ERGONOMİ 4.0 VE AKILLI FABRİKALAR: YENİ İŞ TASARIMINA YÖNELİK İNSAN FAKTÖRÜ TEMELLİ BİR ÖLÇEK ÖNERİSİ
Yıl 2023,
Cilt: 34 Sayı: 1, 109 - 140, 27.04.2023
Burcu Yılmaz Kaya
,
Aylin Adem
,
Metin Dağdeviren
Öz
Son yıllarda süreçlerde yaşanan hızlı dijitalleşme etkileri ile sistemler için yeni teknolojiler geliştirilirken iş sistemi tasarımları da bu hızlı değişimden payını almaktadır. İşçi refahı ile endüstriyel sistem üretkenliği arasındaki güçlü ilişkiye bağlı olarak Endüstri Mühendisliği literatüründe ergonomi ve insan faktörleri mühendisliğine olan ilgi artmaktadır. Endüstri 4.0 uygulamalarını iş sistemlerinde hayata geçirebilmek ve iş tasarımını uyarlayabilmek için bilimsel araştırmacılar ve yöneticiler risk faktörlerinin değerlendirmesi ve ergonomik düzenlemelerin gerçekleştirilmesi için geleneksel bakış açısı ile gelişmekte olan yeni teknolojiyi entegre eden, aynı zamanda mevcut sistemde var olan fiziksel ergonomik riski dengelemek ve azaltmak için müdahaleler öneren yaklaşımlar geliştirmelidir. Bu çalışmada Endüstri 4.0 bileşenlerinden akıllı fabrika ve akıllı üretim alanlarına geçiş süreçlerinde iş tasarımında fiziksel risk seviyesini azaltarak iş ve iş yerinin ergonomik uygunluğu arttıracak sistem tasarımı için işbirlikçi robot (collaborative robot–Cobot) teknolojilerinin kullanımı ele alınmıştır. Çalışmada Cobot teknolojisinin atanacağı iş istasyonu seçiminde dikkat edilmesi gereken faktörler araştırılarak insan-robot etkileşimli üretim hatlarında gerçekleştirilecek uygulamalar için bir uygunluk skalası geliştirilmiştir.
Kaynakça
- Adar T. ve Delice E. (2019). New integrated approaches based on MC-HFLTS for healthcare waste treatment technology selection, Journal of Enterprise Information Management, 32 (4), 688-711. Doi: https://doi.org/10.1108/JEIM-10-2018-0235
- Adem, A., Kaya, B. Y. ve Dağdeviren, M. (2021) Analyzing The OHS Risks Emerged in Transportation of Medical Materials in The Covid-19 Pandemic. 19th International Logistics and Supply Chain Congress, 348-358, Gaziantep, Türkiye.
- Adem, A., Yilmaz Kaya, B. ve Dağdeviren, M. (2022). Intelligent and Fuzzy Techniques in Aviation 4.0. Studies in Systems: Decision and control technology analysis for Logistics 4.0 applications: Criteria affecting UAV performances. Springer, Cham. Doi: https://doi.org/10.1007/978-3-030-75067-1_21
- Adriaensen, A., Costantino, F., Di Gravio, G. ve Patriarca, R. (2022). Teaming with industrial cobots: A socio‐technical perspective on safety analysis. Human Factors and Ergonomics in Manufacturing & Service Industries, 32(2), 173-198. Doi: https://doi.org/10.1002/hfm.20939 .
- Al-Hamouz, S. O. El-Omari, N. K. ve Al-Naimat, A. M. (2019) An ISO compliant safety system for human workers in human-robot interaction work environment, 12th International Conference on Developments in eSystems Engineering (DeSE). 9-14, Kazan, Rusya, Doi: https://doi.org/10.1109/DeSE.2019.00012
- Ashtiani, M. ve Azgomi, M. A. (2016). A hesitant fuzzy model of computational trust considering hesitancy, vagueness and uncertainty. Applied Soft Computing, 42, 18-37. Doi: https://doi.org/10.1016/j.asoc.2016.01.023.
- Ayyıldız, E. (2021). Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era. Environmental Science and Pollution Research, 30, 42476–42494. Doi: https://doi.org/10.1007/s11356-021-16972-y
- Borboni, A., Elamvazuthi, I. ve Cusano, N. (2022). EEG-Based Empathic Safe Cobot. Machines, 10(8), 603. Doi: https://doi.org/10.3390/machines10080603
- Bortolini, M., Faccio, M., Gamberi, M ve Pilati, F. (2020). Motion Analysis System (MAS) for production and ergonomics assessment in the manufacturing processes. Computers & Industrial Engineering, 139, 105485. Doi: https://doi.org/10.1016/j.cie.2018.10.046
- Bortolini, M., Ferrari, E., Gamberi, M., Pilati, F. ve Faccio, M. (2017). Assembly system design in the Industry 4.0 era: a general framework. Ifac-Papersonline, 50(1), 5700-5705. Doi: https://doi.org/10.1016/j.ifacol.2017.08.1121
- Bozkuş, E., Kaya, İ ve Yakut, M. (2022). A fuzzy based model proposal on risk analysis for human-robot interactive systems. International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). 1-6. IEEE. Erişim adresi: https://ieeexplore.ieee.org/stamp/ stamp.jsp?arnumber=9799820.
- Büyüközkan, G., Feyzioğlu, O. ve Göçer, F. (2018). Selection of sustainable urban transportation alternatives using an integrated intuitionistic fuzzy Choquet integral approach. Transportation Research Part D: Transport and Environment, 58, 186-207. Doi: https://doi.org/10.1016/j.trd.2017.12.005
- Can G. F. ve Delice E. (2018). A Task-Based Fuzzy İntegrated Mcdm Approach For Shopping Mall Selection Considering Universal Design Criteria. Soft Computing, 22(22), 7377-7397. Doi: https://doi.org/10.1007/s00500-018-3074-4
- Can, G. F. (2018). An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Human Factors And Ergonomics in Manufacturing & Service Industries, 28(3), 130-147. Doi: https://doi.org/10.1002/hfm.20729
- Caterino, M., Rinaldi, M., & Fera, M. (2023). Digital ergonomics: an evaluation framework for the ergonomic risk assessment of heterogeneous workers. International Journal of Computer Integrated Manufacturing, 36(2), 239-259. Doi: https://doi.org/10.1080/0951192x.2022.2090023
- Chander, G. P. ve Das, S. (2023). Hesitant T-spherical fuzzy linear regression model based decision making approach using gradient descent method. Engineering Applications of Artificial Intelligence, 122, 106074. Doi: https://doi.org/10.1016/j.engappai.2023.106074
- Chatterjee, P., Athawale, V.M. ve Chakraborty, S. (2010). Selection of industrial robots using compromise ranking and outranking methods, Robotics and Computer-Integrated Manufacturing, 26(5), 483–489. Doi: https://doi.org/10.1016/j.rcim.2010.03.007
- Chromjakova, F., Trentesaux, D. ve Kwarteng, M. A. (2021). Human and cobot cooperation ethics: The process management concept of the production workplace. Journal of Competitiveness. 13(3), 21-38. Doi: https://doi.org/10.7441/joc.2021.03.02
- Cohen, Y. Naseraldin, H. Chaudhuri, A. ve Pilati, F. (2019). Assembly systems in Industry 4.0 era: a road map to understand Assembly 4.0, Int. J. Adv. Manuf. Technol. 105, 4037–4054, Doi: https://doi.org/10.1007/s00170-019-04203-1.
