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İşçi Sağlığı ve İş Güvenliğinde Bulanık Yöntemlere Dayalı Risk Değerlendirme Yaklaşımları

Yıl 2021, Cilt: 4 Sayı: 2, 49 - 64, 31.08.2021
https://doi.org/10.38213/ohsacademy.956021

Öz

ÜÜretim ve hizmet veren tüm endüstriyel organizasyonlarda meydana gelmesi olası kazaların ve bu kazaların insana, çevreye ve işletmeye olan zararlarının en aza indirilmesi amacıyla, sürekli ve etkili tedbirlerin alınması iş sağlığı ve güvenliği açısından en büyük ihtiyaçtır. Bu sebeple karşılaşılabilecek tüm tehlikeleri en aza indirgemek için farklı risk değerlendirme metodolojileri kullanılmaktadır. Risk değerlendirmesi, iş sağlığı ve güvenliği (İSG) yönetiminin önemli bir parçasıdır. Uygun bir risk değerlendirmesi yapıldığında tehlikeler ve riskler ortaya konur, risk altında olabilecek kişiler belirlenir ve hastalığı/yaralanmayı önlemek için kontrol önlemlerinin nerede gerekli olduğu belirlenebilir. Bu çalışmanın amacı, bulanık mantık yaklaşımı kullanılarak iş sağlığı ve güvenliği kapsamında yapılan risk değerlendirme uygulamalarını incelemektir. Bu amaçla önceden belirlenmiş dâhil etme kriterleri ile ilgili makaleler için Scopus veri tabanında sistematik bir literatür araştırması yapılmıştır. Çalışmada konferans bildirilerini, tezleri ve kitap bölümleri incelenmemiş olup, sadece araştırma makaleleri incelenmiştir. Ayrıca makalelerin dilleri olarak İngilizce ve Türkçe dışında bir dilde yazılmış herhangi bir makale eklenmemiştir. İncelenen çalışmaların genel olarak üç faktörle çalışıldığı ve bir olayla ilişkili riskleri olayın meydana gelme olasılığı, olayın sıklığı ile önem derecesi açısından incelendiği görülmüştür. Risk değerlenmesinin uygulandığı sektörlerin başında inşaat ve kimya sanayi gelmektedir. Ayrıca bulanık tabanlı risk değerlendirme sürecinin bir parçası olan duyarlılık analizi gözden geçirilen makalelerin birçoğunda yapılmamıştır. Sonuç olarak, uygun bir nicel olasılık modeline sahip olmayan riskler için, bulanık mantık sistemi, neden-sonuç ilişkilerini modellemeye, riske maruz kalma derecesini değerlendirmeye ve hem mevcut verileri hem de uzmanlara göre temel riskleri tutarlı bir şekilde sıralamaya yardımcı olmaktadır.

