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A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort with its Application in Aluminum Extrusion Industry

Year 2021, Volume: 7 Issue: 1, 163 - 172, 30.06.2021
https://doi.org/10.29132/ijpas.943612

Abstract

The metal products industry, including the aluminum extrusion industry, is one of the sectors with high risk in terms of occupational health and safety (OHS). Considering this fact and the increasing trend of occupational accidents in the sector, the need to enhance occupational safety becomes clear. Therefore, this study proposes a quantitative occupational risk assessment by a sorting-based technique for order performance by similarity to ideal solution (TOPSIS-Sort) methodology to manage risks in the aluminum extrusion industry. The methodology has been demonstrated by evaluating 28 potential hazards under three risk parameters (probability, severity and frequency). The assessed hazards are divided into five risk clusters (Very high risk, High risk, Substantial risk, Possible risk, and Risk) and control measures that will initiate the reduction of risks have been determined. Results of the study show that while one hazard has been placed in the Very high risk cluster, 3 in the High risk cluster, 23 in the Substantial risk cluster and one in the Possible risk cluster.

References

  • Aneziris, O. N., Papazoglou, I. A., & Doudakmani, O. (2010). Assessment of occupational risks in an aluminium processing industry. International journal of industrial ergonomics, 40(3), 321-329.
  • Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with applications, 39(17), 13051-13069.
  • de Lima Silva, D. F., & de Almeida Filho, A. T. (2020). Sorting with TOPSIS through boundary and characteristic profiles. Computers & Industrial Engineering, 141, 106328.
  • Demir, L., Akpınar, M. E., Araz, C., & Ilgın, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487.
  • Demirci, K.M. (2013). Dünya alüminyum ticaretinde Türkiye’nin yeri. Metalurji Dergisi, 161.sayı.
  • Faraji Sabokbar, H., Hosseini, A., Banaitis, A., & Banaitiene, N. (2016). A novel sorting method TOPSIS-SORT: an applicaiton for Tehran environmental quality evaluation.
  • 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: an international journal, 24(7), 1723-1760.
  • Gul, M., & Guneri, A. F. (2016). A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry. Journal of Loss Prevention in the Process Industries, 40, 89-100.
  • Gul, M., & Guneri, A. F. (2018). Use of FAHP for occupational safety risk assessment: an application in the aluminum extrusion industry. Fuzzy analytic hierarchy process, 249-271.
  • Gul, M., Mete, S., Serin, F., & Celik, E. (2020). Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment: Approaches, Case Studies and Python Applications (Vol. 398). Springer Nature.
  • Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg.
  • Ishizaka, A., & López, C. (2019). Cost-benefit AHPSort for performance analysis of offshore providers. International Journal of Production Research, 57(13), 4261-4277.
  • Ishizaka, A., Lolli, F., Balugani, E., Cavallieri, R., & Gamberini, R. (2018). DEASort: Assigning items with data envelopment analysis in ABC classes. International Journal of Production Economics, 199, 7-15.
  • Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784.
  • Krejčí, J., & Ishizaka, A. (2018). FAHPSort: A fuzzy extension of the AHPSort method. International Journal of Information Technology & Decision Making, 17(04), 1119-1145.
  • Labella, Á., Ishizaka, A., & Martínez, L. (2021). Consensual Group-AHPSort: Applying consensus to GAHPSort in sustainable development and industrial engineering. Computers & Industrial Engineering, 152, 107013.
  • Marhavilas, P. K., & Koulouriotis, D. E. (2008). A risk-estimation methodological framework using quantitative assessment techniques and real accidents’ data: Application in an aluminum extrusion industry. Journal of Loss Prevention in the Process Industries, 21(6), 596-603.
  • Qin, J., Zeng, Y., & Zhou, Y. (2021). Context-Dependent DEASort: A Multiple Criteria Sorting Method for Ecological Risk Assessment Problems. Information Sciences.
  • Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
  • Roy, B. (1990). The outranking approach and the foundations of ELECTRE methods. In Readings in multiple criteria decision aid (pp. 155-183). Springer, Berlin, Heidelberg.
  • Saaty, T. L., & Vargas, L. G. (1984). The analytic network process. In Decision making with the analytic network process (pp. 1-40). Springer, Boston, MA.
  • Saha, P. K. (2000). Aluminum extrusion technology. ASM International.
  • Satty, T. L. (1980). The analytical hierarchy process: planning, priority setting, resourceallocation. RWS Publication.
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423.
  • Vanderpooten, D. (1990). The construction of prescriptions in outranking methods. In Readings in multiple criteria decision aid (pp. 184-215). Springer, Berlin, Heidelberg.
  • Vincke, P. (1992). Exploitation of a crisp relation in a ranking problem. Theory and Decision, 32(3), 221-240.
  • Xu, Z., Qin, J., Liu, J., & Martinez, L. (2019). Sustainable supplier selection based on AHPSort II in interval type-2 fuzzy environment. Information Sciences, 483, 273-293.
  • Yamagishi, K., & Ocampo, L. (2021). Utilizing TOPSIS-Sort for sorting tourist sites for perceived COVID-19 exposure. Current Issues in Tourism, 1-11.
  • Yoon, K. P., & Hwang, C. L. (1995). Multiple attribute decision making: an introduction. Sage publications.
  • Zou, Z. H., Yi, Y., & Sun, J. N. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental sciences, 18(5), 1020-1023.

