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Güvenli İş Yerlerinin Sağlanması İçin Yapay Zekâ Tabanlı Bir Program Geliştirilmesi Ve Depolama Sektöründe Kayma, Tökezleme Ve Düşme Risklerinin Analizi

Yıl 2025, Cilt: 30 Sayı: 1, 17 - 34, 28.04.2025
https://doi.org/10.17482/uumfd.1553249

Öz

Yapay zekâ (AI), insan bilişi gerektiren görevleri yerine getirebilecek makineler geliştirmek için tasarlanmış olup, birçok alanda yaygın olarak kullanılmaktadır. Yapay zekânın bir alt dalı olan uzman sistemler (ESs), uzman bilgisi kullanarak karmaşık sorunları çözmektedir. Bu çalışma, yaygın ve karmaşık mekanizmalara sahip kayma, tökezleme ve düşme (STF) kazalarını azaltmayı amaçlayan, AI destekli bir ES olan WaSaEx programının geliştirilmesine odaklanmaktadır. WaSaEx, iş güvenliği uzmanları tarafından çevrimdışı olarak kullanılmak üzere tasarlanmış olup, iş sağlığı ve güvenliği (OHS) için risk analizi, maliyet hesaplama ve eğitim planlama gibi işlevler sunmaktadır. Python ve CLIPS kullanılarak geliştirilen WaSaEx, OHS alanında kullanılan diğer programlardan ES tabanlı olmasıyla ayrılmaktadır. Bu çalışma, WaSaEx programını tanıtarak, depolama alanlarındaki STF risklerini raporlama açısından risk analizi ve önleyici tedbirler konusundaki yetkinliğini değerlendirmektedir. Program, kullanıcı yanıtlarına dayalı olarak riskleri değerlendirmek için L-tipi (5x5) matris yöntemi kullanmakta, her bir faktör için risk skorları ve uygun önleyici tedbirler sunmaktadır. Ayrıca, depolama alanlarında kazalara yol açabilecek risk faktörlerinin etkileşimi sistematik olarak analize dahil edilmektedir. Sonuç olarak, WaSaEx, hızlı ve doğru risk analizi yapılmasını hedefleyen, maliyet etkin ve bilgi tabanlı bir çözüm sunmaktadır. Bu yöntem, doğrulanmış önleyici tedbirler sağlamanın yanı sıra artık riskleri önemli ölçüde azaltarak depolama ortamlarında güvenliğin artırılmasına katkıda bulunmaktadır. Uzman bir çerçeveye sahip olan WaSaEx, iş yeri güvenliği standartlarının geliştirilmesinde önemli bir rol oynamaktadır.

