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Classification of occupational safety risks with entropy-based TOPSIS-Sort

Year 2023, , 1550 - 1563, 30.06.2023

Esra Duygu Durmaz , İlker Gölcük

https://doi.org/10.56554/jtom.1258801
Cited By: 2

Abstract

The construction sector is one of the sectors with the highest risk in terms of occupational health and safety due to the frequency of occupational accidents and the weight of their consequences. For this reason, it is of great importance for the enterprises in the sector to regularly review the risk factors and take the necessary precautions. In this study, an integrated risk assessment approach is proposed in order to categorize risks and take effective measures. With the proposed method, 32 risks determined in a construction company were evaluated according to severity, occurence and detectability criteria. Group decision making approach was used and the evaluations of three decision makers were combined. The importance degrees of three risk factors were obtained by the entropy weighting method. Using the TOPSIS-Sort B method, risks were assigned to three predetermined risk clusters. When the results were examined, it was seen that 11 risks were assigned to the high risk cluster, 10 risks to the medium risk cluster and 11 risks to the low risk cluster.

Keywords

OHS risk assessment TOPSIS-Sort Entropy weighting

References

  • Adem, A. (2022). İş sağlığı ve güvenliğinde kullanılan risk analizi tekniklerinin değerlendirilmesi için bir rehber önerisi. Politeknik Dergisi, 25(3), 1319-1328. doi:https://doi.org/10.2339/politeknik.1114897
  • Adem, A., Colak, A., & Dagdeviren, M. (2018). An integrated model using SWOT analysis and Hesitant fuzzy linguistic term set for evaluation occupational safety risks in life cycle of wind turbine. Safety Science, 106, 184-190. doi:https://doi.org/10.1016/j.ssci.2018.02.033
  • Chen, C. Y., Wu, G. S., Chuang, K. J., & Ma, C. M. (2009). A comparative analysis of the factors affecting the implementation of occupational health and safety management systems in the printed circuit board industry in Taiwan. Journal of Loss Prevention in the Process Industries, 22(2), 210-215. doi:https://doi.org/10.1016/j.jlp.2009.01.004
  • Chen, Z., Feng, K. M., Zhang, G. S., Yuan, T., & Pan, C. H. (2008). Preliminary safety research for CH HCSB TBM based on FMEA method. Fusion Engineering and Design, 83(5), 743-746. doi:https://doi.org/10.1016/j.fusengdes.2008.05.046
  • de Lima Silva, D. F., & de Almeida Filho, A. T. (2020). Sorting with TOPSIS through boundary and characteristic profiles. Computers & Industrial Engineering, 141, 106328. doi:https://doi.org/10.1016/j.cie.2020.106328
  • Deng, H., Yeh, C.-H., & Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963-973. doi:https://doi.org/10.1016/S0305-0548(99)00069-6
  • Djapan, M. J., Tadic, D. P., MacUzic, I. D., & Dragojovic, P. D. (2015). A new fuzzy model for determining risk level on the workplaces in manufacturing small and medium enterprises. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 229(5), 456-468. doi:https://doi.org/10.1177/1748006X15581219
  • Ersoy, M., Çelik, M. Y., Yeşilkaya, L., & Çolak, O. (2019). Combination of Fine-Kinney and GRA methods to solve occupational health and safety problems. Journal of the Faculty of Engineering and Architecture of Gazi University, 34(2), 751-770. doi:https://doi.org/10.17341/gazimmfd.416534
  • Feili, H. R., Akar, N., Lotfizadeh, H., Bairampour, M., & Nasiri, S. (2013). Risk analysis of geothermal power plants using Failure Modes and Effects Analysis (FMEA) technique. Energy Conversion and Management, 72, 69-76. doi:https://doi.org/10.1016/j.enconman.2012.10.027
  • Gölcük, İ., & Durmaz, E. D. (2023). An integrated decision-making model with entropy weighting and TOPSIS-Sort for occupational risk assessment. 6. International Conference on Engineering Sciences Abstract Book, 56, Ankara, Türkiye.
  • Gölcük, İ., Durmaz, E. D., & Şahin, R. (2023). Prioritizing occupational safety risks with fuzzy FUCOM and fuzzy graph theory-matrix approach. Journal of the Faculty of Engineering and Architecture of Gazi University, 38(1), 57-70. doi:https://doi.org/10.17341/gazimmfd.970514
  • Grassi, A., Gamberini, R., Mora, C., & Rimini, B. (2009). A fuzzy multi-attribute model for risk evaluation in workplaces. Safety Science, 47(5), 707-716. doi:https://doi.org/10.1016/j.ssci.2008.10.002
  • Gul, M. (2018). A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions. Human and Ecological Risk Assessment, 24(7), 1723-1760. doi:https://doi.org/10.1080/10807039.2018.1424531
  • Gül, M. (2021). A quantitative occupational risk assessment methodology based on TOPSIS-Sort with its application in aluminum extrusion industry. International Journal of Pure and Applied Sciences, 7(1), 163-172.
  • Gul, M., Ak, M. F., & Guneri, A. F. (2017). Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi-criteria approach. Human and Ecological Risk Assessment, 23(2), 187-202. doi:https://doi.org/10.1080/10807039.2016.1234363
  • Hwang, C.-L., & Yoon, K. (1981). Methods for multiple attribute decision making. Multiple attribute decision making: methods and applications a state-of-the-art survey, 58-191.
  • John, A., Paraskevadakis, D., Bury, A., Yang, Z., Riahi, R., & Wang, J. (2014). An integrated fuzzy risk assessment for seaport operations. Safety Science, 68, 180-194. doi:https://doi.org/10.1016/j.ssci.2014.04.001
  • Korkusuz, A. Y., & Inan, U. H. (2020). Occupational health and safety performance measurement in healthcare sector using integrated multi criteria decision making methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(1), 81-96. doi:https://doi.org/10.17341/gazimmfd.441032
  • Liu, H. T., & Tsai, Y. L. (2012). A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety Science, 50(4), 1067-1078. doi:https://doi.org/10.1016/j.ssci.2011.11.021
  • Mahdevari, S., Shahriar, K., & Esfahanipour, A. (2014). Human health and safety risks management in underground coal mines using fuzzy TOPSIS. Science of the Total Environment, 488-489(1), 85-99. doi:https://doi.org/10.1016/j.scitotenv.2014.04.076
  • Makin, A.-M., & Winder, C. (2008). A new conceptual framework to improve the application of occupational health and safety management systems. Safety Science, 46(6), 935-948. doi:https://doi.org/10.1016/j.ssci.2007.11.011
  • Mizrak Özfirat, P. (2014). A new risk analysis methodology integrating fuzzy prioritization method and failure modes and effects analysis. Journal of the Faculty of Engineering and Architecture of Gazi University, 29(4), 755-768. doi:https://doi.org/10.17341/gummfd.04423
  • Sabokbar, F. H., Hosseini, A., Banaitis, A., & Banaitiene, N. (2016). A novel sorting method TOPSIS-SORT: an applicaiton for Tehran environmental quality evaluation. E & M Ekonomie a Management, 19 (2) (2016), 87-104, doi:https://doi.org/10.15240/tul/001/2016-2-006
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423. doi:https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  • Sousa, V., Almeida, N. M., & Dias, L. A. (2015). Risk-based management of occupational safety and health in the construction industry - Part 2: Quantitative model. Safety Science, 74, 184-194. doi:https://doi.org/10.1016/j.ssci.2015.01.003
  • Wang, T.-C., & Lee, H.-D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980-8985. doi:https://doi.org/10.1016/j.eswa.2008.11.035
  • Yilmaz, N., & Senol, M. B. (2017). A model and application of occupational health and safety risk assessment. Journal of the Faculty of Engineering and Architecture of Gazi University, 32(1), 77-87. doi:https://doi.org/10.17341/gazimmfd.300597

Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması

Year 2023, , 1550 - 1563, 30.06.2023

Esra Duygu Durmaz , İlker Gölcük

https://doi.org/10.56554/jtom.1258801
Cited By: 2

Abstract

İnşaat sektörü, iş kazalarının yaşanma sıklığı ve sonuçlarının ağırlığı sebebiyle iş sağlığı ve güvenliği açısından en yüksek riske sahip sektörlerden birisidir. Bu nedenle sektörde yer alan işletmelerin risk faktörlerini düzenli olarak gözden geçirerek gerekli önlemleri alması büyük önem taşımaktadır. Bu çalışmada, risklerin kategorize edilerek, etkin önlemlerin alınabilmesi amacıyla bütünleşik bir risk değerlendirme yaklaşımı önerilmiştir. Önerilen yöntem ile bir inşaat firmasında belirlenen 32 adet risk, şiddet, olasılık ve fark edilebilirlik kriterlerine göre değerlendirilmiştir. Çalışmada grup karar verme yaklaşımı kullanılmış ve üç farklı karar vericinin değerlendirmeleri birleştirilmiştir. Belirlenen üç risk faktörünün önem dereceleri entropi ağırlıklandırma yöntemiyle elde edilmiştir. TOPSIS-Sort B yöntemi kullanılarak riskler, önceden belirlenmiş üç risk sınıfına atanmıştır. Sonuçlar incelendiğinde, 11 riskin yüksek risk sınıfına, 10 riskin orta risk sınıfına ve 11 riskin düşük risk sınıfına atandığı görülmüştür.

