Content Analysis of Articles on Cyber-Physical Manufacturing Systems Published in SCI and SCI Expanded Indexed Journals Between 2015-2021

Yıl 2022, 30. Yıl Özel Sayısı, 205 - 230, 28.07.2022

Bedrettin Türker Palamutçuoğlu , Mustafa Gerşil

https://doi.org/10.18026/cbayarsos.1101334

Öz

Under the conditions of global competition, businesses must have competitive advantages in order to survive. For this, businesses need to keep their production processes under control, automate them, and make human-machine interaction safe and efficient. It has become almost inevitable for businesses today to reduce production errors, reduce maintenance-repair costs, eliminate unnecessary activities and apply the lean production approach. Technological innovations such as additive manufacturing, the internet of things, cloud computing, augmented reality, and artificial intelligence in recent years has led to the emergence of cyber-physical systems. In this paper, a literature summary of the articles on SCI-expanded and SCI on cyber-physical production systems between 2015 to 2021 years is presented in order to guide the scientists and technical personnel of the enterprises who want to work on these systems that will be the basis of the future production systems. It was seen that there were more conceptual studies at the beginning, but a rapid increase in applied studies. In addition, important studies that address the difficulties faced by businesses in the digital transformation process and draw attention to cyber security are also striking.

Anahtar Kelimeler

Machine-Human Interaction

2015-2021 yılları arasında SCI ve SCI Expanded endeksli dergilerde yayınlanan Siber-Fiziksel Üretim Sistemleri Konulu Makalelerin İçerik Analizi

Öz

Küresel rekabet koşulları altında işletmelerin varlıklarını sürdürebilmeleri için rekabetçi üstünlüklere sahip olması gerekmektedir. Bunun için işletmelerin üretim süreçlerini kontrol altında tutmaları, otomatikleştirmeleri, insan-makine etkileşimi emniyetli ve verimli hale getirmeleri gerekmektedir. Üretim hatalarını azaltmak, bakım-onarım maliyetlerini azaltmak, gereksiz faaliyetleri ortadan kaldırıp yalın üretim anlayışını uygulamak günümüzde işletmeler için neredeyse kaçınılmaz hale gelmiştir. Son yıllarda yaşanan eklemeli imalat, nesnelerin interneti, bulut bilişim, artırılmış gerçeklik, yapay zekâ gibi teknolojik yenilikler siber-fiziksel sistemlerin ortaya çıkmaya başlamasına neden olmuştur. Bu makalede geleceğin üretim sistemlerinin temelinde yer alacak bu sistemler hakkında çalışmak isteyen bilim insanlarına ve işletmelerin teknik personellerine yol göstermek ve bir çıkış noktası oluşturmak amacıyla 2015 ve 2021 yılları arasında SCI-expanded ve SCI endeksli dergilerde siber-fiziksel üretim sistemleri konulu makalelerin literatür özeti sunulmuştur. Başlangıçta kavramsal çalışmaların daha fazla olduğu ama uygulamalı çalışmalarında hızlı bir artış gösterdiği görülmüştür. Ayrıca dijital dönüşüm sürecinde işletmelerin karşılaştıkları zorlukları ele alan, siber güvenliğe dikkat çeken önemli çalışmalar da göze çarpmaktadır.

Anahtar Kelimeler

Siber-fiziksel üretim sitemi, Siber-fiziksel imalat sistemi, Dijital İkiz, Makine-İnsan Etkileşimi