Kaynakça

  • Abdul Aziz, F., Nik Mohamed, N.M.Z. and Mohd Rose, A.N. (2022). Integration of analytic hierarchy process technique and knowledge-based system to prioritize essential critical risk factors using the web-based approach, enabling industry 4.0 through advances in manufacturing and materials, Selected Articles from IM3F 2021, Malaysia https://doi.org/10.1007/978-981-19-2890-1_49
  • Alawad, H., Kaewunruen, S. and An, M. (2020) A deep learning approach towards railway safety risk assessment, IEEE Access, 8, 102811–102832. https://doi.org/10.1109/ACCESS.2020.2997946
  • Allahverdi, N. (2002) Uzman Sistemler: Bir Yapay Zekâ Uygulaması, Atlas Yayın
  • Amiri, M., Ardeshir, A. and Fazel Zarandi, M. H. (2017) Fuzzy probabilistic expert system for occupational hazard assessment in construction, Safety Science, 93, 16–28. https://doi.org/10.1016/j.ssci.2016.11.008
  • Azadeh, A., Fam I.M., Khoshnoud, M. and Nikafrouz, M. (2008) Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: The case of a gas refinery, Information Sciences, 178(22):4280–4300. https://doi.org/10.1016/j.ins.2008.06.026
  • Baron, P., Brázda, P., Dobránsky, J and Kočiško, M. (2012) Expert system approach to safety management, Risk Analysis 2012: 8th International Conference on Risk Analysis and Hazard Mitigation 2012, WIT Transactions on Information and Communication Technologies, 77-88. http://dx.doi.org/10.2495/RISK120081
  • Başak, H., Şahin, İ and Gülen, M. (2008) İnsansız hava aracı kazalarının önlenmesi için uzman sisteme dayalı risk yönetimi modeli, Teknoloji 11(3),187–200
  • Bentley, T., Tappin, D., Moore, D., Legg, S., Ashby, L. and Parker, R. (2005) Investigating slips, trips, and falls in the New Zealand dairy farming sector, Ergonomics, 48(8), 1008–1019. https://doi.org/10.1080/00140130500182072
  • Bentley, T. A., Hide, S., Tappin, D., Moore, D., Legg, S., Ashby, L. and Parker, R. (2006) Investigating risk factors for slips, trips, and falls in New Zealand residential construction using incident-centered and incident-independent methods, Ergonomics, 49(1), 62–77. https://doi.org/10.1080/00140130612331392236
  • Beriha, G.S., Patnaik, B., Mahapatra, S.S and Padhee, S. (2012) Assessment of safety performance in Indian industries using fuzzy approach, Expert Systems with Applications 39(3), 3311–3323. https://doi.org/10.1016/j.eswa.2011.09.018
  • Chang, W.‑R., Leclercq, S., Lockhart, T. E. and Haslam, R. (2016) State of science: occupational slips, trips, and falls on the same level, Ergonomics, 1–23. https://doi.org/10.1080/00140139.2016.1157214
  • Chen, D., Asaeikheybari, G., Chen, H., Xu, W. and Huang, M.‑C. (2020) Ubiquitous fall hazard identification with smart insole, IEEE Journal of Biomedical and Health Informatics, 25(7), 2768–2776. https://doi.org/10.1109/jbhi.2020.3046701
  • Chen, S., Dong, F. and Demachi, K. (2023) Hybrid visual information analysis for on-site occupational hazards identification: A case study on stairway safety, Safety Science, 159. https://doi.org/10.1016/j.ssci.2022.106043
  • Dashti, S. M., and Dashti, S. F. (2020) An expert system to diagnose spinal disorders, The Open Bioinformatics Journal, 13(1), 57–73. https://doi.org/10.2174/ 1875036202013010057
  • Dong, R. G., Wu, J. Z., Dai, F. and Breloff, S. P. (2021) An alternative method for analyzing the slip potential of workers on sloped surfaces, Safety Science, 133, https://doi.org/10.1016/j.ssci.2020.105026
  • Durdevic, D., Andrejic, M. and Pavlov, N. (2022) Framework for improving warehouse safety, 5th Logistics International Conference, Symposium Belgrade
  • Gupta, I. and Nagpal, G. (2020) Artificial Intelligence and Expert Systems, Mercury Learning and Information.
  • Han, Z., Li, Y., Zhao, Z. and Zhang, B. (2022) An Online safety monitoring system of hydropower station based on expert system, Energy Reports 8:1552–1567. https://doi.org/10.1016/j.egyr.2022.02.040
  • Haslam, R. and Filingeri, V. (2018) Slips, trips, and falls in crowds. Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), 752–758, Springer
  • Hollnagel, E. (2012) FRAM, the functional resonance analysis method. Modelling complex socio-technical systems, Farnham, Surrey, UK England
