Volume 8, Issue 4 (12-2018)
J Health Saf Work 2018, 8(4): 397-408 |
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Golbabaei F, Omidvar M, Nirumand F. Risk assessment of heat stress using the AHP and TOPSIS methods in fuzzy environment- A case study in a foundry shop. J Health Saf Work 2018; 8 (4) :397-408
URL: http://jhsw.tums.ac.ir/article-1-5962-en.html
URL: http://jhsw.tums.ac.ir/article-1-5962-en.html
1- Department of Occupational Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
2- Assistant Professor, Bushehr University of Medical Sciences, Bushehr, Iran , m.omidvar@bpums.ac.ir
3- B.Sc., University of Applied Science and Technology, Tehran, Iran
2- Assistant Professor, Bushehr University of Medical Sciences, Bushehr, Iran , m.omidvar@bpums.ac.ir
3- B.Sc., University of Applied Science and Technology, Tehran, Iran
Abstract: (5349 Views)
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.
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.
Type of Study: Research |
Received: 2018/12/7 | Accepted: 2018/12/7 | Published: 2018/12/7
Received: 2018/12/7 | Accepted: 2018/12/7 | Published: 2018/12/7
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