- Colgate, J. E., Wannasuphoprasit, W. ve Peshkin, M. A. (1996). Cobots: Robots for collaboration with human operators. ASME international mechanical engineering congress and exposition. 55, 433-439, Atlanta. Erişim adresi: https://peshkin.mech.northwestern.edu/publications/1996_Colgate_CobotsRobotsCollaboration.pdf.
- Dalay, M. ve Sarı, K. (2022). Tedarikçi Seçiminde Yeşil Kriterin Öneminin Araştırılması: Türk Gıda Sektörü Örneği. Endüstri Mühendisliği, 33 (3) , 500-513 . Doi: https://doi.org/10.46465/endustrimuhendisligi.1152540
- de Man, J. C. ve Strandhagen, J. O. (2017). An Industry 4.0 research agenda for sustainable business models. Procedia CIRP, 63, 721-726. Doi: https://doi.org/10.1016/j.procir.2017.03.315
- Dede, G. Mitropoulou, P. Nikolaidou, M. Kamalakis T. ve Michalakelis, C. (2020). Safety requirements for symbiotic human–robot collaboration systems in smart factories: a pairwise comparison approach to explore requirements dependencies. Requirements Engineering. 26(1), 115-141. Doi: https://doi.org/10.1007/s00766-020-00337-x
- Dekker, F., Salomons, A. ve Waal, J. V. D. (2017). Fear of
robots at work: the role of economic self-interest. Socio-Economic Review, 15(3), 539-562. Doi: https://doi.org/10.1093/ser/mwx005
- Delice E. ve Zegerek S. (2016). Ranking occupational risk levels of emergency departments using a new fuzzy mcdm model: A case study in Turkey, Applied Mathematics And Information Sciences.10(6), 2345-2356. Doi: https://doi.org/10.18576/amis/100638
- Deng, X., Li, W. ve Liu, Y. (2022). Hesitant fuzzy portfolio selection model with score and novel hesitant semi-variance. Computers & Industrial Engineering, 164, 107879. Doi: https://doi.org/10.1016/j.cie.2021.107879
- Devi, K. (2011). Extension of VIKOR method in intuitionistic fuzzy environment for robot selection.Expert Systems with Applications, 38(11), 14163-14168. Doi: https://doi.org/10.1016/j.eswa.2011.04.227
- Dilibal, S. ve Şahin, H. (2018). İşbirlikçi endüstriyel robotlar ve dijital endüstri. International Journal of 3D Printing Technologies and Digital Industry, 2(1), 86-96. Erişim adresi: https://dergipark.org.tr/tr/download/article-file/435679.
- Djuric, A. M., Urbanic, R. J. ve Rickli, J. L. (2016). A framework for collaborative robot (CoBot) integration in advanced manufacturing systems. SAE International Journal of Materials and Manufacturing, 9(2), 457-464. Doi: https://doi.org/10.4271/2016-01-0337
- Dong, M., Li, S. ve Zhang, H. (2015). Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP. Expert Systems with Applications, 42(21), 7846-7857. Doi: https://doi.org/10.1016/j.eswa.2015.06.007
- Eski, Ö. ve Uzun Araz, Ö. (2021). İyileştirme Projelerinin Bulanık Vikor Yöntemi İle Değerlendirilmesi. Endüstri Mühendisliği, 32 (3), 473-495. Erişim adresi : Https://Dergipark.Org.Tr/Tr/Pub/Endustrimuhendisligi/İssue/66238/955025
- Fang, B. (2023). Some uncertainty measures for probabilistic hesitant fuzzy information. Information Sciences. 625, 255-276, Doi: https://doi.org/10.1016/j.ins.2022.12.101
- Fast-Berglund, Å. Palmkvist, F. Nyqvist, P. Ekered S. ve Åkerman, M. (2016) Evaluating cobots for final assembly, Procedia CIRP. 44, 175–180, Doi: https://doi.org/10.1016/j.procir.2016.02.114
- Fournier, É., Kilgus, D., Landry, A., Hmedan, B., Pellier, D., Fiorino, H. ve Jeoffrion, C. (2022). The impacts of human-cobot collaboration on perceived cognitive load and usability during an industrial task: an exploratory experiment. IISE Transactions on Occupational Ergonomics and Human Factors, 10(2), 83-90. Doi: https://doi.org/10.1080/24725838.2022.2072021
- Garg, K., Pawar, P., Gosavi, J., Sharan N. ve More J. (2021). Industry 4.0 Integration with Industrial Engineering. 1st Indian International Conference on Industrial Engineering and Operations Management, Bangalore, India. Erişim adresi: https://www.ieomsociety.org/proceedings/2021india/215.pdf.
- Ghorabaee, M. K. (2016). Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing. 37, 221-232. Doi: https://doi.org/10.1016/j.rcim.2015.04.007
- Gil-Vilda, F., Sune, A., Yagüe-Fabra, J. A., Crespo, C. ve Serrano, H. (2017). Integration of a collaborative robot in a U-shaped production line: a real case study. Procedia Manufacturing, 13, 109-115. Doi: https://doi.org/10.1016/j.promfg.2017.09.015
- Guiochet, J., Machin, M. ve Waeselynck, H. (2017). Safety-critical advanced robots: A survey. Robotics and Autonomous Systems, 94, 43-52. Doi: https://doi.org/10.1016/j.robot.2017.04.004
- Guleria, A. ve Bajaj, R. K. (2020). T-spherical fuzzy graphs: operations and applications in various selection processes. Arabian Journal for Science and Engineering, 45(3), 2177-2193. Doi: https://doi.org/10.1007/s13369-019-04107-y
- Gül, S. (2021). Fermatean fuzzy set extensions of SAW, ARAS, and VIKOR with applications in COVID‐19 testing laboratory selection problem. Expert Systems, 38(8), e12769. Doi: https://doi.org/10.1111/exsy.12769.
- Gül, S. (2021). Hastane Yeri Seçiminde Nesnel Ağırlıklandırmalı Sezgisel Bulanık Vıkor Yöntemi. Endüstri Mühendisliği, 32(2), 177-200. Doi: https://doi.org/10.46465/endustrimuhendisligi.795479
- Hanna, A. Bengtsson, K. Götvall P. -L. ve Ekström, M. (2020). Towards safe human robot collaboration - Risk assessment of intelligent automation, 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 424-431, Doi: https://doi.org/10.1109/ETFA46521.2020.9212127
- Hata, A., Inam, R., Raizer, K., Wang, S. ve Cao, E. (2019). AI-based safety analysis for collaborative mobile robots. 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 1722-1729. Doi: https://doi.org/10.1109/ETFA.2019.8869263
- Hentout, A. Aouache, M. Maoudj, A. ve Akli, (2019). I. Human–robot interaction in industrial collaborative robotics: a literature review of the decade 2008–2017, Adv. Robot. 33, (15–16), 1–36, Doi: https://doi.org/10.1080/01691864.2019.1636714. https://www.globenewswire.com/news-release/2019/08/19/1903451/0/en/Digital-Transformation-in-Manufacturing-Market-to-hit-642-35-billion-by-2025-Analysis-by-Technology-and-Innovation-Landscape-Key-Initiatives-Case-Studies-and-Vendor-Outlook-Adroit-.html : “Technology and Innovation Landscape, Key Initiatives, Case Studies and Vendor Outlook: Adroit Market Research”
- ISO 10218 “Robots and robotic devices – Safety requirements for industrial robots”, with parts 1 (“Robots”) and 2 (“Robot systems and integration”), ISO Copyright Office, Geneva, 2011.