TOPSIS-Sort Temelli Nicel Bir Mesleki Risk Değerlendirme Metodolojisi ve Alüminyum Ekstrüzyon Endüstrisinde Uygulanması

Year 2021, Volume: 7 Issue: 1, 163 - 172, 30.06.2021
https://doi.org/10.29132/ijpas.943612

Abstract

Alüminyum ekstrüzyon üretimini de kapsayan metal ürünleri sektörü, iş sağlığı ve güvenliği (İSG) açısından yüksek risk taşıyan sektörlerden biridir. Bu durum ve sektördeki iş kazalarının artış eğilimi göz önüne alındığında, iş güvenliğinin artırılması ihtiyacı ortaya çıkmaktadır. Bu nedenle, bu çalışma, alüminyum ekstrüzyon endüstrisindeki riskleri yönetmek için kümeleme temelli bir TOPSIS yaklaşımı (TOPSIS-Sort) ile nicel bir mesleki risk değerlendirmesi önermektedir. Metodolojinin uygulanabilirliği, 28 potansiyel tehlikenin üç risk parametresi (olasılık, ciddiyet ve sıklık) altında değerlendirilmesiyle gösterilmiştir. Değerlendirilen tehlikeler beş risk kümesine (Çok yüksek risk, Yüksek risk, Önemli risk, Olası risk ve Risk) bölünmüş ve risklerin azaltılmasını sağlayacak kontrol önlemleri belirlenmiştir. Çalışmanın sonuçları, Çok yüksek risk kümesine bir tehlikenin, Yüksek risk kümesine 3, Önemli risk kümesine 23 ve Olası risk kümesine bir tehlike atandığını göstermektedir.