Keywords

İSG risk değerlendirme TOPSIS-Sort Entropi ağırlıklandırma

References

  • Adem, A. (2022). İş sağlığı ve güvenliğinde kullanılan risk analizi tekniklerinin değerlendirilmesi için bir rehber önerisi. Politeknik Dergisi, 25(3), 1319-1328. doi:https://doi.org/10.2339/politeknik.1114897
  • Adem, A., Colak, A., & Dagdeviren, M. (2018). An integrated model using SWOT analysis and Hesitant fuzzy linguistic term set for evaluation occupational safety risks in life cycle of wind turbine. Safety Science, 106, 184-190. doi:https://doi.org/10.1016/j.ssci.2018.02.033
  • Chen, C. Y., Wu, G. S., Chuang, K. J., & Ma, C. M. (2009). A comparative analysis of the factors affecting the implementation of occupational health and safety management systems in the printed circuit board industry in Taiwan. Journal of Loss Prevention in the Process Industries, 22(2), 210-215. doi:https://doi.org/10.1016/j.jlp.2009.01.004
  • Chen, Z., Feng, K. M., Zhang, G. S., Yuan, T., & Pan, C. H. (2008). Preliminary safety research for CH HCSB TBM based on FMEA method. Fusion Engineering and Design, 83(5), 743-746. doi:https://doi.org/10.1016/j.fusengdes.2008.05.046
  • de Lima Silva, D. F., & de Almeida Filho, A. T. (2020). Sorting with TOPSIS through boundary and characteristic profiles. Computers & Industrial Engineering, 141, 106328. doi:https://doi.org/10.1016/j.cie.2020.106328
  • Deng, H., Yeh, C.-H., & Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963-973. doi:https://doi.org/10.1016/S0305-0548(99)00069-6
  • Djapan, M. J., Tadic, D. P., MacUzic, I. D., & Dragojovic, P. D. (2015). A new fuzzy model for determining risk level on the workplaces in manufacturing small and medium enterprises. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 229(5), 456-468. doi:https://doi.org/10.1177/1748006X15581219
  • Ersoy, M., Çelik, M. Y., Yeşilkaya, L., & Çolak, O. (2019). Combination of Fine-Kinney and GRA methods to solve occupational health and safety problems. Journal of the Faculty of Engineering and Architecture of Gazi University, 34(2), 751-770. doi:https://doi.org/10.17341/gazimmfd.416534
  • Feili, H. R., Akar, N., Lotfizadeh, H., Bairampour, M., & Nasiri, S. (2013). Risk analysis of geothermal power plants using Failure Modes and Effects Analysis (FMEA) technique. Energy Conversion and Management, 72, 69-76. doi:https://doi.org/10.1016/j.enconman.2012.10.027
  • Gölcük, İ., & Durmaz, E. D. (2023). An integrated decision-making model with entropy weighting and TOPSIS-Sort for occupational risk assessment. 6. International Conference on Engineering Sciences Abstract Book, 56, Ankara, Türkiye.
  • Gölcük, İ., Durmaz, E. D., & Şahin, R. (2023). Prioritizing occupational safety risks with fuzzy FUCOM and fuzzy graph theory-matrix approach. Journal of the Faculty of Engineering and Architecture of Gazi University, 38(1), 57-70. doi:https://doi.org/10.17341/gazimmfd.970514
  • Grassi, A., Gamberini, R., Mora, C., & Rimini, B. (2009). A fuzzy multi-attribute model for risk evaluation in workplaces. Safety Science, 47(5), 707-716. doi:https://doi.org/10.1016/j.ssci.2008.10.002
  • Gul, M. (2018). A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions. Human and Ecological Risk Assessment, 24(7), 1723-1760. doi:https://doi.org/10.1080/10807039.2018.1424531
  • Gül, M. (2021). A quantitative occupational risk assessment methodology based on TOPSIS-Sort with its application in aluminum extrusion industry. International Journal of Pure and Applied Sciences, 7(1), 163-172.
  • Gul, M., Ak, M. F., & Guneri, A. F. (2017). Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi-criteria approach. Human and Ecological Risk Assessment, 23(2), 187-202. doi:https://doi.org/10.1080/10807039.2016.1234363
  • Hwang, C.-L., & Yoon, K. (1981). Methods for multiple attribute decision making. Multiple attribute decision making: methods and applications a state-of-the-art survey, 58-191.
  • John, A., Paraskevadakis, D., Bury, A., Yang, Z., Riahi, R., & Wang, J. (2014). An integrated fuzzy risk assessment for seaport operations. Safety Science, 68, 180-194. doi:https://doi.org/10.1016/j.ssci.2014.04.001
  • Korkusuz, A. Y., & Inan, U. H. (2020). Occupational health and safety performance measurement in healthcare sector using integrated multi criteria decision making methods. Journal of the Faculty of Engineering and Architecture of Gazi University, 35(1), 81-96. doi:https://doi.org/10.17341/gazimmfd.441032
  • Liu, H. T., & Tsai, Y. L. (2012). A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety Science, 50(4), 1067-1078. doi:https://doi.org/10.1016/j.ssci.2011.11.021
  • Mahdevari, S., Shahriar, K., & Esfahanipour, A. (2014). Human health and safety risks management in underground coal mines using fuzzy TOPSIS. Science of the Total Environment, 488-489(1), 85-99. doi:https://doi.org/10.1016/j.scitotenv.2014.04.076
  • Makin, A.-M., & Winder, C. (2008). A new conceptual framework to improve the application of occupational health and safety management systems. Safety Science, 46(6), 935-948. doi:https://doi.org/10.1016/j.ssci.2007.11.011
  • Mizrak Özfirat, P. (2014). A new risk analysis methodology integrating fuzzy prioritization method and failure modes and effects analysis. Journal of the Faculty of Engineering and Architecture of Gazi University, 29(4), 755-768. doi:https://doi.org/10.17341/gummfd.04423
  • Sabokbar, F. H., Hosseini, A., Banaitis, A., & Banaitiene, N. (2016). A novel sorting method TOPSIS-SORT: an applicaiton for Tehran environmental quality evaluation. E & M Ekonomie a Management, 19 (2) (2016), 87-104, doi:https://doi.org/10.15240/tul/001/2016-2-006
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423. doi:https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
  • Sousa, V., Almeida, N. M., & Dias, L. A. (2015). Risk-based management of occupational safety and health in the construction industry - Part 2: Quantitative model. Safety Science, 74, 184-194. doi:https://doi.org/10.1016/j.ssci.2015.01.003
  • Wang, T.-C., & Lee, H.-D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980-8985. doi:https://doi.org/10.1016/j.eswa.2008.11.035
  • Yilmaz, N., & Senol, M. B. (2017). A model and application of occupational health and safety risk assessment. Journal of the Faculty of Engineering and Architecture of Gazi University, 32(1), 77-87. doi:https://doi.org/10.17341/gazimmfd.300597
There are 27 citations in total.