  • Kong, P. W., Suyama, J. and Hostler, D. (2013) A Review of risk factors of accidental slips, trips, and falls among firefighters, Safety Science, 60, 203–209 https://doi.org/10.1016/j.ssci.2013.07.016
  • Larue, G. S., Popovic, V., Legge, M., Brophy, C. and Blackman, R. (2021) Safe trip: factors contributing to slip, trip, and fall risk at train stations, Applied Ergonomics, 92, https://doi.org/10.1016/j.apergo.2020.103316
  • Leclercq, S., Morel, G., Chauvin, C. and Claudon, L. (2021) Analysis method for revealing human and organisational factors of occupational accidents with movement disturbance (OAMDs), Ergonomics, 64(1), 113–128. https://doi.org/10.1080/00140139.2020.1817570
  • Li, J., Goerlandt, F. and Li, K. W. (2019) Slip and fall incidents at work: a visual analytics analysis of the research domain, International Journal of Environmental Research and Public Health, 16(24), 4972. https://doi.org/10.3390/ijerph16244972
  • Lilić, N., Obradović, I. and Cvjetić, A. (2010) An intelligent hybrid system for surface coal mine safety analysis, Engineering Applications of Artificial Intelligence 23(4):453–462. https://doi.org/10.1016/j.engappai.2010.01.025
  • Liberty Mutual (2021). Liberty Mutual Workplace Safety Index 2021. Access Address: https://business.libertymutual.com/ wp-content/uploads/2021/06/ 2021_ WSI_ 1000 _R2.pdf (Access Date: 23.11.2022)
  • Meciarova J. (2011) Expert system for assessing health hazards of metalworking fluids, Annals of DAAAM for 2011 & proceedings of the 22nd International DAAAM Symposium, 22, Vienna, Austria
  • Mohan, S., Anand, A., Ul Haq, M. I., Raina, A., Kumar, R. and Kamal, M. (2020) Development of a NIOSH based software tool for musculoskeletal disorders. Indian Journal of Engineering and Materials Sciences (IJEMS), 27(4), 860–865.
  • Motorcu, A. R. and Murat, B. (2021a) İş kazası etmeni olarak kayma, tökezleme ve düşme (KTD): Türkiye incelemesi. Mühendislik ve Multidisipliner Yaklaşımlar, 572–592. Güven Plus A.Ş.
  • Motorcu, A. R. and Murat, B. (2021b). Yeni işyeri riskleri ve yapay zekanin iş sağliği ve güvenliğinde kullanimi. Mühendislik ve Multidisipliner Yaklaşımlar 369–402. Güven Plus A.Ş.
  • Murat, B., Motorcu, A. R. and Kayır, Y. (2022) Uzman sistem çalışmalarının bibliyometrik analizi ve iş sağliği güvenliğinde uygulama örnekleri. İş Güvenliği ve Çalışan Sağlığı, 222–247. Güven Plus A.Ş.
  • Nenonen, N. (2013) Analysing factors related to slipping, stumbling, and falling accidents at work: application of data mining methods to Finnish occupational accidents and diseases statistics database, Applied Ergonomics, 44(2), 215–224. https://doi.org/10.1016/j.apergo.2012.07.001
  • Newaz, M.T., Ershadi, M, Jefferies, M. Pillay, M. and Davis, P. (2023) A Systematic review of contemporary safety management research: a multi-level approach to identifying trending domains in the construction industry, Construction Management and Economics, 41 (2), 97–115. https://doi.org/10.1080/01446193.2022.2124527
  • Pac, M., Mikutskaya, I. and Mulawka, J. (2021) Knowledge discovery from medical data and development of an expert system in immunology, Entropy, 23(6). https://doi.org/10.3390/e23060695
  • Pawłowska, Z. (2010) Occupational Risk Assessment, Boca Raton, FL: CRC Press/Taylor & Francis (Human factors and ergonomics).
  • Popovic, V., Larue, G. S., Legge, M., Brophy, C. and Blackman, R. (2023) Risk mitigation at train stations: underlying causes of slips, trips, and falls for passengers with reduced mobility, Ergonomics, 1–22. https://doi.org/10.1080/00140139.2023.2195139
  • Qiu, S., Sallak, M., Schön, W. and Ming, H. X. (2018) A Valuation-based system approach for risk assessment of belief rule-based expert systems, Information Sciences, 466, 323–336. https://doi.org/10.1016/j.ins.2018.04.039
  • Pavlovic-Veselinovic, S., Hedge, A. and Veselinovic, M. (2016) An ergonomic expert system for risk assessment of work-related musculo-skeletal disorders, International Journal of Industrial Ergonomics, 53:130–139. https://doi.org/10.1016/j.ergon.2015.11.008.
  • Rasmussen, J. and Svedung, I. (2000) Proactive Risk Management in a Dynamic Society. First Edition. Sweden.
  • Richards, G. (2018) Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse (3rd ed.), Kogan Page Limited.
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DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES

Yıl 2025, Cilt: 30 Sayı: 1, 17 - 34, 28.04.2025
https://doi.org/10.17482/uumfd.1553249

Öz

Artificial intelligence (AI), designed to enable machines to perform tasks requiring human cognition, is widely used across many fields. Expert systems (ESs), a subset of AI, solve complex problems via expert knowledge. This study focuses on mitigating prevalent and complex slip, trip, and fall (STF) incidents by developing a program called WaSaEx, based on an AI-supported ES. WaSaEx, designed for offline use by occupational safety specialists, offers risk analysis, cost estimation, and training planning for occupational health and safety (OHS). Developed via Python and CLIPS, WaSaEx is ES-based, distinct from other OHS programs. This study introduces the WaSaEx program and evaluates its capability for risk analysis and preventive measures, specifically for reporting STF risks in storage areas. The program uses an L-type (5x5) matrix method to assess risks based on user responses, providing risk scores and preventive measures for each factor. It also systematically accounts for the interaction of risk factors that may lead to accidents. Consequently, WaSaEx offers a cost-effective, knowledge-based solution to enable swift and accurate risk analysis. This methodology delivers validated preventive measures and substantially reduces residual risks, thus fostering improved safety in storage environments. WaSaEx is pivotal in advancing workplace safety standards through its expert framework.