Kaynakça

• Ait-Alla, A., Kreutz,, M., Rippel,, D., Lütjen, M., & Freitag, M. (2021). Simulated-based methodology for the interface configuration of cyber-physical production systems, International Journal of Production Research, 59 (17), 5388-5403. Doi: 10.1080/00207543.2020.1778209.
• Alam, K. M., & El Saddik, A. 2017. “C2PS: A digital twin architecture reference model for the cloud-based cyber-physical systems”. IEEE Access, 5, 2050–2062. doi: 10.1109/ACCESS.2017.2657006.
• Andronie, M., Lazaroiu, G., Iatagan, M., Hurloiu, I., & Dijmarescu, I. (2021b). Sustainable Cyber-Physical Production Systems in Big Data-Driven Smart Urban Economy: A Systematic Literature Review. Sustainability, 13(2). Doi: 10.3390/su13020751.
• Andronie, M., Lazaroiu, G., Iatagan, M., Uta, C ., Stefanescu, R., & Cocosatu, M. (2021c). Artificial Intelligence-Based Decision-Making Algorithms, Internet of Things Sensing Networks, and Deep Learning-Assisted Smart Process Management in Cyber-Physical Production Systems. Electronics, 10(20). Doi: 10.3390/electronics10202497.
• Andronie, M., Lazaroiu, G., Ştefanescu, R., Uta, C., & Dijmarescu, I. (2021). Sustainable, Smart, and Sensing Technologies for Cyber-Physical Manufacturing Systems: A Systematic Literature Review. Sustainability, 13 (10). Doi: 10.3390/su13105495
• Ansari, F., Glawar, R., & Nemeth, T. (2919). PriMa: a prescriptive maintenance model for cyber-physical production systems, International Journal of Computer Integrated Manufacturing, 32 (4-5), 482-503. Doi: 10.1080/0951192X.2019.1571236
• Baena, F., Guarin, A., Mora, J., Sauza J., & Retat, S. (2017). Learning factory: The path to industry 4.0. 7th Conference on Learning Factories, CLF - Procedia Manufacturing, 9, 73–80.
• Bampoula, X., Siaterlis, G., Nikolakis, N. ve Alexopoulos, K. (2021). A Deep Learning Model for Predictive Maintenance in Cyber-Physical Production Systems Using LSTM Autoencoders. Sensors, 21(3). Doi: 10.3390/s21030972.
• Bayhan, H., Meißner, M., Kaiser, P., Meyer, M., & ten Hompel, M. (2020). Presentation of a novel real-time production supply concept with cyber-physical systems and efficiency validation by process status indicators. International Journal of Advanced Manufacturing Technology, 108(1-2), 527-537. Doi: 10.1007/s00170-020-05373-z.
• Beregi, R., Pedone, G., & Mezgár, I. (2019). A novel fluid architecture for cyber-physical production systems. International Journal of Computer Integrated Manufacturing, 32:4-5, 340-351, DOI: 10.1080/0951192X.2019.1571239
• Beregi, R., Pedone, G., Háy, B., & Váncza, J. (2021). Manufacturing Execution System Integration through the Standardization of a Common Service Model for Cyber-Physical Production Systems. Applied Sciences. 11 (16). Doi: 10.3390/app11167581.
• Beregi, R., Pedone, G., & Preuveneers, D. (2021). Towards trustworthy Cyber-physical Production Systems: A dynamic agent accountability approach. Journal Of Ambıent Intelligence And Smart Environments, 13 (2), 157-180. Doi: 10.3233/AIS-210593.
• Bin Islam, S.O., Lughmani, W.A., Qureshi, W.S., Khalid, A., Mariscal, M.A., & Garcia-Herrero, S. (2019). Exploiting visual cues for safe and flexible cyber-physical production systems. Advances in Mechanical Engineering, 11 (12), 1-13. Doi: 10.1177/1687814019897228.
• Brandman, J., Sturm, L., White, J., & Williams, C. (2020). A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems. Journal of Manufacturing Systems, 56, 202-212. Doi: 10.1016/j.jmsy.2020.05.014