References

  • Aneziris, O. N., Papazoglou, I. A., & Doudakmani, O. (2010). Assessment of occupational risks in an aluminium processing industry. International journal of industrial ergonomics, 40(3), 321-329.
  • Behzadian, M., Otaghsara, S. K., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with applications, 39(17), 13051-13069.
  • de Lima Silva, D. F., & de Almeida Filho, A. T. (2020). Sorting with TOPSIS through boundary and characteristic profiles. Computers & Industrial Engineering, 141, 106328.
  • Demir, L., Akpınar, M. E., Araz, C., & Ilgın, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487.
  • Demirci, K.M. (2013). Dünya alüminyum ticaretinde Türkiye’nin yeri. Metalurji Dergisi, 161.sayı.
  • Faraji Sabokbar, H., Hosseini, A., Banaitis, A., & Banaitiene, N. (2016). A novel sorting method TOPSIS-SORT: an applicaiton for Tehran environmental quality evaluation.
  • 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: an international journal, 24(7), 1723-1760.
  • Gul, M., & Guneri, A. F. (2016). A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry. Journal of Loss Prevention in the Process Industries, 40, 89-100.
  • Gul, M., & Guneri, A. F. (2018). Use of FAHP for occupational safety risk assessment: an application in the aluminum extrusion industry. Fuzzy analytic hierarchy process, 249-271.
  • Gul, M., Mete, S., Serin, F., & Celik, E. (2020). Fine–Kinney-Based Fuzzy Multi-criteria Occupational Risk Assessment: Approaches, Case Studies and Python Applications (Vol. 398). Springer Nature.
  • Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58-191). Springer, Berlin, Heidelberg.
  • Ishizaka, A., & López, C. (2019). Cost-benefit AHPSort for performance analysis of offshore providers. International Journal of Production Research, 57(13), 4261-4277.
  • Ishizaka, A., Lolli, F., Balugani, E., Cavallieri, R., & Gamberini, R. (2018). DEASort: Assigning items with data envelopment analysis in ABC classes. International Journal of Production Economics, 199, 7-15.
  • Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784.
  • Krejčí, J., & Ishizaka, A. (2018). FAHPSort: A fuzzy extension of the AHPSort method. International Journal of Information Technology & Decision Making, 17(04), 1119-1145.
  • Labella, Á., Ishizaka, A., & Martínez, L. (2021). Consensual Group-AHPSort: Applying consensus to GAHPSort in sustainable development and industrial engineering. Computers & Industrial Engineering, 152, 107013.
  • Marhavilas, P. K., & Koulouriotis, D. E. (2008). A risk-estimation methodological framework using quantitative assessment techniques and real accidents’ data: Application in an aluminum extrusion industry. Journal of Loss Prevention in the Process Industries, 21(6), 596-603.
  • Qin, J., Zeng, Y., & Zhou, Y. (2021). Context-Dependent DEASort: A Multiple Criteria Sorting Method for Ecological Risk Assessment Problems. Information Sciences.
  • Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57.
  • Roy, B. (1990). The outranking approach and the foundations of ELECTRE methods. In Readings in multiple criteria decision aid (pp. 155-183). Springer, Berlin, Heidelberg.
  • Saaty, T. L., & Vargas, L. G. (1984). The analytic network process. In Decision making with the analytic network process (pp. 1-40). Springer, Boston, MA.
  • Saha, P. K. (2000). Aluminum extrusion technology. ASM International.
  • Satty, T. L. (1980). The analytical hierarchy process: planning, priority setting, resourceallocation. RWS Publication.
  • Shannon, C. E. (1948). A mathematical theory of communication. The Bell system technical journal, 27(3), 379-423.
  • Vanderpooten, D. (1990). The construction of prescriptions in outranking methods. In Readings in multiple criteria decision aid (pp. 184-215). Springer, Berlin, Heidelberg.
  • Vincke, P. (1992). Exploitation of a crisp relation in a ranking problem. Theory and Decision, 32(3), 221-240.
  • Xu, Z., Qin, J., Liu, J., & Martinez, L. (2019). Sustainable supplier selection based on AHPSort II in interval type-2 fuzzy environment. Information Sciences, 483, 273-293.
  • Yamagishi, K., & Ocampo, L. (2021). Utilizing TOPSIS-Sort for sorting tourist sites for perceived COVID-19 exposure. Current Issues in Tourism, 1-11.
  • Yoon, K. P., & Hwang, C. L. (1995). Multiple attribute decision making: an introduction. Sage publications.
  • Zou, Z. H., Yi, Y., & Sun, J. N. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental sciences, 18(5), 1020-1023.
There are 30 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Muhammet Gül 0000-0002-5319-4289

Publication Date June 30, 2021
Submission Date May 27, 2021
Acceptance Date June 6, 2021
Published in Issue Year 2021 Volume: 7 Issue: 1

Cite

APA 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. https://doi.org/10.29132/ijpas.943612
AMA Gül M. A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort with its Application in Aluminum Extrusion Industry. International Journal of Pure and Applied Sciences. June 2021;7(1):163-172. doi:10.29132/ijpas.943612
Chicago Gül, Muhammet. “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, no. 1 (June 2021): 163-72. https://doi.org/10.29132/ijpas.943612.
EndNote Gül M (June 1, 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.
IEEE M. Gül, “A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort with its Application in Aluminum Extrusion Industry”, International Journal of Pure and Applied Sciences, vol. 7, no. 1, pp. 163–172, 2021, doi: 10.29132/ijpas.943612.
ISNAD Gül, Muhammet. “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 (June 2021), 163-172. https://doi.org/10.29132/ijpas.943612.
JAMA Gül M. A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort with its Application in Aluminum Extrusion Industry. International Journal of Pure and Applied Sciences. 2021;7:163–172.
MLA Gül, Muhammet. “A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort With Its Application in Aluminum Extrusion Industry”. International Journal of Pure and Applied Sciences, vol. 7, no. 1, 2021, pp. 163-72, doi:10.29132/ijpas.943612.
Vancouver Gül M. A Quantitative Occupational Risk Assessment Methodology Based on TOPSIS-Sort with its Application in Aluminum Extrusion Industry. International Journal of Pure and Applied Sciences. 2021;7(1):163-72.

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