- ISO/TS 15066, “Robots and robotic devices - Collaborative robots,” 2016.
- URL:https://www.sis.se/en/produkter/manufacturing-engineering/industrial-automation-systems/industrial-robots-manipulators/isots150662016 .
- Jiao, H. (2020). Selection of resettlement site in reservoir construction using Pythagorean fuzzy MULTIMOORA multi-criteria decision-making method. Journal of Coastal Research, 115(SI), 502-505. Doi: https://doi.org/10.2112/JCR-SI115-138.1
- Johansson, A., Christiernin, L. G. ve Pejryd, L. (2016). Manufacturing system design for business value, a holistic design approach. Procedia CIRP, 50, 659-664. Doi: https://doi.org/10.1016/j.procir.2016.04.140
- Kasap, S. S. , Şahin, Y. ve Çınar, T. (2020). Bulanık Tabanlı Çok Kriterli Karar Verme Teknikleri İle Demirçelik Endüstrisinde En Uygun Yatırım Seçeneğinin Belirlenmesi. Endüstri Mühendisliği, I.EİM Kongresi, 59-71. Erişim adresi : https://dergipark.org.tr/tr/pub/endustrimuhendisligi/issue/52861/641077
- Keršuliené, V., Zavadskas, E. K. ve Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. Doi: https://doi.org/10.3846/jbem. 2010.12
- Kim, W. Peternel, L. Lorenzini, M. Babič J. ve Ajoudani, A. (2021). A Human-Robot Collaboration Framework for Improving Ergonomics During Dexterous Operation of Power Tools, Robotics and Computer-Integrated Manufacturing, 68, 102084, doi: https://doi.org/10.1016/j.rcim.2020.102084
- Koch, P. J., van Amstel, M. K., Dębska, P., Thormann, M. A., Tetzlaff, A. J., Bøgh, S. ve Chrysostomou, D. (2017). A Skill-based Robot Co-worker for Industrial Maintenance Tasks. Procedia Manufacturing, 11, 83-90. Doi: https://doi.org/10.1016/j.promfg.2017.07.141
- Komenda, T., Schmidbauer, C., Kames, D. ve Schlund, S. (2021). Learning to share-teaching the impact of flexible task allocation in human-cobot teams. Conference on Learning Factories (CLF). Graz, Avusturya. Doi: https://doi.org/10.2139/ssrn.3869551
- Kopp, T. Baumgartner, M. ve Kinkel, S. (2021) Success factors for introducing industrial human–robot interaction in practice: an empirically driven framework, Int. J. Adv. Manuf. Technol. 112, 685–704, Doi: https://doi.org/10.1007/s00170-020-06398-0
- Lee, H. J., Kim, J. S. ve Kim, H. W. (2019). Analysis of artificial intelligence technology based on the requirements of collaborative robots through patent analysis. ICIC Express Letters, 13(6), 521-527. Doi: https://doi.org/10.24507/icicel.13.06.521.
- Liu, B., Fu, W., Wang, W., Li, R., Gao, Z., Peng, L. ve Du, H. (2022) Cobot Motion Planning Algorithm for Ensuring Human Safety Based on Behavioral Dynamics. Sensors, 22, 4376. Doi: https://doi.org/10.3390/s22124376.
- Liu, Z., Wang, X., Cai, Y., Xu, W., Liu, Q., Zhou, Z. ve Pham, D. T. (2020). Dynamic risk assessment and active response strategy for industrial human-robot collaboration. Computers & Industrial Engineering, 141, 106302. Doi: https://doi.org/10.1016/j.cie.2020.106302
- Ly, P. T. M., Lai, W. H., Hsu, C. W. ve Shih, F. Y. (2018). Fuzzy AHP analysis of Internet of Things (IoT) in enterprises. Technological Forecasting and Social Change, 136(C), 1-13. Doi: https://doi.org/10.1016/j.techfore.2018.08.016
- Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. Doi: https://doi.org/10.1016/j.futures.2017.03.006.
- McClure, P. K. (2018). “You’re fired,” says the robot: The rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), 139-156. Doi: https://doi.org/10.1177/0894439317698637.
- Mo, H. (2021). A SWOT method to evaluate safety risks in life cycle of wind turbine extended by D number theory. Journal of Intelligent & Fuzzy Systems, 40(3), 4439-4452. Doi: https://doi.org/10.3233/JIFS-201277.
- Nordander, C., Ohlsson, K., Balogh, I., Hansson, G-A ̊, Axmon, A., Persson, R. ve Skerfving, S. (2008). Gender differences in workers with identical repetitive industrial tasks: exposure and musculoskeletal disorders. Int Arch Occup Environ Health 81:939–94. Doi: https://doi.org/10.1007/s00420-007-0286-9.
- Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990. Doi: https://doi.org/10.1016/j.eswa.2011.04.097
Otto, A. ve Scholl, A. (2013). Reducing ergonomic risks by job rotation scheduling. OR spectrum, 35, 711-733. Doi: https://doi.org/10.1007/s00291-012-0291-6.
- Özcan, S. G. , Yıldızbası, A. ve Eraslan, E. (2019). İnşaat Firmalarının İSG Bağlamında Bulanık Grup Karar Verme Yaklaşımı ile Değerlendirilmesi. Endüstri Mühendisliği, 30(3), 204-219. Erişim adresi: https://dergipark.org.tr/tr/pub/endustrimuhendisligi/issue/50398/606553
- Paliga, M. (2022). Human–cobot interaction fluency and cobot operators’ job performance. The mediating role of work engagement: A survey. Robotics and Autonomous Systems, 155, 104191. Doi: https://doi.org/10.1016/j.robot.2022.104191.
- Pant, M. ve Kumar, S. (2022). Particle swarm optimization and intuitionistic fuzzy set-based novel method for fuzzy time series forecasting. Granular Computing, 7(2), 285-303. Doi: https://doi.org/10.1007/s41066-021-00265-3.
- Papetti, A., Ciccarelli, M., Scoccia, C. ve Germani, M. (2021). A multi-criteria method to design the collaboration between humans and robots. Procedia CIRP, 104, 939-944. Doi: https://doi.org/10.1016/j.procir.2021.11.158
- Parameshwaran, R., Kumar, S. P. ve Saravanakumar, K. (2015). An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria. Applied Soft Computing, 26, 31-41. Doi: https://doi.org/10.1016/j.asoc.2014.09.025.
- Park, K. C. ve Shin, D. H. (2017). Security assessment framework for IoT service, Telecommunication Systems, 64(1), 193-209. Doi: https://doi.org/10.1007/s11235-016-0168-0 .
- Peng, X. ve Yang, Y. (2015). Some results for Pythagorean fuzzy sets. International Journal of Intelligent Systems, 30(11), 1133-1160. Doi: 10.1002/int.21738.
- Peng, X. ve Yuan, H. (2016). Fundamental properties of Pythagorean fuzzy aggregation operators. Fundamenta Informaticae, 147(4), 415-446. Doi: https://doi.org/10.1002/int.21790 .