• Broy, M., Cengarle, M. V., & Geisberger, E. (2012). Cyber-Physical Systems: Imminent Challenges. In Monterey workshop 2012: Large-Scale Complex IT Systems. Development, Operation and Management (pp. 1-28). March 2018, Springer, Berlin, Heidelberg.
• Cardin, O. (2019). Classification of cyber-physical production systems applications: Proposition of an analysis framework. Computers in Industry, 104, 11-21. Doi: 10.1016/j.compind.2018.10.002.
• Chen, X.W., Jiang, G.Z., Xiao, Y.M., Li, G.F., & Xiang, F. (2021). A Hyper Heuristic Algorithm Based Genetic Programming for Steel Production Scheduling of Cyber-Physical System-ORIENTED. Mathematics, 9(18). Doi: 10.3390/math9182256.
• Chhetri, S.R., & Al Faruque, M.A. (2018). Side Channels of Cyber–Physical Systems: Case Study in Additive Manufacturing. IEEE Design&Test, 34 (4), 18-25. Doi: 10.1109/MDAT.2017.2682225.
• Chuang, W., Guanghui, Z., & Junsheng, W. (2021). Smart cyber-physical production system enabled workpiece production in digital twin job shop. Advances in Mechanical Engineering, 13 (9), 1-15. Doi:10.1177/16878140211040888.
• Dhiman, H., & Röcker, C. (2021). Middleware for providing activity-driven assistance in cyber-physical production systems. Journal of Computational Design and Engineering, 8 (1), 428–451. Doi: 10.1093/jcde/qwaa088.
• Elhabashy, A.E., Wells, L.J., Camelio, J.A., & Woodall, W.H. (2019). A cyber-physical attack taxonomy for production systems: a quality control perspective. Journal of Intelligent Manufacturing, 30 (6), 2489-2504. Doi: 10.1007/s10845-018-1408-9.
• Farooq, B., Bao, J., & Ma, Q. (2020). Flow-Shop Predictive Modeling for Multi-Automated Guided Vehicles Scheduling in Smart Spinning Cyber-Physical Production Systems. Electronics, 9(5). Doi: 10.3390/electronics9050799.
• Fischbach, A., Strohschein, J., Bunte, A., Stork, J., Faeskorn-Woyke, H., Moriz, N., & Bartz-Beielstein, T. (2020). CAAI—a cognitive architecture to introduce artificial intelligence in cyber-physical production systems. The International Journal of Advanced Manufacturing Technology, 111 (1-2), 609-626. Doi: 10.1007/s00170-020-06094-z.
• García, C.A., Castellanos, E.X., & García, M.V. (2018). UML-Based Cyber-Physical Production Systems on Low-Cost Devices under IEC-61499. Machines. 6 (2). Doi: 10.3390/machines6020022.
• García, M.V., Irisarri, E., Pérez, F., Estévez, E., & Marcos, M. (2018). Automation Architecture based on Cyber Physical Systems for Flexible Manufacturing within Oil&Gas Industry. Revista Iberoamericana de Automática e Informática industrial, 15 (2), 156-166. Doi: 10.4995/riai.2017.8823.
• Grochowski, M., Simon, H., Bohlender, D., Kowalewski, S., Löcklin, A., Müller, T., Jazdi, N., Zeller, A., & Weyrich, M. (2020). Formal methods for reconfigurable cyber-physical systems in production. at - Automatisierungstechnik, 68 (1), 3-14. Doi: 10.1515/auto-2019-0115.
• Gupta, N., Tiwari, A., Bukkapatnam, S.T.S., & Karri, R. (2020). Additive Manufacturing Cyber-Physical System: Supply Chain Cybersecurity and Risks. IEEE Access, 8, 47322-47333. Doi: 10.1109/ACCESS.2020.2978815.
• Harrison, R., Vera, D.A., & Ahmad, B. (2021). A Connective Framework to Support the Lifecycle of Cyber–Physical Production Systems. Proceedings of the IEEE, 109 (4), 568-581. Doi: 10.1109/JPROC.2020.3046525.
• Hastbacka, D., Halme, J., Barna, L., Hoikka, H., Pettinen, H., Larranaga, M., Bjorkbom, M., Mesia, H., Jaatinen, A., & Elo, M. (2022). Dynamic Edge and Cloud Service Integration for Industrial IoT and Production Monitoring Applications of Industrial Cyber-Physical Systems. IEEE Transactions on Industrial Informatics, 18(1), 498-508. Doi: 10.1109/TII.2021.3071509.
