuzzy TOPSIS technique.   

Result: Eleven indicators were identified as follows: management commitment, performance management system, flow of information/communication, involvement culture, error management culture, education, preparedness, flexibility, innovation culture, change management, and human resource management.

Conclusion: Critical sociotechnical organizations especially refinery complexes in order to improve safety management and resilience situation should focus on effective indicators. Monitoring and improving them will increase safety and the resilience level of organization

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Introduction: Working in hot and harsh weather conditions can cause heat related diseases and in some cases, even can lead to death. Risk assessment of heat stress in these environments is of particular importance. As there are many factors that could affect the heat stress, therefore, an index should be applied that could properly reflect the effect of all of these factors.
Material and Method: Initially a five-member expert team was established. Then, the weight of each variable was determined by the fuzzy analytical hierarchy process (FAHP) method. In next step, five work stations of the casting process evaluated applying fuzzy TOPSIS (FTOPSIS) method and the risk of heat stress prioritized in these stations. Lastly, the Pearson’s correlation coefficient was used to determine correlation between the results of proposed method with WBGT index.
Result:  The weights of three main variables including task characteristics, working environment, and worker characteristics was determined as 0.279, 0.526, and 0.195. The risk priority of the five work stations including, stocking, melting furnace, pouring and casting, polishing, and warehousing was established as S1= 4, S2= 2, S3= 1, S4= 3, and S5= 5. The Pearson’s correlation coefficient between the similarity index (CCi) and WBGT was 0.97.
Conclusion: From three main variables that can affect the heat stress, “Working Environment” has main impact in the risk assessment process; therefore, the most efforts must be focused on controlling this variable. The proposed method in this study has the capability of concurrent quantitative and qualitative assessment of factors that could affect the heat stress and can minimize the uncertainties in the risk assessment process relying upon the fuzzy sets.

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Introduction: Skin disease caused by exposure to the chemicals is one of the major health-related problems in the workplaces. This study has done to prioritize the strategies for skin exposure with chemical in a painting company.
Material and Method: In this analytical cross-sectional study 7 criteria and 8 selection control methods were initially chosen by surveying the existing records and through the assessments of expert panel and checking the result of previous studies. Subsequently, control strategies were prioritized according to the criteria using Fuzzy Analytical Hierarchy process & Topsis.
Result: Results of the paired comparison showed that the safety of the control strategy (w=0.298) and it’s up to date (w=0.0138) were the most and least important criteria for skin control strategies. Among skin control strategies for chemical exposure, the highest and lowest importance were for training (w=0.817) and work-rest schedule (w=0.233), respectively.
Conclusion: In this study, training was determined as the best control strategies for skin chemical exposure in the studied painting company according to the investigated criteria. This decision-making process could be applied for promotion of the skin health among workers.

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Introduction: Failure Mode and Effects Analysis (FMEA) is a structured way to find and understand the states of a system’s failure and to calculate the resulting effects. In this method, which has been criticized by many researchers, the risk priority number is obtained for each failure mode based on the multiplication of the three parameters of occurrence (O), severity (S) and detection (D). In order to overcome the disadvantages of the traditional method of FMEA, such as ranking the failure and weighting the parameters, this research proposes a model in the fuzzy set.
Material and Methods: The model proposed in this paper is a nonlinear model for weighting the parameters of the FMEA and the revised TOPSIS method for ranking the failures, which is used for the first time to improve the FMEA method.
Results: The proposed model was presented in the Copper Complex of Shahr-e-Babak to assess safety risks. Based on the results of the study, it was found that in this proposed model, the weights of severity and detection were 0.479 and 0.186, respectively, and the results of the ranking showed that the risks of falling from height and getting stuck between objects had the highest and lowest priorities, respectively.
Conclusion: In the proposed model, based on Logarithmic Fuzzy Preference Programming and the revised TOPSIS method, the definite weights of the parameters were presented without any fuzzy number ranking and risk ranking with more criteria, respectively. Therefore, the proposed model has a higher ability compared to the traditional FMEA, and its application can be recommended to determine the ranking of risks.