- Perçin, S. (2023). Identifying barriers to big data analytics adoption in circular agri-food supply chains: a case study in Turkey. Environmental Science and Pollution Research, 1-17. Doi: https://doi.org/10.1007/s11356-023-26091-5
- Putz-Anderson, V., Bernard, B. P., Burt, S. E., Cole, L. L., Fairfield-Estill, C., Fine, L. J., Grant, K.A., Gjessing, C., Jenkins, L., Hurrell Jr., J.J., Nelson, N., Pfirman, D., Roberts, R., Stetson, D., Haring-Sweeney, M. ve Tanaka, S. (1997). Musculoskeletal disorders and workplace factors. National Institute for Occupational Safety and Health (NIOSH), 104, 97-141. Erişim adresi: https://www.cdc.gov/niosh/docs/97-141/pdfs/97-141.pdf?id=10.26616/ NIOSHPUB97141.
- Rezagholi, M. ve Bantekas, A. (2015). Making economic social decisions for improving occupational health a predictive cost-benefit analysis. Occupational Medicine & Health Affairs. 3(06), 1000225, Doi: https://doi.org/10.4172/2329-6879.1000225.
- Savaş, E. (2016). On Generalized Double Statistical Convergence of Order α in Intuitionistic Fuzzy Normed Spaces. Mathematical and Computational Applications, 21(3), 36. Doi: https://doi.org/10.3390/mca21030036.
- Schou, C., Andersen, R.S., Chrysostomou, D., Bøgh, S. Ve Madsen, O. (2018). Skill-based instruction of collaborative robots in industrial settings, Robot. Comput. Integr. Manuf. 53 72–80, Doi: https://doi.org/10.1016/j.rcim.2018.03.008
- Scimmi, L. S., Melchiorre, M., Troise, M., Mauro, S. ve Pastorelli, S. (2021). A practical and effective layout for a safe human-robot collaborative assembly task. Applied Sciences, 11(4), 1763. Doi: https://doi.org/10.3390/app11041763 .
- Sharaf, I. M. ve Khalil, E. A. H. A. (2021). A spherical fuzzy TODIM approach for green occupational health and safety equipment supplier selection. International Journal of Management Science and Engineering Management, 16(1), 1-13. Doi: https://doi.org/10.1080/17509653.2020.1788467.
- Sriviboon, Y., & Jiamsanguanwong, A. Usability Evaluation and User Acceptance of Cobot: Case Study of Universal Robots CB Series. The International Conference on Industrial Engineering and Operations Management. Istanbul, Türkiye. Doi: https://doi.org/10.1145/3419249.3420161.
- Sumrit, D. (2020). Supplier selection for vendor-managed inventory in healthcare using fuzzy multi-criteria decision-making approach. Decision Science Letters, 9, 233–256. Doi: https://doi.org/10.5267/j.dsl.2019.10.002.
- Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert systems with applications, 37(12), 7745-7754. Doi: https://doi.org/10.1016/j.eswa.2010.04.066 .
- Veza, I., Mladineo, M., Kutlesa, M., Gjeldum, N., Bilic, B., Crnjac Zizic, M., Alinovic, A. ve Basic, A. (2022). Selection of the Cobot Workstation for the Learning Factory by using the Multi-Criteria Analysis. 12th Conference on Learning Factories, CLF2022, Singapur. Doi: https://doi.org/10.2139/ssrn.4072387
- Virgillito, M. E. (2017). Rise of the robots: Technology and the threat of a jobless future, Labor History, 58(2), 240-242.
- Vitolo, F., Rega, A., Di Marino, C., Pasquariello, A., Zanella, A. ve Patalano, S. (2022). Mobile Robots and Cobots Integration: A Preliminary Design of a Mechatronic Interface by Using MBSE Approach. Applied Sciences, 12(1), 419. Doi: https://doi.org/10.3390/app12010419.
- Vysocky, A. ve Novak, P. (2016). Human-robot collaboration in industry. MM Science Journal, 9(2), 903-906. Doi: https://doi.org/10.17973/MMSJ.2016_06_201611
- Yener, Y. ve Can, G. F. (2021). A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration. Expert Systems with Applications, 183, 115413. Doi: https://doi.org/10.1016/j.eswa.2021.115413.
- Yılmaz, B. ve Dağdeviren, M. (2010) Comparative analysis of PROMETHEE and fuzzy PROMETHEE methods in equipment selection problem. Journal of the Faculty of Engineering and Architecture of Gazi University, 25(4). Erişim adresi: https://dergipark.org.tr/tr/pub/gazimmfd/issue/6686/88606.
- Yılmaz, B. ve Dağdeviren, M. (2011). A combined approach for equipment selection: F-PROMETHEE method and zero–one goal programming. Expert Systems with Applications, 38(9), 11641-11650. Doi: https://doi.org/10.1016/j.eswa.2011.03.043.
- Yılmaz Kaya, B. (2022). Human factors engineerıng on the edge of Industry 4.0: Analysis for IoT-Aided technologies. Endüstri Mühendisliği, 33(1), 1-21. Doi: https://doi.org/10.46465/endustrimuhendisligi.1025701.
- Yılmaz Kaya, B. (2022). Contemplation and analysis of pandemic impacts on accommodation industry and a system reformulation proposal with Kano model: Turkey case. Current Issues in Tourism, 25(8), 1226-1241. Doi: https://doi.org/10.1080/13683500.2021.2007860
- Yılmaz Kaya, B. (2022). Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies. Discrete Dynamics in Nature and Society, 9511339. Doi: https://doi.org/10.1155/2022/9511339.
- Yılmaz Kaya, B. ve Dağdeviren, M. (2016). Selecting occupational safety equipment by MCDM approach considering universal design principles. Human Factors and Ergonomics in Manufacturing & Service Industries, 26(2), 224-242. Doi: https://doi.org/10.1002/hfm.20625
- Yılmaz Kaya, B. ve Dağdeviren, M. (2017) A fuzzy marketing strategy benchmarking analysis in service sector. The 5th International Fuzzy Systems Symposium, TOBB-ETU, Ankara, Türkiye.
- Yılmaz Kaya, B. ve Dağdeviren, M. (2019). A guiding analysis to accomplish the challenges for implementation of Industry 4.0. 10th International Symposium on Intelligent Manufacturing and Service Systems, 738-746, Sakarya, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2018). A human centered multi-criteria decision making approach proposition for priorization of ergonomic factors in terms of working productivity. The 12th International Conference on New Challenges in Industrial Engineering and Operations Management, Ankara, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2021). A Multi-criteria Approach to Usability Research for Digital Platforms in Fuzzy Environment. INFUS 2021 Conference, August 24-26, 2021. 417-425, İstanbul, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2022). Dijital ergonomi, akıllı fabrikalar ve işbirlikçi robot uygulamaları. 28. Ulusal Ergonomi Kongresi, 14-16 Ekim, Eskişehir, Türkiye.
- Yücesan, M. ve Gül, M. (2020). Hospital service quality evaluation: An integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Computing, 24(5), 3237-3255. Doi: https://doi.org/10.1007/s00500-019-04084-2.
- Zacharaki, A., Kostavelis, I., Gasteratos, A. ve Dokas, I. (2020). Safety bounds in human robot interaction: A survey. Safety science, 127, 104667. Doi: https://doi.org/10.1016/j.ssci.2020.104667.
- Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353. Doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
- Zhang, Z. (2016). Some hesitant multiplicative aggregation operators and their application in group decision making with hesitant multiplicative preference relations. International Journal of Fuzzy Systems, 18(2), 177-197. Doi: https://doi.org/10.1007/s40815-016-0158-0.