• Hozdić, E., Kozjek, D., & Butala, P. (2019). A Cyber-Physical Approach to the Management and Control of Manufacturing Systems. Strojniški vestnik - Journal of Mechanical Engineering, 66 (1), 61-70. Doi: 10.5545/sv-jme.2019.6156.
• Huang, J., Zhu, Y., Cheng, B., Lin, C., & Chen, J. (2016). A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems. Sensors, 16 (3). Doi: 10.3390/s16030382.
• Iber, M., Lechner, P., Jandl, C., Mader, M., & Reichmann, M. (2021). Auditory augmented process monitoring for cyber physical production systems. Personal and Ubiquitous Computing, 25 (4), 691-704. Doi: 10.1007/s00779-020-01394-3
• Jiang, Z., Jin, Y., Mingcheng, E., & Li, Q. (2018a). Distributed Dynamic Scheduling for Cyber-Physical Production Systems Based on a Multi-Agent System. IEEE Access, 6, 1855-1869. Doi: 10.1109/ACCESS.2017.2780321.
• Jiang, Z., Jin, Y., Mingcheng, E., & Li, Q. (2018b). Method of tasks and resources matching and analysis for cyberphysical production system. Advances in Mechanical Engineering, 10(5), 1-9. Doi: 10.1177/1687814018777828.
• Khalid, A., Khan, Z.H., Idrees, M., Kirisci, P., Ghrairi, Z., Thoben, K.D., & Pannek, J. (2021): Understanding vulnerabilities in cyber physical production systems, International Journal of Computer Integrated Manufacturing, DOI:10.1080/0951192X.2021.1992656.
• Kim, B.S., Nam, S., Jin, Y., & Seo, K.M. (2020). Simulation Framework for Cyber-Physical Production System: Applying Concept of LVC Interoperation. Complexity, 2020. Doi:10.1155/2020/4321873.
• Kondoh, S., Furukawa, Y., & Kishita, Y. (2021). A method for redesigning business workflow for cyberphysical production system. Journal of Advanced Mechanical Design, Systems, and Manufacturing, 15 (5). Doi: 10.1299/jamdsm.2021jamdsm0063.
• Lanza, G., Haefner, B., & Kraemer, A. (2015). Optimization of selective assembly and adaptive manufacturing by means of cyber-physical system based matching. CIRP Annals - Manufacturing Technology, 64 (1), 399-402. Doi: 10.1016/j.cirp.2015.04.123.
• Lee,, J.H., Noh, S.D., Kim, H.J., & Kang, Y.S. (2018). Implementation of Cyber-Physical Production Systems for Quality Prediction and Operation Control in Metal Casting. Sensors, 18(5). Doi: 10.3390/s18051428.
• Leiden, A., Herrmann, C., & Thiede, S. (2021). Cyber-physical production system approach for energy and resource ef fi cient planning and operation of plating process chains. Journal of Cleaner Production, 280(2). Doi: 10.1016/j.jclepro.2020.125160.
• Lhachemi, H., Malik, A., & Shorten, R. (2019). Augmented Reality, Cyber-Physical Systems, and Feedback Control for Additive Manufacturing: A Review. IEEE Access, 7, 50119-50135. Doi: 10.1109/ACCESS.2019.2907287.
• Macherki, D., Diallo, T.M.L., Choley, J.Y., Guizani, A., Barkallah, M., & Haddar, M. (2021). QHAR: Q-Holonic-Based ARchitecture for Self-Configuration of Cyber-Physical Production Systems. Applied Sciences-Basel, 11(19). Doi: 10.3390/app11199013.
• Mahmood, K., Karaulova, T., Otto, T., & Shevtshenko, E. (2019). Development of cyber-physical production systems based on modelling technologies. Proceedings of the Estonian Academy of Sciences, 68 (4), 348-355. Doi: 10.3176/proc.2019.4.02.
• Malik, A., Lhachemi, H., & Shorten, R. (2020). I-nteract: A Cyber-Physical System for Real-Time Interaction With Physical and Virtual Objects Using Mixed Reality Technologies for Additive Manufacturing. IEEE Access, 8, 98761-98774. Doi: 10.1109/ACCESS.2020.2997533.