Kaynakça

  • Abul-Haggag O. Y., Barakat W. (2013). Application of Fuzzy Logic for Risk Assessment using Risk Matrix, International Journal of Emerging Technology and Advanced Engineering, 3(1). https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.413.6689&rep=rep1&type=pdf
  • Acuner, O., Çebi, S., (2016). An Effectıve Rısk-Preventıve Model Proposal For Occupatıonal Accidents at Shıpyards. Brodogradnja, 67, 67-84. Doi: http://dx.doi.org/10.21278/brod67104.
  • Âdem A., Çakit E. & Dağdeviren M., (2020). Occupational health and safety risk assessment in the domain of Industry 4.0., SN Applied Sciences, 2(5), Doi: http://dx.doi.org/10.1007/s42452-020-2817-x.
  • Akalp G., Özok A.F., (2017). Ergonomik Risklerin Bulanık Mantık Yöntemi ile Modellenmesi ve Bir Uygulama, Journal of Engineering Sciences and Design, 5(SI: Ergonomi2016), 69-79, Doi: http://dx.doi.org/10.21923/jesd.19802.
  • Ardeshir A, Amiri M, Ghasemi Y, Errington M. (2014). Risk Assessment of Construction Projects for Water Conveyance Tunnels Using Fuzzy Fault Tree Analysis, International Journal of Civil Engineering. 12 (4), 396-412. http://ijce.iust.ac.ir/article-1-878-en.pdf
  • Booth A, Papaioannou D., Sutton A., (2012). Systematic Approaches to a Successful Literature Review, London, Sage Publications.
  • Can G. F, Toktas, P. (2018). A novel fuzzy risk matrix based risk assessment approach. Kybernetes, Doi: http://dx.doi.org/10.1108/K-12-2017-0497.
  • Çebi̇ S., Temi̇zoğlu H. (2020). Makine Tabanlı Dinamik Risk Analizi İçin Bir Karar Destek Sistemi Geliştirme. Uluslararası İktisadi ve İdari İncelemeler Dergisi, Prof. Dr. Talha Ustasüleyman Özel Sayısı, 149-166. Doi: http://dx.doi.org/10.18092/ulikidince.579073
  • Debnath, J., Biswas, A., Sivan, P., Sen, K. N., Sahu, S. (2016). Fuzzy inference model for assessing occupational risks in construction sites. International Journal of Industrial Ergonomics, 55, 114–128. Doi: http://dx.doi.org/10.1016/j.ergon.2016.08.004
  • 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: http://dx.doi.org/10.1177/1748006x15581219
  • Fink A., (2009). Conducting Research Literature Reviews: From the Internet to Paper, California, Sage Publications.
  • Gjerdrum D., Peter M. (2011). The New International Standard on the Practice of Risk Management- A Comparison of ISO 31000:2009 and the COSO ERM Framework, Risk Management, Society of Actuaries, 21, 8-12., https://www.soa.org/globalassets/assets/library/newsletters/risk-management-newsletter/2011/march/jrm-2011-iss21-gjerdrum.pdf
  • Gul M., Ak, M. F., Guneri, A. F. (2016). Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi criteria approach. Human and Ecological Risk Assessment: An International Journal, 187-202. Doi: http://dx.doi.org/10.1080/10807039.2016.1234363
  • Gul M., Guneri, A. F & Başkan M. (2018). An occupational risk assessment approach for construction and operation period of wind turbines, Global Journal of Environmental Science and Management, 4(3), 281-298. Doi: http://dx.doi.org/10.22034/gjesm.2018.03.003
  • Gul M, Ak M. F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA, Stochastic Environmental Research and Risk Assessment, Doi: http://dx.doi.org/10.1007/s00477-020-01816-x
  • 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, Doi: http://dx.doi.org/10.1016/j.jlp.2015.11.023.
  • Herrera F, Viedma E.H. (2000). Linguistic Decision Analysis: Steps For Solving Decision Problems Under Linguistic Information. Fuzzy Sets and Systems, 115(1), 67–82, Doi: http://dx.doi.org/10.1016/S0165-0114(99)00024-X
  • Ilbahar, E., Karaşan, A., Cebi, S., Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103, 124–136. Doi: http://dx.doi.org/10.1016/j.ssci.2017.10.025.
  • Jana, D. K., Pramanik, S., Sahoo, P., Mukherjee, A. (2017). Interval type-2 fuzzy logic and its application to occupational safety risk performance in industries, Soft Computing, Doi: http://dx.doi.org/10.1007/s00500-017-2860-8
  • Korkusuz A, İnan U, Özdemi̇r Y, Başlıgi̇l H. (2019). Entegre çok kriterli karar verme yöntemleriyle sağlık sektöründe iş sağlığı ve güvenliği performansının ölçülmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35 (1), 81-96. Doi: http://dx.doi.org/10.17341/gazimmfd.441032.
  • Liu, H.-T., Tsai, Y. (2012). A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety Science, 50(4), 1067–1078, Doi: http://dx.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, 85–99. Doi: http://dx.doi.org/10.1016/j. scitotenv.2014.04.076
  • Mete S., (2019). Assessing occupational risks in pipeline construction using FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy environment, Human and Ecological Risk Assessment: An International Journal, 25 (7), 1645-1660, Doi: http://dx.doi.org/10.1080/10807039.2018.1546115.
  • Özdemir Y., Gül M., Çelik E. (2017). Assessment of occupational hazards and associated risks in fuzzy environment: a case study of a university chemical laboratory, Human and Ecological Risk Assessment: An International Journal, 23 (4),895-924, Doi: http://dx.doi.org/10.1080/10807039.2017.1292844.
  • Rezaee MJ, Salimi A, Yousefi S. (2017). Identifying and managing failures in stone processing industry using cost-based FMEA. The International Journal of Advanced Manufacturing Technology, 88(9–12),3329–42, Doi: http://dx.doi.org/10.1007/s00170-016-9019-0
  • Ringdahl L. H., (2001). Safety Analysis Principles and Practice in Occupational Safety Risk Assessment, New York, Taylor&Francis.
  • Supciller A., Abali N. (2015). Occupational Health and Safety Within the Scope of Risk Analysis with Fuzzy Proportional Risk Assessment Technique (Fuzzy Prat). Quality and Reliability Engineering International, 31(7), 1137–1150. Doi: http://dx.doi.org/10.1002/qre.1908.
  • Tadic, D., Djapan, M., Misita, M., Stefanovic, M., Milanovic, D. D. (2012). A Fuzzy Model for Assessing Risk of Occupational Safety in the Processing Industry. International Journal of Occupational Safety and Ergonomics, 18(2), 115–126. Doi: http://dx.doi.org/10.1080/10803548.2012.1107692
  • Tepe S., Kaya İ. (2019). A fuzzy-based risk assessment model for evaluations of hazards with a real-case study, Human and Ecological Risk Assessment, 26 (2), 512-537, Doi: http://dx.doi.org/10.1080/10807039.2018.1521262.
  • Yazdi M., Kabir S., (2017). A Fuzzy Bayesian Network approach for Risk Analysis in Process Industries. Process Safety and Environmental Protection, Doi: http://dx.doi.org/10.1016/j.psep.2017.08.015
  • Yazdi, M.& Zarei, E. (2018). Uncertainty Handling in the Safety Risk Analysis: An Integrated Approach Based on Fuzzy Fault Tree Analysis. Journal of Failure Analysis and Prevention, Doi: http://dx.doi.org/10.1007/s11668-018-0421-9.
  • Yılmaz N., & Şenol M.B. (2017). İş sağlığı ve güvenliği risk değerlendirme süreci için bulanık çok kriterli bir model ve uygulaması. Journal of the Faculty of Engineering and Architecture of Gazi University. 32(1), 77-87. Doi: http://dx.doi.org/10.17341/gazimmfd.300597
  • Zile M., (2015). İş Güvenliği Risk Değerlendirme Analiz Modellemesi ve Yazılımının Bulanık Mantıkla Oluşturulması, Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 30(2), 267-273. Doi: https://doi.org/10.21605/cukurovaummfd.242762
  • Zhou Z, Goh Y.M., Li Q, (2015). Overview and analysis of safety management studies in the construction industry, Safety Science, 72, 337-350. Doi: https://doi.org/10.1016/j.ssci.2014.10.006