ERGONOMICS 4.0 AND SMART FACTORIES: A HUMAN FACTORS BASED SCALE PROPOSITION FOR THE NEW JOB DESIGN
Yıl 2023,
Cilt: 34 Sayı: 1, 109 - 140, 27.04.2023
Burcu Yılmaz Kaya
,
Aylin Adem
,
Metin Dağdeviren
Öz
With the rapid digitalization effect experienced recently, new technologies have been developed for systems, where, system design has also taken its share from this rapid change. Due to the strong relationship between employee welfare and industrial system productivity, there is an increasing interest in ergonomics and human factors engineering fields in Industrial Engineering literature. In order to implement Industry 4.0 applications in work systems and adapt the job design, scientific researchers and managers are integrating the traditional point of view and developing new technology for the evaluation of risk factors as well as realization of ergonomic regulations, while at the same time suggesting interventions to balance and reduce the physical ergonomic risk existing in the current system. approaches should be developed. In this study, the use of collaborative robot (Cobot) technologies for system design that will increase the ergonomic suitability of the work system and workplace by reducing the level of physical risk in job design during the transformation to smart factory and smart production areas as Industry 4.0 componenta is discussed. In the study, a suitability scale was developed for the applications to be realized in human-robot interactive production lines by investigating the factors that should be considered in the selection of the workstation to which the Cobot technology will be assigned.
Kaynakça
- Adar T. ve Delice E. (2019). New integrated approaches based on MC-HFLTS for healthcare waste treatment technology selection, Journal of Enterprise Information Management, 32 (4), 688-711. Doi: https://doi.org/10.1108/JEIM-10-2018-0235
- Adem, A., Kaya, B. Y. ve Dağdeviren, M. (2021) Analyzing The OHS Risks Emerged in Transportation of Medical Materials in The Covid-19 Pandemic. 19th International Logistics and Supply Chain Congress, 348-358, Gaziantep, Türkiye.
- Adem, A., Yilmaz Kaya, B. ve Dağdeviren, M. (2022). Intelligent and Fuzzy Techniques in Aviation 4.0. Studies in Systems: Decision and control technology analysis for Logistics 4.0 applications: Criteria affecting UAV performances. Springer, Cham. Doi: https://doi.org/10.1007/978-3-030-75067-1_21
- Adriaensen, A., Costantino, F., Di Gravio, G. ve Patriarca, R. (2022). Teaming with industrial cobots: A socio‐technical perspective on safety analysis. Human Factors and Ergonomics in Manufacturing & Service Industries, 32(2), 173-198. Doi: https://doi.org/10.1002/hfm.20939 .
- Al-Hamouz, S. O. El-Omari, N. K. ve Al-Naimat, A. M. (2019) An ISO compliant safety system for human workers in human-robot interaction work environment, 12th International Conference on Developments in eSystems Engineering (DeSE). 9-14, Kazan, Rusya, Doi: https://doi.org/10.1109/DeSE.2019.00012
- Ashtiani, M. ve Azgomi, M. A. (2016). A hesitant fuzzy model of computational trust considering hesitancy, vagueness and uncertainty. Applied Soft Computing, 42, 18-37. Doi: https://doi.org/10.1016/j.asoc.2016.01.023.
- Ayyıldız, E. (2021). Interval valued intuitionistic fuzzy analytic hierarchy process-based green supply chain resilience evaluation methodology in post COVID-19 era. Environmental Science and Pollution Research, 30, 42476–42494. Doi: https://doi.org/10.1007/s11356-021-16972-y
- Borboni, A., Elamvazuthi, I. ve Cusano, N. (2022). EEG-Based Empathic Safe Cobot. Machines, 10(8), 603. Doi: https://doi.org/10.3390/machines10080603
- Bortolini, M., Faccio, M., Gamberi, M ve Pilati, F. (2020). Motion Analysis System (MAS) for production and ergonomics assessment in the manufacturing processes. Computers & Industrial Engineering, 139, 105485. Doi: https://doi.org/10.1016/j.cie.2018.10.046
- Bortolini, M., Ferrari, E., Gamberi, M., Pilati, F. ve Faccio, M. (2017). Assembly system design in the Industry 4.0 era: a general framework. Ifac-Papersonline, 50(1), 5700-5705. Doi: https://doi.org/10.1016/j.ifacol.2017.08.1121
- Bozkuş, E., Kaya, İ ve Yakut, M. (2022). A fuzzy based model proposal on risk analysis for human-robot interactive systems. International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). 1-6. IEEE. Erişim adresi: https://ieeexplore.ieee.org/stamp/ stamp.jsp?arnumber=9799820.
- Büyüközkan, G., Feyzioğlu, O. ve Göçer, F. (2018). Selection of sustainable urban transportation alternatives using an integrated intuitionistic fuzzy Choquet integral approach. Transportation Research Part D: Transport and Environment, 58, 186-207. Doi: https://doi.org/10.1016/j.trd.2017.12.005
- Can G. F. ve Delice E. (2018). A Task-Based Fuzzy İntegrated Mcdm Approach For Shopping Mall Selection Considering Universal Design Criteria. Soft Computing, 22(22), 7377-7397. Doi: https://doi.org/10.1007/s00500-018-3074-4
- Can, G. F. (2018). An intutionistic approach based on failure mode and effect analysis for prioritizing corrective and preventive strategies. Human Factors And Ergonomics in Manufacturing & Service Industries, 28(3), 130-147. Doi: https://doi.org/10.1002/hfm.20729
- Caterino, M., Rinaldi, M., & Fera, M. (2023). Digital ergonomics: an evaluation framework for the ergonomic risk assessment of heterogeneous workers. International Journal of Computer Integrated Manufacturing, 36(2), 239-259. Doi: https://doi.org/10.1080/0951192x.2022.2090023
- Chander, G. P. ve Das, S. (2023). Hesitant T-spherical fuzzy linear regression model based decision making approach using gradient descent method. Engineering Applications of Artificial Intelligence, 122, 106074. Doi: https://doi.org/10.1016/j.engappai.2023.106074
- Chatterjee, P., Athawale, V.M. ve Chakraborty, S. (2010). Selection of industrial robots using compromise ranking and outranking methods, Robotics and Computer-Integrated Manufacturing, 26(5), 483–489. Doi: https://doi.org/10.1016/j.rcim.2010.03.007
- Chromjakova, F., Trentesaux, D. ve Kwarteng, M. A. (2021). Human and cobot cooperation ethics: The process management concept of the production workplace. Journal of Competitiveness. 13(3), 21-38. Doi: https://doi.org/10.7441/joc.2021.03.02
- Cohen, Y. Naseraldin, H. Chaudhuri, A. ve Pilati, F. (2019). Assembly systems in Industry 4.0 era: a road map to understand Assembly 4.0, Int. J. Adv. Manuf. Technol. 105, 4037–4054, Doi: https://doi.org/10.1007/s00170-019-04203-1.
- Colgate, J. E., Wannasuphoprasit, W. ve Peshkin, M. A. (1996). Cobots: Robots for collaboration with human operators. ASME international mechanical engineering congress and exposition. 55, 433-439, Atlanta. Erişim adresi: https://peshkin.mech.northwestern.edu/publications/1996_Colgate_CobotsRobotsCollaboration.pdf.