• Martín-Gómez, A., Ávila-Gutiérrez, M. J., & Aguayo-González, F. (2021). Holonic Reengineering to Foster Sustainable Cyber-Physical Systems Design in Cognitive Manufacturing. Applied Sciences, 11 (7). Doi: 10.3390/app11072941.
• Mörth, O., Emmanouilidis, C., Hafner, N., & Schadler, M. (2020). Cyber-physical systems for performance monitoring in production intralogistics. Computers&Industrial Engineering, 142. Doi: 10.1016/j.cie.2020.106333.
• Neghina, M., Zamfirescu, C.B., & Pierce, K. (2020). Early‑stage analysis of cyber‑physical production systems through collaborative modelling. Software and Systems Modeling, 19 (3), 581-600. Doi: 10.1007/s10270-019-00753-w.
• Nikolakis, N., Senington, R., Sipsas, K., Syberfeldt, A., & Makris, S. (2019). On a containerized approach for the dynamic planning and control of a cyber - physical production system. Robotics and Computer-Integrated Manufacturing, 64. Doi: 10.1016/j.rcim.2019.101919.
• Nouiri, M., Trentesaux, D., & Bekrar, A. (2019). Towards Energy Efficient Scheduling of Manufacturing Systems through Collaboration between Cyber Physical Production and Energy Systems. Energies. 12 (23). Doi: 10.3390/en12234448.
• Pan, Y., White,, J., Schmidt,, D.C., Elhabashy, A., Sturm, L., Camelio, J., & Williams, C. (2017). Taxonomies for Reasoning About Cyber-physical Attacks in IoT-based Manufacturing Systems. International Journal Of Interactive Multimedia And Artificial Intelligence, 4 (3), 45-54. Doi: 10.9781/ijimai.2017.437.
• Park, K.T., Lee, J., Kim, H.J., & Noh, S. (2020). Digital twin-based cyber physical production system architectural framework for personalized production. International Journal of Advanced Manufacturing Technology, 106(5-6), 1787-1810. Doi: 10.1007/s00170-019-04653-7
• Pinzone, M., Albè, F., Orlandelli, D., Barletta, I., Berlin, C., Johansson, B., & Taisch, M. (2020). A framework for operative and social sustainability functionalities in Human-Centric Cyber-Physical Production Systems. Computers&Industrial Engineering, 139. Doi: 10.1016/j.cie.2018.03.028.
• Qian, J., Du, X., Chen, B., Qu, B., Zeng, K., & Liu, J. (2020). Cyber-Physical Integrated Intrusion Detection Scheme in SCADA System of Process Manufacturing Industry. IEEE Access, 8, 147471-147481. Doi: 10.1109/ACCESS.2020.3015900.
• Qin, J., Liu, Y., & Grosvenor, R. (2016). A categorical framework of manufacturing for industry 4.0 and beyond. Changeable, Agile, Reconfigurable & Virtual Production - Procedia CIRP, 52, 173–178.
• Ralph, B.J., Sorger, M., Hartl, K., Schwarz-Gsaxner, A., Messner, F., & Stockinger, M. (2022). Transformation of a rolling mill aggregate to a cyber physical production system: from sensor retrofitting to machine learning. Journal of Intelligent Manufacturing, 33(2), 493-518. Doi: 10.1007/s10845-021-01856-2.
• Ribeiro, L., & Bjorkman, M. (2018). Transitioning From Standard Automation Solutions to Cyber-Physical Production Systems: An Assessment of Critical Conceptual and Technical Challenges. IEEE Systems Journal, 12(4), 3816-3827. Doi: 10.1109/JSYST.2017.2771139.
• Romero-Silva, R., & Hernandez-Lopez, G. (2020). Shop-floor scheduling as a competitive advantage: A study on the relevance of cyber-physical systems in different manufacturing contexts. International Journal of Production Economics, 224. Doi: 10.1016/j.ijpe.2019.107555.
• Runji, J.M., & Lin, C.Y. (2020). Switchable Glass Enabled Contextualization for a Cyber-Physical Safe and Interactive Spatial Augmented Reality PCBA Manufacturing Inspection System. Sensors, 20(15). Doi: 10.3390/s20154286.