Kaynakça

  • Abdul Aziz, F., Nik Mohamed, N.M.Z. and Mohd Rose, A.N. (2022). Integration of analytic hierarchy process technique and knowledge-based system to prioritize essential critical risk factors using the web-based approach, enabling industry 4.0 through advances in manufacturing and materials, Selected Articles from IM3F 2021, Malaysia https://doi.org/10.1007/978-981-19-2890-1_49
  • Alawad, H., Kaewunruen, S. and An, M. (2020) A deep learning approach towards railway safety risk assessment, IEEE Access, 8, 102811–102832. https://doi.org/10.1109/ACCESS.2020.2997946
  • Allahverdi, N. (2002) Uzman Sistemler: Bir Yapay Zekâ Uygulaması, Atlas Yayın
  • Amiri, M., Ardeshir, A. and Fazel Zarandi, M. H. (2017) Fuzzy probabilistic expert system for occupational hazard assessment in construction, Safety Science, 93, 16–28. https://doi.org/10.1016/j.ssci.2016.11.008
  • Azadeh, A., Fam I.M., Khoshnoud, M. and Nikafrouz, M. (2008) Design and implementation of a fuzzy expert system for performance assessment of an integrated health, safety, environment (HSE) and ergonomics system: The case of a gas refinery, Information Sciences, 178(22):4280–4300. https://doi.org/10.1016/j.ins.2008.06.026
  • Baron, P., Brázda, P., Dobránsky, J and Kočiško, M. (2012) Expert system approach to safety management, Risk Analysis 2012: 8th International Conference on Risk Analysis and Hazard Mitigation 2012, WIT Transactions on Information and Communication Technologies, 77-88. http://dx.doi.org/10.2495/RISK120081
  • Başak, H., Şahin, İ and Gülen, M. (2008) İnsansız hava aracı kazalarının önlenmesi için uzman sisteme dayalı risk yönetimi modeli, Teknoloji 11(3),187–200
  • Bentley, T., Tappin, D., Moore, D., Legg, S., Ashby, L. and Parker, R. (2005) Investigating slips, trips, and falls in the New Zealand dairy farming sector, Ergonomics, 48(8), 1008–1019. https://doi.org/10.1080/00140130500182072
  • Bentley, T. A., Hide, S., Tappin, D., Moore, D., Legg, S., Ashby, L. and Parker, R. (2006) Investigating risk factors for slips, trips, and falls in New Zealand residential construction using incident-centered and incident-independent methods, Ergonomics, 49(1), 62–77. https://doi.org/10.1080/00140130612331392236
  • Beriha, G.S., Patnaik, B., Mahapatra, S.S and Padhee, S. (2012) Assessment of safety performance in Indian industries using fuzzy approach, Expert Systems with Applications 39(3), 3311–3323. https://doi.org/10.1016/j.eswa.2011.09.018
  • Chang, W.‑R., Leclercq, S., Lockhart, T. E. and Haslam, R. (2016) State of science: occupational slips, trips, and falls on the same level, Ergonomics, 1–23. https://doi.org/10.1080/00140139.2016.1157214
  • Chen, D., Asaeikheybari, G., Chen, H., Xu, W. and Huang, M.‑C. (2020) Ubiquitous fall hazard identification with smart insole, IEEE Journal of Biomedical and Health Informatics, 25(7), 2768–2776. https://doi.org/10.1109/jbhi.2020.3046701
  • Chen, S., Dong, F. and Demachi, K. (2023) Hybrid visual information analysis for on-site occupational hazards identification: A case study on stairway safety, Safety Science, 159. https://doi.org/10.1016/j.ssci.2022.106043
  • Dashti, S. M., and Dashti, S. F. (2020) An expert system to diagnose spinal disorders, The Open Bioinformatics Journal, 13(1), 57–73. https://doi.org/10.2174/ 1875036202013010057
  • Dong, R. G., Wu, J. Z., Dai, F. and Breloff, S. P. (2021) An alternative method for analyzing the slip potential of workers on sloped surfaces, Safety Science, 133, https://doi.org/10.1016/j.ssci.2020.105026
  • Durdevic, D., Andrejic, M. and Pavlov, N. (2022) Framework for improving warehouse safety, 5th Logistics International Conference, Symposium Belgrade
  • Gupta, I. and Nagpal, G. (2020) Artificial Intelligence and Expert Systems, Mercury Learning and Information.
  • Han, Z., Li, Y., Zhao, Z. and Zhang, B. (2022) An Online safety monitoring system of hydropower station based on expert system, Energy Reports 8:1552–1567. https://doi.org/10.1016/j.egyr.2022.02.040
  • Haslam, R. and Filingeri, V. (2018) Slips, trips, and falls in crowds. Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018), 752–758, Springer
  • Hollnagel, E. (2012) FRAM, the functional resonance analysis method. Modelling complex socio-technical systems, Farnham, Surrey, UK England
  • Kong, P. W., Suyama, J. and Hostler, D. (2013) A Review of risk factors of accidental slips, trips, and falls among firefighters, Safety Science, 60, 203–209 https://doi.org/10.1016/j.ssci.2013.07.016
  • Larue, G. S., Popovic, V., Legge, M., Brophy, C. and Blackman, R. (2021) Safe trip: factors contributing to slip, trip, and fall risk at train stations, Applied Ergonomics, 92, https://doi.org/10.1016/j.apergo.2020.103316
  • Leclercq, S., Morel, G., Chauvin, C. and Claudon, L. (2021) Analysis method for revealing human and organisational factors of occupational accidents with movement disturbance (OAMDs), Ergonomics, 64(1), 113–128. https://doi.org/10.1080/00140139.2020.1817570
  • Li, J., Goerlandt, F. and Li, K. W. (2019) Slip and fall incidents at work: a visual analytics analysis of the research domain, International Journal of Environmental Research and Public Health, 16(24), 4972. https://doi.org/10.3390/ijerph16244972
  • Lilić, N., Obradović, I. and Cvjetić, A. (2010) An intelligent hybrid system for surface coal mine safety analysis, Engineering Applications of Artificial Intelligence 23(4):453–462. https://doi.org/10.1016/j.engappai.2010.01.025
  • Liberty Mutual (2021). Liberty Mutual Workplace Safety Index 2021. Access Address: https://business.libertymutual.com/ wp-content/uploads/2021/06/ 2021_ WSI_ 1000 _R2.pdf (Access Date: 23.11.2022)
  • Meciarova J. (2011) Expert system for assessing health hazards of metalworking fluids, Annals of DAAAM for 2011 & proceedings of the 22nd International DAAAM Symposium, 22, Vienna, Austria