- Dalay, M. ve Sarı, K. (2022). Tedarikçi Seçiminde Yeşil Kriterin Öneminin Araştırılması: Türk Gıda Sektörü Örneği. Endüstri Mühendisliği, 33 (3) , 500-513 . Doi: https://doi.org/10.46465/endustrimuhendisligi.1152540
- de Man, J. C. ve Strandhagen, J. O. (2017). An Industry 4.0 research agenda for sustainable business models. Procedia CIRP, 63, 721-726. Doi: https://doi.org/10.1016/j.procir.2017.03.315
- Dede, G. Mitropoulou, P. Nikolaidou, M. Kamalakis T. ve Michalakelis, C. (2020). Safety requirements for symbiotic human–robot collaboration systems in smart factories: a pairwise comparison approach to explore requirements dependencies. Requirements Engineering. 26(1), 115-141. Doi: https://doi.org/10.1007/s00766-020-00337-x
- Dekker, F., Salomons, A. ve Waal, J. V. D. (2017). Fear of
robots at work: the role of economic self-interest. Socio-Economic Review, 15(3), 539-562. Doi: https://doi.org/10.1093/ser/mwx005
- Delice E. ve Zegerek S. (2016). Ranking occupational risk levels of emergency departments using a new fuzzy mcdm model: A case study in Turkey, Applied Mathematics And Information Sciences.10(6), 2345-2356. Doi: https://doi.org/10.18576/amis/100638
- Deng, X., Li, W. ve Liu, Y. (2022). Hesitant fuzzy portfolio selection model with score and novel hesitant semi-variance. Computers & Industrial Engineering, 164, 107879. Doi: https://doi.org/10.1016/j.cie.2021.107879
- Devi, K. (2011). Extension of VIKOR method in intuitionistic fuzzy environment for robot selection.Expert Systems with Applications, 38(11), 14163-14168. Doi: https://doi.org/10.1016/j.eswa.2011.04.227
- Dilibal, S. ve Şahin, H. (2018). İşbirlikçi endüstriyel robotlar ve dijital endüstri. International Journal of 3D Printing Technologies and Digital Industry, 2(1), 86-96. Erişim adresi: https://dergipark.org.tr/tr/download/article-file/435679.
- Djuric, A. M., Urbanic, R. J. ve Rickli, J. L. (2016). A framework for collaborative robot (CoBot) integration in advanced manufacturing systems. SAE International Journal of Materials and Manufacturing, 9(2), 457-464. Doi: https://doi.org/10.4271/2016-01-0337
- Dong, M., Li, S. ve Zhang, H. (2015). Approaches to group decision making with incomplete information based on power geometric operators and triangular fuzzy AHP. Expert Systems with Applications, 42(21), 7846-7857. Doi: https://doi.org/10.1016/j.eswa.2015.06.007
- Eski, Ö. ve Uzun Araz, Ö. (2021). İyileştirme Projelerinin Bulanık Vikor Yöntemi İle Değerlendirilmesi. Endüstri Mühendisliği, 32 (3), 473-495. Erişim adresi : Https://Dergipark.Org.Tr/Tr/Pub/Endustrimuhendisligi/İssue/66238/955025
- Fang, B. (2023). Some uncertainty measures for probabilistic hesitant fuzzy information. Information Sciences. 625, 255-276, Doi: https://doi.org/10.1016/j.ins.2022.12.101
- Fast-Berglund, Å. Palmkvist, F. Nyqvist, P. Ekered S. ve Åkerman, M. (2016) Evaluating cobots for final assembly, Procedia CIRP. 44, 175–180, Doi: https://doi.org/10.1016/j.procir.2016.02.114
- Fournier, É., Kilgus, D., Landry, A., Hmedan, B., Pellier, D., Fiorino, H. ve Jeoffrion, C. (2022). The impacts of human-cobot collaboration on perceived cognitive load and usability during an industrial task: an exploratory experiment. IISE Transactions on Occupational Ergonomics and Human Factors, 10(2), 83-90. Doi: https://doi.org/10.1080/24725838.2022.2072021
- Garg, K., Pawar, P., Gosavi, J., Sharan N. ve More J. (2021). Industry 4.0 Integration with Industrial Engineering. 1st Indian International Conference on Industrial Engineering and Operations Management, Bangalore, India. Erişim adresi: https://www.ieomsociety.org/proceedings/2021india/215.pdf.
- Ghorabaee, M. K. (2016). Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing. 37, 221-232. Doi: https://doi.org/10.1016/j.rcim.2015.04.007
- Gil-Vilda, F., Sune, A., Yagüe-Fabra, J. A., Crespo, C. ve Serrano, H. (2017). Integration of a collaborative robot in a U-shaped production line: a real case study. Procedia Manufacturing, 13, 109-115. Doi: https://doi.org/10.1016/j.promfg.2017.09.015
- Guiochet, J., Machin, M. ve Waeselynck, H. (2017). Safety-critical advanced robots: A survey. Robotics and Autonomous Systems, 94, 43-52. Doi: https://doi.org/10.1016/j.robot.2017.04.004
- Guleria, A. ve Bajaj, R. K. (2020). T-spherical fuzzy graphs: operations and applications in various selection processes. Arabian Journal for Science and Engineering, 45(3), 2177-2193. Doi: https://doi.org/10.1007/s13369-019-04107-y
- Gül, S. (2021). Fermatean fuzzy set extensions of SAW, ARAS, and VIKOR with applications in COVID‐19 testing laboratory selection problem. Expert Systems, 38(8), e12769. Doi: https://doi.org/10.1111/exsy.12769.
- Gül, S. (2021). Hastane Yeri Seçiminde Nesnel Ağırlıklandırmalı Sezgisel Bulanık Vıkor Yöntemi. Endüstri Mühendisliği, 32(2), 177-200. Doi: https://doi.org/10.46465/endustrimuhendisligi.795479
- Hanna, A. Bengtsson, K. Götvall P. -L. ve Ekström, M. (2020). Towards safe human robot collaboration - Risk assessment of intelligent automation, 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 424-431, Doi: https://doi.org/10.1109/ETFA46521.2020.9212127
- Hata, A., Inam, R., Raizer, K., Wang, S. ve Cao, E. (2019). AI-based safety analysis for collaborative mobile robots. 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 1722-1729. Doi: https://doi.org/10.1109/ETFA.2019.8869263
- Hentout, A. Aouache, M. Maoudj, A. ve Akli, (2019). I. Human–robot interaction in industrial collaborative robotics: a literature review of the decade 2008–2017, Adv. Robot. 33, (15–16), 1–36, Doi: https://doi.org/10.1080/01691864.2019.1636714. https://www.globenewswire.com/news-release/2019/08/19/1903451/0/en/Digital-Transformation-in-Manufacturing-Market-to-hit-642-35-billion-by-2025-Analysis-by-Technology-and-Innovation-Landscape-Key-Initiatives-Case-Studies-and-Vendor-Outlook-Adroit-.html : “Technology and Innovation Landscape, Key Initiatives, Case Studies and Vendor Outlook: Adroit Market Research”
- ISO 10218 “Robots and robotic devices – Safety requirements for industrial robots”, with parts 1 (“Robots”) and 2 (“Robot systems and integration”), ISO Copyright Office, Geneva, 2011.
- ISO/TS 15066, “Robots and robotic devices - Collaborative robots,” 2016.
- URL:https://www.sis.se/en/produkter/manufacturing-engineering/industrial-automation-systems/industrial-robots-manipulators/isots150662016 .