• Saez, M.A., Maturana, F.P., Barton, K., & Tilbury, D.M. (2020). Context-Sensitive Modeling and Analysis of Cyber-Physical Manufacturing Systems for Anomaly Detection and Diagnosis. IEEE Transactions on Automation Science and Engineering, 17(1), 29-40. Doi: 10.1109/TASE.2019.2918562.
• Salazar, L.A.C., Ryashentseva, D., Luder, A., & Vogel-Heuser, B. (2019). Cyber-physical production systems architecture based on multi-agent's design pattern-comparison of selected approaches mapping four agent patterns. International Journal of Advanced Manufacturing Technology, 105(9), 4005-4034. Doi: 10.1007/s00170-019-03800-4.
• Soylu, A. (2017). Endüstri 4.0 ve Girişimcilikte Yeni Yaklaşımlar. Pamukkale Üniversitesi Sosyal Bililmler Enstitüsü Dergisi, 32, s.43-57.
• Stern, H., & Becker, T. (2019). Concept and Evaluation of a Method for the Integration of Human Factors into Human-Oriented Work Design in Cyber-Physical Production Systems. Sustainability, 11(16). Doi: 10.3390/su11164508.
• Strohschein, J., Fischbach, A., Bunte, A., Faeskorn-Woyke, H., Moriz, N., &Bartz-Beielstein, T. (2021). Cognitive capabilities for the CAAI in cyber-physical production systems. International Journal Of Advanced Manufacturing Technology, 115, 11-12. Doi: 10.1007/s00170-021-07248-3
• Suvarna, M., Yap, K.S., Yang, W., Li, J., Ng, Y.T., & Wang, X. (2021). Cyber-Physical Systems for Data-Driven, Decentralized, and Secure Manufacturing-A Perspective. Engineering, 7 (9), 1212-1223. Doi:10.1016/j.eng.2021.04.021.
• Talkhestani, B.A., Jung, T., Lindeman, B., Sahlab, N., Jazdi, N., Schloegl, W., & Weyrich, M. (2019). An architecture of an Intelligent Digital Twin in a Cyber-Physical Production System. At-Automatisierungstechnik, 67 (9), 762-782. Doi: 10.1515/auto-2019-0039.
• Tan, Y., Yang, W., Yoshida, K., & Takakuwa, S. (2019). Application of IoT-Aided Simulation to Manufacturing Systems in Cyber-Physical System. Machines, 7 (1). Doi: 10.3390/machines7010002.
• Tao, F., Qi, QL., Wang, L.H., & Nee, A.Y.C. (2019). Digital Twins and Cyber-Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison. Engineering, 5(4), 653-661. Doi: 10.1016/j.eng.2019.01.014.
• TAYSAD. (2016). Tasarım Teknoloji Tedarik Dünyada İlk 10. Sayı 88 Mart - Nisan. http://www.taysadmag.com/uploads/tasarim-teknoloji-tedarik05072019091357.pdf (Erişim Tarihi: 01.10.2019).
• Thramboulidis, K., Vachtsevanou, D.C., & Kontou, I. (2019). CPuS-IoT: A cyber-physical microservice and IoT-based framework for manufacturing assembly systems. Annual Reviews in Control, 47, 237-248. Doi: 10.1016/j.arcontrol.2019.03.005.
• Tomiyama, T., & Moyen, F. (2018). Resilient architecture for cyber-physical production systems. CIRP Annals - Manufacturing Technology, 67 (1), 161-164. Doi: 10.1016/j.cirp.2018.04.021
• Traganos, K., Grefen, P., Vanderfeesten, I., Erasmus, J., Boultadakis, G., & Bouklis, P. (2021). The HORSE framework: A reference archtitecture for cyber-physical systems in hybrid smart manufacturing. Journal of Manufacturing Systems, 61, 461-494. Doi: 10.1016/j.jmsy.2021.09.003.
• Tran, N.H., Park, H.S., Nguyen, Q.V., & Hoang, T.D. (2019). Development of a Smart Cyber-Physical Manufacturing System in the Industry 4.0 Context. Applied Sciences, 9 (16). Doi: 10.3390/app9163325.
• Trappey, A.J.C., Trappey, C.V., Govindarajan, U.H., Sun, J.J., & Chuang, A.C. (2016). A Review of Technology Standards and Patent Portfolios for Enabling Cyber-Physical Systems in Advanced Manufacturing. IEEE Access, 4, 7356-7382. Doi: 10.1109/ACCESS.2016.2619360.