  • Mohan, S., Anand, A., Ul Haq, M. I., Raina, A., Kumar, R. and Kamal, M. (2020) Development of a NIOSH based software tool for musculoskeletal disorders. Indian Journal of Engineering and Materials Sciences (IJEMS), 27(4), 860–865.
  • Motorcu, A. R. and Murat, B. (2021a) İş kazası etmeni olarak kayma, tökezleme ve düşme (KTD): Türkiye incelemesi. Mühendislik ve Multidisipliner Yaklaşımlar, 572–592. Güven Plus A.Ş.
  • Motorcu, A. R. and Murat, B. (2021b). Yeni işyeri riskleri ve yapay zekanin iş sağliği ve güvenliğinde kullanimi. Mühendislik ve Multidisipliner Yaklaşımlar 369–402. Güven Plus A.Ş.
  • Murat, B., Motorcu, A. R. and Kayır, Y. (2022) Uzman sistem çalışmalarının bibliyometrik analizi ve iş sağliği güvenliğinde uygulama örnekleri. İş Güvenliği ve Çalışan Sağlığı, 222–247. Güven Plus A.Ş.
  • Nenonen, N. (2013) Analysing factors related to slipping, stumbling, and falling accidents at work: application of data mining methods to Finnish occupational accidents and diseases statistics database, Applied Ergonomics, 44(2), 215–224. https://doi.org/10.1016/j.apergo.2012.07.001
  • Newaz, M.T., Ershadi, M, Jefferies, M. Pillay, M. and Davis, P. (2023) A Systematic review of contemporary safety management research: a multi-level approach to identifying trending domains in the construction industry, Construction Management and Economics, 41 (2), 97–115. https://doi.org/10.1080/01446193.2022.2124527
  • Pac, M., Mikutskaya, I. and Mulawka, J. (2021) Knowledge discovery from medical data and development of an expert system in immunology, Entropy, 23(6). https://doi.org/10.3390/e23060695
  • Pawłowska, Z. (2010) Occupational Risk Assessment, Boca Raton, FL: CRC Press/Taylor & Francis (Human factors and ergonomics).
  • Popovic, V., Larue, G. S., Legge, M., Brophy, C. and Blackman, R. (2023) Risk mitigation at train stations: underlying causes of slips, trips, and falls for passengers with reduced mobility, Ergonomics, 1–22. https://doi.org/10.1080/00140139.2023.2195139
  • Qiu, S., Sallak, M., Schön, W. and Ming, H. X. (2018) A Valuation-based system approach for risk assessment of belief rule-based expert systems, Information Sciences, 466, 323–336. https://doi.org/10.1016/j.ins.2018.04.039
  • Pavlovic-Veselinovic, S., Hedge, A. and Veselinovic, M. (2016) An ergonomic expert system for risk assessment of work-related musculo-skeletal disorders, International Journal of Industrial Ergonomics, 53:130–139. https://doi.org/10.1016/j.ergon.2015.11.008.
  • Rasmussen, J. and Svedung, I. (2000) Proactive Risk Management in a Dynamic Society. First Edition. Sweden.
  • Richards, G. (2018) Warehouse Management: A Complete Guide to Improving Efficiency and Minimizing Costs in the Modern Warehouse (3rd ed.), Kogan Page Limited.
  • Rostamy, AAA. and Ghatari, AR. (2023) An expert system to evaluate the impacts of health, safety, and environment system implementation on firms’ financial performance using analytic network process and promethee techniques, Green and Low-Carbon Economy. https://doi.org/10.47852/bonviewGLCE32021448
  • Rubel, A. K. M., Sultana, S., Alam, A. M. U., Nizam, S., Yasmin, R., Ahmad, S. A. and Faruquee, M. H. (2021). Slips, trips and falls among the workers in a garment industry in Dhaka, Bangladesh, International Journal of Occupational Safety and Health, 11(1), 40–47. https://doi.org/10.3126/ijosh.v11i1.36062
  • Sarı, K., Kayır, Y. and Dilipak, H. (2023) An Expert system for bolt selection, Bilişim Teknolojileri Dergisi, 16(2), 83–94. https://doi.org/10.17671/gazibtd.1195078
  • Sattari, F., Macciotta, R., Kurian, D. and Lefsrud, L. (2021) Application of bayesian network and artificial intelligence to reduce accident/incident rates in oil and gas companies, Safety Science, 133. https://doi.org/10.1016/j.ssci.2020.104981
  • Stamatelatos, M., Dezfuli, H., Apostolakis, G., Everline, C., Guarro, S., Mathias, D., Mosleh, A. (2011) Probabilistic risk assessment procedures guide for NASA managers and practitioners (Second Edition), NASA.
  • Stellman, J. M., Rau, S., Thaker, P. (2021) Occupational safety and health management, Handbook of Human Factors And Ergonomics. 5th ed. Hoboken, New Jersey: https://doi.org/10.1002/9781119636113.ch21
  • Suryono, S, Surarso, B., Saputra, R. and Sudalma, S. (2019) Real-time decision support system for carbon monoxide threat warning using online expert system, Journal of Applied Engineering Sciences, 17(1):18–25. https://doi.org/10.5937/jaes17-17429
  • Taçgın, E. and Sağır, Z. (2020) Development of an intelligent knowledge base for identification of accident causes based on Fu .et al.’s model, International Journal of Occupational Safety and Ergonomics, 1–18. https://doi.org/10.1080/10803548. 2020.1831786
  • Teke, Ç. (2022) Bireylerin koroner arter hastalığı risk seviyesinin bulanık uzman sistem yaklaşımı ile belirlenmesi, Zeki Sistemler Teori ve Uygulamaları Dergisi, 5(2), 153–160. https://doi.org/10.38016/jista.1144535
  • Tofiło, P., Konecki, M., Gałaj, J., Jaskółowski, W., Tuśnio, N. and Cisek, M.(2013) Expert system for building fire safety analysis and risk assessment, Procedia Engineering, 57, 1156-1165. https://doi.org/10.1016/j.proeng.2013.04.146
  • Teke, Ç. (2024) Green supplier assessment with fuzzy expert system approach, Türk Doğa ve Fen Dergisi, 13(1), 40-46. https://doi.org/10.46810/tdfd.1350936
  • Urrea, C. and Mignogna, A. (2020) Development of an expert system for pre-diagnosis of hypertension, diabetes mellitus type 2 and metabolic syndrome, Health Informatics Journal, 26(4), 2776–2791. https://doi.org/10.1177/1460458220937095
  • Yoon, H.‑Y. and Lockhart, T. E. (2006) Nonfatal occupational injuries associated with slips and falls in the United States, International Journal of Industrial Ergonomics, 36(1), 83–92. https://doi.org/10.1016/j.ergon.2005.08.005
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makine Mühendisliği (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Bilal Murat 0000-0002-1257-3039