Risk Assessment Approaches Based on Fuzzy Methods in Occupational Health and Safety

Yıl 2021, Cilt: 4 Sayı: 2, 49 - 64, 31.08.2021
https://doi.org/10.38213/ohsacademy.956021

Öz

Taking continuous and effective measures is the greatest need in terms of occupational health and safety to minimize possible accidents that may occur in all industrial organizations that provide production and service and the damage of these accidents to humans, the environment, and business. For this reason, different risk assessment methodologies are used to minimize all possible hazards. Risk assessment is an important part of occupational health and safety (OHS) management. When an appropriate risk assessment is carried out, hazards and risks are identified, people who may be at risk are identified, and where control measures are needed to prevent illness/injury can be determined. This study aims to examine the risk assessment applications made within the scope of occupational health and safety by using the fuzzy logic approach. For this purpose, a systematic literature search was conducted in the Scopus database for articles related to predetermined inclusion criteria. In the study, conference proceedings, theses, and book chapters were not examined, only research articles were examined. In addition, no articles written in a language other than English and Turkish were added as the languages of the articles. It was seen that the studies examined were generally studied with three factors and the risks associated with an event were examined in terms of the probability of occurrence of the event, the frequency of the event, and the degree of importance. The construction and chemical industries are the leading sectors in which risk assessment is applied. Also, sensitivity analysis, which is part of the fuzzy-based risk assessment process, was not performed in many of the articles reviewed. As a result, for risks that do not have an appropriate quantitative probability model, the fuzzy logic system helps to model cause-effect relationships, assess the degree of risk exposure, and consistently rank the key risks according to both available data and experts.