Details

Primary Language Turkish
Subjects Industrial Engineering
Journal Section Research Article
Authors

Esra Duygu Durmaz 0000-0002-8882-333X

İlker Gölcük 0000-0002-8430-7952

Publication Date June 30, 2023
Submission Date March 2, 2023
Acceptance Date April 17, 2023
Published in Issue Year 2023

Cite

APA Durmaz, E. D., & Gölcük, İ. (2023). Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması. Journal of Turkish Operations Management, 7(1), 1550-1563. https://doi.org/10.56554/jtom.1258801
AMA Durmaz ED, Gölcük İ. Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması. JTOM. June 2023;7(1):1550-1563. doi:10.56554/jtom.1258801
Chicago Durmaz, Esra Duygu, and İlker Gölcük. “Entropi Tabanlı TOPSIS-Sort Ile Iş güvenliği Risklerinin sınıflandırılması”. Journal of Turkish Operations Management 7, no. 1 (June 2023): 1550-63. https://doi.org/10.56554/jtom.1258801.
EndNote Durmaz ED, Gölcük İ (June 1, 2023) Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması. Journal of Turkish Operations Management 7 1 1550–1563.
IEEE E. D. Durmaz and İ. Gölcük, “Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması”, JTOM, vol. 7, no. 1, pp. 1550–1563, 2023, doi: 10.56554/jtom.1258801.
ISNAD Durmaz, Esra Duygu - Gölcük, İlker. “Entropi Tabanlı TOPSIS-Sort Ile Iş güvenliği Risklerinin sınıflandırılması”. Journal of Turkish Operations Management 7/1 (June 2023), 1550-1563. https://doi.org/10.56554/jtom.1258801.
JAMA Durmaz ED, Gölcük İ. Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması. JTOM. 2023;7:1550–1563.
MLA Durmaz, Esra Duygu and İlker Gölcük. “Entropi Tabanlı TOPSIS-Sort Ile Iş güvenliği Risklerinin sınıflandırılması”. Journal of Turkish Operations Management, vol. 7, no. 1, 2023, pp. 1550-63, doi:10.56554/jtom.1258801.
Vancouver Durmaz ED, Gölcük İ. Entropi tabanlı TOPSIS-Sort ile iş güvenliği risklerinin sınıflandırılması. JTOM. 2023;7(1):1550-63.

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Alanya Akademik Bakış
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