Ali Riza Motorcu 0000-0002-9129-8935

Yunus Kayır 0000-0001-6793-7103

Erken Görünüm Tarihi 11 Nisan 2025
Yayımlanma Tarihi 28 Nisan 2025
Gönderilme Tarihi 20 Eylül 2024
Kabul Tarihi 5 Ocak 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 30 Sayı: 1

Kaynak Göster

APA Murat, B., Motorcu, A. R., & Kayır, Y. (2025). DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, 30(1), 17-34. https://doi.org/10.17482/uumfd.1553249
AMA Murat B, Motorcu AR, Kayır Y. DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. UUJFE. Nisan 2025;30(1):17-34. doi:10.17482/uumfd.1553249
Chicago Murat, Bilal, Ali Riza Motorcu, ve Yunus Kayır. “DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 30, sy. 1 (Nisan 2025): 17-34. https://doi.org/10.17482/uumfd.1553249.
EndNote Murat B, Motorcu AR, Kayır Y (01 Nisan 2025) DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 30 1 17–34.
IEEE B. Murat, A. R. Motorcu, ve Y. Kayır, “DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES”, UUJFE, c. 30, sy. 1, ss. 17–34, 2025, doi: 10.17482/uumfd.1553249.
ISNAD Murat, Bilal vd. “DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi 30/1 (Nisan 2025), 17-34. https://doi.org/10.17482/uumfd.1553249.
JAMA Murat B, Motorcu AR, Kayır Y. DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. UUJFE. 2025;30:17–34.
MLA Murat, Bilal vd. “DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES”. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, c. 30, sy. 1, 2025, ss. 17-34, doi:10.17482/uumfd.1553249.
Vancouver Murat B, Motorcu AR, Kayır Y. DEVELOPMENT OF AN ARTIFICIAL INTELLIGENCE-BASED PROGRAM FOR ENSURING WORKPLACE SAFETY AND ANALYZING SLIP, TRIP, AND FALL RISKS IN WAREHOUSES. UUJFE. 2025;30(1):17-34.

DUYURU:

30.03.2021- Nisan 2021 (26/1) sayımızdan itibaren TR-Dizin yeni kuralları gereği, dergimizde basılacak makalelerde, ilk gönderim aşamasında Telif Hakkı Formu yanısıra, Çıkar Çatışması Bildirim Formu ve Yazar Katkısı Bildirim Formu da tüm yazarlarca imzalanarak gönderilmelidir. Yayınlanacak makalelerde de makale metni içinde "Çıkar Çatışması" ve "Yazar Katkısı" bölümleri yer alacaktır. İlk gönderim aşamasında doldurulması gereken yeni formlara "Yazım Kuralları" ve "Makale Gönderim Süreci" sayfalarımızdan ulaşılabilir. (Değerlendirme süreci bu tarihten önce tamamlanıp basımı bekleyen makalelerin yanısıra değerlendirme süreci devam eden makaleler için, yazarlar tarafından ilgili formlar doldurularak sisteme yüklenmelidir).  Makale şablonları da, bu değişiklik doğrultusunda güncellenmiştir. Tüm yazarlarımıza önemle duyurulur.

Bursa Uludağ Üniversitesi, Mühendislik Fakültesi Dekanlığı, Görükle Kampüsü, Nilüfer, 16059 Bursa. Tel: (224) 294 1907, Faks: (224) 294 1903, e-posta: mmfd@uludag.edu.tr