• TÜSİAD. (2016). Türkiye’nin Küresel Rekabetçiliği İçin Bir Gereklilik Olarak Sanayi 4.0 Gelişmekte Olan Ekonomi Perspektifi, Mart 2016, TÜSİADT/2016-03/576.
• Urbina, M., Atarloa, A., Lázaro, J., Bidarte, U., Villalta, I., & Rodriguez, M. (2017). Cyber-Physical Production System Gateway Based on a Programmable SoC Platform. IEEE Access, 5, 20408-20417. Doi: 10.1109/ACCESS.2017.2757048.
• Villalonga, A., Negri, E., Biscardo, G., Castano, F., Haber, R.E., Fumagalli, L., & Macchi, M. (2021). A decision-making framework for dynamic scheduling of cyber-physical production systems based on digital twins. Annual Reviews in Control, 51, 357-373. Doi: 10.1016/j.arcontrol.2021.04.008.
• Vogel-Heuser, B., Lee, J., & Leitão, P. (2015). Agents enabling cyber-physical production systems. at – Automatisierungstechnik. 63 (10), 777–789. Doi: 10.1515/auto-2014-1153.
• Vogel-Heuser, B., Trunzer, E., Hujo, D., & Sollfrank, M. (2021). (Re)deployment of Smart Algorithms in Cyber–Physical Production Systems Using DSL4hDNCS. Proceedings of the IEEE, 10 (4), 542-555. Doi: 10.1109/JPROC.2021.3050860.
• Wan, G., & Zeng, P. (2020).An Event-Based Programming Model with Geometric Spatial Semantics For Cyber-Physical Production Systems. Applied Sciences-Basel, 10(21). Doi: 10.3390/app10217651.
• Waschull, S., Bokhorst, J.A.C., Molleman, E., & Wortmann, J.C. (2020). Work design in future industrial production: Transforming towards cyberphysical systems. Computers&Industrial Engineering, 139. Doi: 10.1016/j.cie.2019.01.053.
• Wiemer, H., Dementyev, A., & Ihlenfeldt, S. (2021). Holistic Quality Assurance Approach for Machine Learning Applications in Cyber-Physical Production Systems. Applied Sciences, 11(29). Doi: 10.3390/app11209590.
• Wilhelm, J., Petzoldt, C., Beinke, T., & Freitag, M. (2021). Review of Digital Twin-based Interaction in Smart Manufacturing: Enabling Cyber-Physical Systems for Human-Machine Interaction, International Journal of Computer Integrated Manufacturing, 34(10), 1031-1048, Doi: 10.1080/0951192X.2021.1963482
• Yao, X., Zhou, J., Lin, Y., Li, Y., Yu, H., & Liu, Y. (2019). Smart manufacturing based on cyber-physical systems and beyond. Journal of Intelligent Manufacturing, 30 (8), 2805-2817. Doi: 10.1007/s10845-017-1384-5.
• Yin, D., Ming, X., & Zhang, X. (2020). Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context. Sensors, 20(18). Doi: 10.3390/s20185319.
• Yu, Z., Ouyang, J., Li, S., & Peng, X. (2017). Formal modeling and control of cyber-physical manufacturing systems. Advances in Mechanical Engineering, 9 (10), 1-12. Doi: 10.1177/1687814017725472.
• Yu, Z., Zhou, L., Ma, Z., & El-Meligy, M.A. (2017). Trustworthiness Modeling and Analysis of Cyber-physical Manufacturing Systems. IEEE Access, 5, 26076-26085. Doi: 10.1109/ACCESS.2017.2777438.
• Yükçü, S., & Aydın, Ö. (2020). Maliyet Düşürme Yöntemi Olarak Dijital İkiz. Muhasebe Bilim Dünyası Dergisi, 22(3),563-579.
• Zheng, M., & Ming, X. (2017). Construction of cyber-physical system–integrated smart manufacturing workshops: A case study in automobile industry. Advances in Mechanical Engineering, 9 (10), 1-17. Doi: 10.1177/1687814017733246.
• Zhou, J., Zhou, Y.H., Wang, B., & Zang, J.Y. (2019). Human-Cyber-Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing. Engineering, 5 (4), 624-636. Doi: 10.1016/j.eng.2019.07.015.
• Zhou, X., Xu, X., Liang, W., Zeng, Z., Shimizu, S., Yang, L.T., & Jin, Q. (2022). Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems. IEEE Transactions on Industrial Informatics, 18 (2), 1377-1386. Doi: 10.1109/TII.2021.3061419.