- Jiao, H. (2020). Selection of resettlement site in reservoir construction using Pythagorean fuzzy MULTIMOORA multi-criteria decision-making method. Journal of Coastal Research, 115(SI), 502-505. Doi: https://doi.org/10.2112/JCR-SI115-138.1
- Johansson, A., Christiernin, L. G. ve Pejryd, L. (2016). Manufacturing system design for business value, a holistic design approach. Procedia CIRP, 50, 659-664. Doi: https://doi.org/10.1016/j.procir.2016.04.140
- Kasap, S. S. , Şahin, Y. ve Çınar, T. (2020). Bulanık Tabanlı Çok Kriterli Karar Verme Teknikleri İle Demirçelik Endüstrisinde En Uygun Yatırım Seçeneğinin Belirlenmesi. Endüstri Mühendisliği, I.EİM Kongresi, 59-71. Erişim adresi : https://dergipark.org.tr/tr/pub/endustrimuhendisligi/issue/52861/641077
- Keršuliené, V., Zavadskas, E. K. ve Turskis, Z. (2010). Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management, 11(2), 243-258. Doi: https://doi.org/10.3846/jbem. 2010.12
- Kim, W. Peternel, L. Lorenzini, M. Babič J. ve Ajoudani, A. (2021). A Human-Robot Collaboration Framework for Improving Ergonomics During Dexterous Operation of Power Tools, Robotics and Computer-Integrated Manufacturing, 68, 102084, doi: https://doi.org/10.1016/j.rcim.2020.102084
- Koch, P. J., van Amstel, M. K., Dębska, P., Thormann, M. A., Tetzlaff, A. J., Bøgh, S. ve Chrysostomou, D. (2017). A Skill-based Robot Co-worker for Industrial Maintenance Tasks. Procedia Manufacturing, 11, 83-90. Doi: https://doi.org/10.1016/j.promfg.2017.07.141
- Komenda, T., Schmidbauer, C., Kames, D. ve Schlund, S. (2021). Learning to share-teaching the impact of flexible task allocation in human-cobot teams. Conference on Learning Factories (CLF). Graz, Avusturya. Doi: https://doi.org/10.2139/ssrn.3869551
- Kopp, T. Baumgartner, M. ve Kinkel, S. (2021) Success factors for introducing industrial human–robot interaction in practice: an empirically driven framework, Int. J. Adv. Manuf. Technol. 112, 685–704, Doi: https://doi.org/10.1007/s00170-020-06398-0
- Lee, H. J., Kim, J. S. ve Kim, H. W. (2019). Analysis of artificial intelligence technology based on the requirements of collaborative robots through patent analysis. ICIC Express Letters, 13(6), 521-527. Doi: https://doi.org/10.24507/icicel.13.06.521.
- Liu, B., Fu, W., Wang, W., Li, R., Gao, Z., Peng, L. ve Du, H. (2022) Cobot Motion Planning Algorithm for Ensuring Human Safety Based on Behavioral Dynamics. Sensors, 22, 4376. Doi: https://doi.org/10.3390/s22124376.
- Liu, Z., Wang, X., Cai, Y., Xu, W., Liu, Q., Zhou, Z. ve Pham, D. T. (2020). Dynamic risk assessment and active response strategy for industrial human-robot collaboration. Computers & Industrial Engineering, 141, 106302. Doi: https://doi.org/10.1016/j.cie.2020.106302
- Ly, P. T. M., Lai, W. H., Hsu, C. W. ve Shih, F. Y. (2018). Fuzzy AHP analysis of Internet of Things (IoT) in enterprises. Technological Forecasting and Social Change, 136(C), 1-13. Doi: https://doi.org/10.1016/j.techfore.2018.08.016
- Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. Doi: https://doi.org/10.1016/j.futures.2017.03.006.
- McClure, P. K. (2018). “You’re fired,” says the robot: The rise of automation in the workplace, technophobes, and fears of unemployment. Social Science Computer Review, 36(2), 139-156. Doi: https://doi.org/10.1177/0894439317698637.
- Mo, H. (2021). A SWOT method to evaluate safety risks in life cycle of wind turbine extended by D number theory. Journal of Intelligent & Fuzzy Systems, 40(3), 4439-4452. Doi: https://doi.org/10.3233/JIFS-201277.
- Nordander, C., Ohlsson, K., Balogh, I., Hansson, G-A ̊, Axmon, A., Persson, R. ve Skerfving, S. (2008). Gender differences in workers with identical repetitive industrial tasks: exposure and musculoskeletal disorders. Int Arch Occup Environ Health 81:939–94. Doi: https://doi.org/10.1007/s00420-007-0286-9.
- Opricovic, S. (2011). Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38(10), 12983-12990. Doi: https://doi.org/10.1016/j.eswa.2011.04.097
Otto, A. ve Scholl, A. (2013). Reducing ergonomic risks by job rotation scheduling. OR spectrum, 35, 711-733. Doi: https://doi.org/10.1007/s00291-012-0291-6.
- Özcan, S. G. , Yıldızbası, A. ve Eraslan, E. (2019). İnşaat Firmalarının İSG Bağlamında Bulanık Grup Karar Verme Yaklaşımı ile Değerlendirilmesi. Endüstri Mühendisliği, 30(3), 204-219. Erişim adresi: https://dergipark.org.tr/tr/pub/endustrimuhendisligi/issue/50398/606553
- Paliga, M. (2022). Human–cobot interaction fluency and cobot operators’ job performance. The mediating role of work engagement: A survey. Robotics and Autonomous Systems, 155, 104191. Doi: https://doi.org/10.1016/j.robot.2022.104191.
- Pant, M. ve Kumar, S. (2022). Particle swarm optimization and intuitionistic fuzzy set-based novel method for fuzzy time series forecasting. Granular Computing, 7(2), 285-303. Doi: https://doi.org/10.1007/s41066-021-00265-3.
- Papetti, A., Ciccarelli, M., Scoccia, C. ve Germani, M. (2021). A multi-criteria method to design the collaboration between humans and robots. Procedia CIRP, 104, 939-944. Doi: https://doi.org/10.1016/j.procir.2021.11.158
- Parameshwaran, R., Kumar, S. P. ve Saravanakumar, K. (2015). An integrated fuzzy MCDM based approach for robot selection considering objective and subjective criteria. Applied Soft Computing, 26, 31-41. Doi: https://doi.org/10.1016/j.asoc.2014.09.025.
- Park, K. C. ve Shin, D. H. (2017). Security assessment framework for IoT service, Telecommunication Systems, 64(1), 193-209. Doi: https://doi.org/10.1007/s11235-016-0168-0 .
- Peng, X. ve Yang, Y. (2015). Some results for Pythagorean fuzzy sets. International Journal of Intelligent Systems, 30(11), 1133-1160. Doi: 10.1002/int.21738.
- Peng, X. ve Yuan, H. (2016). Fundamental properties of Pythagorean fuzzy aggregation operators. Fundamenta Informaticae, 147(4), 415-446. Doi: https://doi.org/10.1002/int.21790 .
- Perçin, S. (2023). Identifying barriers to big data analytics adoption in circular agri-food supply chains: a case study in Turkey. Environmental Science and Pollution Research, 1-17. Doi: https://doi.org/10.1007/s11356-023-26091-5
- Putz-Anderson, V., Bernard, B. P., Burt, S. E., Cole, L. L., Fairfield-Estill, C., Fine, L. J., Grant, K.A., Gjessing, C., Jenkins, L., Hurrell Jr., J.J., Nelson, N., Pfirman, D., Roberts, R., Stetson, D., Haring-Sweeney, M. ve Tanaka, S. (1997). Musculoskeletal disorders and workplace factors. National Institute for Occupational Safety and Health (NIOSH), 104, 97-141. Erişim adresi: https://www.cdc.gov/niosh/docs/97-141/pdfs/97-141.pdf?id=10.26616/ NIOSHPUB97141.