Kaynakça

  • Abul-Haggag O. Y., Barakat W. (2013). Application of Fuzzy Logic for Risk Assessment using Risk Matrix, International Journal of Emerging Technology and Advanced Engineering, 3(1). https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.413.6689&rep=rep1&type=pdf
  • Acuner, O., Çebi, S., (2016). An Effectıve Rısk-Preventıve Model Proposal For Occupatıonal Accidents at Shıpyards. Brodogradnja, 67, 67-84. Doi: http://dx.doi.org/10.21278/brod67104.
  • Âdem A., Çakit E. & Dağdeviren M., (2020). Occupational health and safety risk assessment in the domain of Industry 4.0., SN Applied Sciences, 2(5), Doi: http://dx.doi.org/10.1007/s42452-020-2817-x.
  • Akalp G., Özok A.F., (2017). Ergonomik Risklerin Bulanık Mantık Yöntemi ile Modellenmesi ve Bir Uygulama, Journal of Engineering Sciences and Design, 5(SI: Ergonomi2016), 69-79, Doi: http://dx.doi.org/10.21923/jesd.19802.
  • Ardeshir A, Amiri M, Ghasemi Y, Errington M. (2014). Risk Assessment of Construction Projects for Water Conveyance Tunnels Using Fuzzy Fault Tree Analysis, International Journal of Civil Engineering. 12 (4), 396-412. http://ijce.iust.ac.ir/article-1-878-en.pdf
  • Booth A, Papaioannou D., Sutton A., (2012). Systematic Approaches to a Successful Literature Review, London, Sage Publications.
  • Can G. F, Toktas, P. (2018). A novel fuzzy risk matrix based risk assessment approach. Kybernetes, Doi: http://dx.doi.org/10.1108/K-12-2017-0497.
  • Çebi̇ S., Temi̇zoğlu H. (2020). Makine Tabanlı Dinamik Risk Analizi İçin Bir Karar Destek Sistemi Geliştirme. Uluslararası İktisadi ve İdari İncelemeler Dergisi, Prof. Dr. Talha Ustasüleyman Özel Sayısı, 149-166. Doi: http://dx.doi.org/10.18092/ulikidince.579073
  • Debnath, J., Biswas, A., Sivan, P., Sen, K. N., Sahu, S. (2016). Fuzzy inference model for assessing occupational risks in construction sites. International Journal of Industrial Ergonomics, 55, 114–128. Doi: http://dx.doi.org/10.1016/j.ergon.2016.08.004
  • 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: http://dx.doi.org/10.1177/1748006x15581219
  • Fink A., (2009). Conducting Research Literature Reviews: From the Internet to Paper, California, Sage Publications.
  • Gjerdrum D., Peter M. (2011). The New International Standard on the Practice of Risk Management- A Comparison of ISO 31000:2009 and the COSO ERM Framework, Risk Management, Society of Actuaries, 21, 8-12., https://www.soa.org/globalassets/assets/library/newsletters/risk-management-newsletter/2011/march/jrm-2011-iss21-gjerdrum.pdf
  • Gul M., Ak, M. F., Guneri, A. F. (2016). Occupational health and safety risk assessment in hospitals: A case study using two-stage fuzzy multi criteria approach. Human and Ecological Risk Assessment: An International Journal, 187-202. Doi: http://dx.doi.org/10.1080/10807039.2016.1234363
  • Gul M., Guneri, A. F & Başkan M. (2018). An occupational risk assessment approach for construction and operation period of wind turbines, Global Journal of Environmental Science and Management, 4(3), 281-298. Doi: http://dx.doi.org/10.22034/gjesm.2018.03.003
  • Gul M, Ak M. F. (2020). Assessment of occupational risks from human health and environmental perspectives: a new integrated approach and its application using fuzzy BWM and fuzzy MAIRCA, Stochastic Environmental Research and Risk Assessment, Doi: http://dx.doi.org/10.1007/s00477-020-01816-x
  • 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, Doi: http://dx.doi.org/10.1016/j.jlp.2015.11.023.
  • Herrera F, Viedma E.H. (2000). Linguistic Decision Analysis: Steps For Solving Decision Problems Under Linguistic Information. Fuzzy Sets and Systems, 115(1), 67–82, Doi: http://dx.doi.org/10.1016/S0165-0114(99)00024-X
  • Ilbahar, E., Karaşan, A., Cebi, S., Kahraman, C. (2018). A novel approach to risk assessment for occupational health and safety using Pythagorean fuzzy AHP & fuzzy inference system. Safety Science, 103, 124–136. Doi: http://dx.doi.org/10.1016/j.ssci.2017.10.025.