- Rezagholi, M. ve Bantekas, A. (2015). Making economic social decisions for improving occupational health a predictive cost-benefit analysis. Occupational Medicine & Health Affairs. 3(06), 1000225, Doi: https://doi.org/10.4172/2329-6879.1000225.
- Savaş, E. (2016). On Generalized Double Statistical Convergence of Order α in Intuitionistic Fuzzy Normed Spaces. Mathematical and Computational Applications, 21(3), 36. Doi: https://doi.org/10.3390/mca21030036.
- Schou, C., Andersen, R.S., Chrysostomou, D., Bøgh, S. Ve Madsen, O. (2018). Skill-based instruction of collaborative robots in industrial settings, Robot. Comput. Integr. Manuf. 53 72–80, Doi: https://doi.org/10.1016/j.rcim.2018.03.008
- Scimmi, L. S., Melchiorre, M., Troise, M., Mauro, S. ve Pastorelli, S. (2021). A practical and effective layout for a safe human-robot collaborative assembly task. Applied Sciences, 11(4), 1763. Doi: https://doi.org/10.3390/app11041763 .
- Sharaf, I. M. ve Khalil, E. A. H. A. (2021). A spherical fuzzy TODIM approach for green occupational health and safety equipment supplier selection. International Journal of Management Science and Engineering Management, 16(1), 1-13. Doi: https://doi.org/10.1080/17509653.2020.1788467.
- Sriviboon, Y., & Jiamsanguanwong, A. Usability Evaluation and User Acceptance of Cobot: Case Study of Universal Robots CB Series. The International Conference on Industrial Engineering and Operations Management. Istanbul, Türkiye. Doi: https://doi.org/10.1145/3419249.3420161.
- Sumrit, D. (2020). Supplier selection for vendor-managed inventory in healthcare using fuzzy multi-criteria decision-making approach. Decision Science Letters, 9, 233–256. Doi: https://doi.org/10.5267/j.dsl.2019.10.002.
- Sun, C. C. (2010). A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert systems with applications, 37(12), 7745-7754. Doi: https://doi.org/10.1016/j.eswa.2010.04.066 .
- Veza, I., Mladineo, M., Kutlesa, M., Gjeldum, N., Bilic, B., Crnjac Zizic, M., Alinovic, A. ve Basic, A. (2022). Selection of the Cobot Workstation for the Learning Factory by using the Multi-Criteria Analysis. 12th Conference on Learning Factories, CLF2022, Singapur. Doi: https://doi.org/10.2139/ssrn.4072387
- Virgillito, M. E. (2017). Rise of the robots: Technology and the threat of a jobless future, Labor History, 58(2), 240-242.
- Vitolo, F., Rega, A., Di Marino, C., Pasquariello, A., Zanella, A. ve Patalano, S. (2022). Mobile Robots and Cobots Integration: A Preliminary Design of a Mechatronic Interface by Using MBSE Approach. Applied Sciences, 12(1), 419. Doi: https://doi.org/10.3390/app12010419.
- Vysocky, A. ve Novak, P. (2016). Human-robot collaboration in industry. MM Science Journal, 9(2), 903-906. Doi: https://doi.org/10.17973/MMSJ.2016_06_201611
- Yener, Y. ve Can, G. F. (2021). A FMEA based novel intuitionistic fuzzy approach proposal: Intuitionistic fuzzy advance MCDM and mathematical modeling integration. Expert Systems with Applications, 183, 115413. Doi: https://doi.org/10.1016/j.eswa.2021.115413.
- Yılmaz, B. ve Dağdeviren, M. (2010) Comparative analysis of PROMETHEE and fuzzy PROMETHEE methods in equipment selection problem. Journal of the Faculty of Engineering and Architecture of Gazi University, 25(4). Erişim adresi: https://dergipark.org.tr/tr/pub/gazimmfd/issue/6686/88606.
- Yılmaz, B. ve Dağdeviren, M. (2011). A combined approach for equipment selection: F-PROMETHEE method and zero–one goal programming. Expert Systems with Applications, 38(9), 11641-11650. Doi: https://doi.org/10.1016/j.eswa.2011.03.043.
- Yılmaz Kaya, B. (2022). Human factors engineerıng on the edge of Industry 4.0: Analysis for IoT-Aided technologies. Endüstri Mühendisliği, 33(1), 1-21. Doi: https://doi.org/10.46465/endustrimuhendisligi.1025701.
- Yılmaz Kaya, B. (2022). Contemplation and analysis of pandemic impacts on accommodation industry and a system reformulation proposal with Kano model: Turkey case. Current Issues in Tourism, 25(8), 1226-1241. Doi: https://doi.org/10.1080/13683500.2021.2007860
- Yılmaz Kaya, B. (2022). Minimizing OHS Risks with Spherical Fuzzy Sets as a Verdict to Inventory Management: A Case Regarding Energy Companies. Discrete Dynamics in Nature and Society, 9511339. Doi: https://doi.org/10.1155/2022/9511339.
- Yılmaz Kaya, B. ve Dağdeviren, M. (2016). Selecting occupational safety equipment by MCDM approach considering universal design principles. Human Factors and Ergonomics in Manufacturing & Service Industries, 26(2), 224-242. Doi: https://doi.org/10.1002/hfm.20625
- Yılmaz Kaya, B. ve Dağdeviren, M. (2017) A fuzzy marketing strategy benchmarking analysis in service sector. The 5th International Fuzzy Systems Symposium, TOBB-ETU, Ankara, Türkiye.
- Yılmaz Kaya, B. ve Dağdeviren, M. (2019). A guiding analysis to accomplish the challenges for implementation of Industry 4.0. 10th International Symposium on Intelligent Manufacturing and Service Systems, 738-746, Sakarya, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2018). A human centered multi-criteria decision making approach proposition for priorization of ergonomic factors in terms of working productivity. The 12th International Conference on New Challenges in Industrial Engineering and Operations Management, Ankara, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2021). A Multi-criteria Approach to Usability Research for Digital Platforms in Fuzzy Environment. INFUS 2021 Conference, August 24-26, 2021. 417-425, İstanbul, Türkiye.
- Yılmaz Kaya, B., Adem, A. ve Dağdeviren, M. (2022). Dijital ergonomi, akıllı fabrikalar ve işbirlikçi robot uygulamaları. 28. Ulusal Ergonomi Kongresi, 14-16 Ekim, Eskişehir, Türkiye.
- Yücesan, M. ve Gül, M. (2020). Hospital service quality evaluation: An integrated model based on Pythagorean fuzzy AHP and fuzzy TOPSIS. Soft Computing, 24(5), 3237-3255. Doi: https://doi.org/10.1007/s00500-019-04084-2.
- Zacharaki, A., Kostavelis, I., Gasteratos, A. ve Dokas, I. (2020). Safety bounds in human robot interaction: A survey. Safety science, 127, 104667. Doi: https://doi.org/10.1016/j.ssci.2020.104667.
- Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353. Doi: https://doi.org/10.1016/S0019-9958(65)90241-X.
- Zhang, Z. (2016). Some hesitant multiplicative aggregation operators and their application in group decision making with hesitant multiplicative preference relations. International Journal of Fuzzy Systems, 18(2), 177-197. Doi: https://doi.org/10.1007/s40815-016-0158-0.