  • Jana, D. K., Pramanik, S., Sahoo, P., Mukherjee, A. (2017). Interval type-2 fuzzy logic and its application to occupational safety risk performance in industries, Soft Computing, Doi: http://dx.doi.org/10.1007/s00500-017-2860-8
  • Korkusuz A, İnan U, Özdemi̇r Y, Başlıgi̇l H. (2019). Entegre çok kriterli karar verme yöntemleriyle sağlık sektöründe iş sağlığı ve güvenliği performansının ölçülmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35 (1), 81-96. Doi: http://dx.doi.org/10.17341/gazimmfd.441032.
  • Liu, H.-T., Tsai, Y. (2012). A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety Science, 50(4), 1067–1078, Doi: http://dx.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, 85–99. Doi: http://dx.doi.org/10.1016/j. scitotenv.2014.04.076
  • Mete S., (2019). Assessing occupational risks in pipeline construction using FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy environment, Human and Ecological Risk Assessment: An International Journal, 25 (7), 1645-1660, Doi: http://dx.doi.org/10.1080/10807039.2018.1546115.
  • Özdemir Y., Gül M., Çelik E. (2017). Assessment of occupational hazards and associated risks in fuzzy environment: a case study of a university chemical laboratory, Human and Ecological Risk Assessment: An International Journal, 23 (4),895-924, Doi: http://dx.doi.org/10.1080/10807039.2017.1292844.
  • Rezaee MJ, Salimi A, Yousefi S. (2017). Identifying and managing failures in stone processing industry using cost-based FMEA. The International Journal of Advanced Manufacturing Technology, 88(9–12),3329–42, Doi: http://dx.doi.org/10.1007/s00170-016-9019-0
  • Ringdahl L. H., (2001). Safety Analysis Principles and Practice in Occupational Safety Risk Assessment, New York, Taylor&Francis.
  • Supciller A., Abali N. (2015). Occupational Health and Safety Within the Scope of Risk Analysis with Fuzzy Proportional Risk Assessment Technique (Fuzzy Prat). Quality and Reliability Engineering International, 31(7), 1137–1150. Doi: http://dx.doi.org/10.1002/qre.1908.
  • Tadic, D., Djapan, M., Misita, M., Stefanovic, M., Milanovic, D. D. (2012). A Fuzzy Model for Assessing Risk of Occupational Safety in the Processing Industry. International Journal of Occupational Safety and Ergonomics, 18(2), 115–126. Doi: http://dx.doi.org/10.1080/10803548.2012.1107692
  • Tepe S., Kaya İ. (2019). A fuzzy-based risk assessment model for evaluations of hazards with a real-case study, Human and Ecological Risk Assessment, 26 (2), 512-537, Doi: http://dx.doi.org/10.1080/10807039.2018.1521262.
  • Yazdi M., Kabir S., (2017). A Fuzzy Bayesian Network approach for Risk Analysis in Process Industries. Process Safety and Environmental Protection, Doi: http://dx.doi.org/10.1016/j.psep.2017.08.015
  • Yazdi, M.& Zarei, E. (2018). Uncertainty Handling in the Safety Risk Analysis: An Integrated Approach Based on Fuzzy Fault Tree Analysis. Journal of Failure Analysis and Prevention, Doi: http://dx.doi.org/10.1007/s11668-018-0421-9.
  • Yılmaz N., & Şenol M.B. (2017). İş sağlığı ve güvenliği risk değerlendirme süreci için bulanık çok kriterli bir model ve uygulaması. Journal of the Faculty of Engineering and Architecture of Gazi University. 32(1), 77-87. Doi: http://dx.doi.org/10.17341/gazimmfd.300597
  • Zile M., (2015). İş Güvenliği Risk Değerlendirme Analiz Modellemesi ve Yazılımının Bulanık Mantıkla Oluşturulması, Çukurova Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 30(2), 267-273. Doi: https://doi.org/10.21605/cukurovaummfd.242762
  • Zhou Z, Goh Y.M., Li Q, (2015). Overview and analysis of safety management studies in the construction industry, Safety Science, 72, 337-350. Doi: https://doi.org/10.1016/j.ssci.2014.10.006
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Derleme Makale
Yazarlar

Emine Bozkuş 0000-0002-1823-6105

Özcan Bozkuş 0000-0002-0975-025X

Yayımlanma Tarihi 31 Ağustos 2021
Kabul Tarihi 27 Ağustos 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 4 Sayı: 2

Kaynak Göster

APA Bozkuş, E., & Bozkuş, Ö. (2021). İşçi Sağlığı ve İş Güvenliğinde Bulanık Yöntemlere Dayalı Risk Değerlendirme Yaklaşımları. OHS ACADEMY, 4(2), 49-64. https://doi.org/10.38213/ohsacademy.956021