{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T20:14:45Z","timestamp":1791922485265,"version":"4.3.4"},"reference-count":42,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u201cDun\u0103rea de Jos\u201d University of Galati"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper deals with a \u201cdigital twin\u201d (DT) approach for processing, reprocessing, and scrapping (P\/R\/S) technology running on a modular production system (MPS) assisted by a mobile cyber\u2013physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC. In addition to the connection via Profibus of the four PLCs, related to the WSs, to the main PLC, there are also the connections of other devices to the local networks, LAN Profinet and LAN Ethernet. There are the connections to the Internet, Cloud and Virtual Private Network (VPN) via WAN Ethernet by open platform communication unified architecture (OPC-UA). The overall system follows a DT approach that enables task planning through augmented reality (AR) and uses virtual reality (VR) for visualization through Synchronized Hybrid Petri Net (SHPN) simulation. Timed Petri Nets (TPNs) are used to control the processes within the MPS\u2019s workstations. Continuous Petri Nets (CPNs) handle the movement of the MCPRS. Task planning in AR enables users to interact with the system in real time using AR technology to visualize and plan tasks. SHPN in VR is a combination of TPNs and CPNs used in the virtual representation of the system to synchronize tasks between the MPS and MCPRS. The workpiece (WP) visits stations successively as it is moved along the line for processing. If the processed WP does not pass the quality test, it is taken from the last WS and is transported, by MCPRS, to the first WS where it will be considered for reprocessing or scrapping.<\/jats:p>","DOI":"10.3390\/s25020591","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T12:32:52Z","timestamp":1737376372000},"page":"591","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Cloud\/VPN-Based Remote Control of a Modular Production System Assisted by a Mobile Cyber\u2013Physical Robotic System\u2014Digital Twin Approach"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3007-3601","authenticated-orcid":false,"given":"Georgian","family":"Simion","sequence":"first","affiliation":[{"name":"Department of Automation, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"},{"name":"Doctoral School of Fundamental Sciences and Engineering, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1225-2243","authenticated-orcid":false,"given":"Adrian","family":"Filipescu","sequence":"additional","affiliation":[{"name":"Department of Automation, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"},{"name":"Doctoral School of Fundamental Sciences and Engineering, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Ionescu","sequence":"additional","affiliation":[{"name":"Department of Automation, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"},{"name":"Doctoral School of Fundamental Sciences and Engineering, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adriana","family":"Filipescu","sequence":"additional","affiliation":[{"name":"Department of Automation, \u201cDunarea de Jos\u201d University of Galati, 800008 Galati, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23020","DOI":"10.3390\/s150923020","article-title":"Optimization and Control of Cyber-Physical Vehicle Systems","volume":"15","author":"Bradley","year":"2015","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Minc\u0103, E., Filipescu, A., Cernega, D., \u0218olea, R., Filipescu, A., Ionescu, D., and Simion, G. (2022). Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor\u2014Challenges towards Industry 5.0. Sensors, 22.","DOI":"10.3390\/s22218153"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Simion, G., Filipescu, A., Ionescu, D., \u0218olea, R., Cernega, D., Minc\u0103, E., and Filipescu, A. (2022). Mobile Visual Servoing Based Control of a Complex Autonomous System Assisting a Manufacturing Technology on a Mechatronics Line. Inventions, 7.","DOI":"10.3390\/inventions7030047"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Segovia, M., and Garcia-Alfaro, J. (2022). Design, Modeling and Implementation of Digital Twins. Sensors, 22.","DOI":"10.3390\/s22145396"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Moiceanu, G., and Paraschiv, G. (2022). Digital Twin and Smart Manufacturing in Industries: A Bibliometric Analysis with a Focus on Industry 4.0. Sensors, 22.","DOI":"10.3390\/s22041388"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Carlos-Mancilla, M.A., Luque-Vega, L.F., Guerrero-Osuna, H.A., Ornelas-Vargas, G., Aguilar-Molina, Y., and Gonz\u00e1lez-Jim\u00e9nez, L.E. (2021). Educational Mechatronics and Internet of Things: A Case Study on Dynamic Systems Using MEIoT Weather Station. Sensors, 21.","DOI":"10.3390\/s21010181"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Berriche, A., Mhenni, F., Mlika, A., and Choley, J.-Y. (2020). Towards Model Synchronization for Consistency Management of Mechatronic Systems. Appl. Sci., 10.","DOI":"10.3390\/app10103577"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Filipescu, A., Eugenia, M., Cernega, D., Solea, R., Filipescu, A., Simion, G., and Ionescu, D. (2023, January 11\u201313). Digital Twin Based a Processing Technology Assisted by a MCPRS, Ready for Industry 5.0, 97\u20143022023. Proceedings of the 27th International Conference on System Theory, Control and Computing, ICSTCC, Timisoara, Romania.","DOI":"10.1109\/ICSTCC59206.2023.10308478"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Filipescu, A., Minc\u0103, E., Filipescu, A., and Coand\u0103, H.-G. (2020). Manufacturing Technology on a Mechatronics Line Assisted by Autonomous Robotic Systems, Robotic Manipulators and Visual Servoing Systems. Actuators, 9.","DOI":"10.3390\/act9040127"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Filipescu, A., Minca, E., and Filipescu, A. (2019, January 18\u201320). Mechatronics Manufacturing Line with Integrated Autonomous Robots and Visual Servoing Systems. Proceedings of the 9th IEEE International Conference on Cybernetics and Intelligent Systems, and Robotics, Automation and Mechatronics (CIS-RAM 2019), Bangkok, Thailand.","DOI":"10.1109\/CIS-RAM47153.2019.9095848"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Martinez, E.M., Ponce, P., Macias, I., and Molina, A. (2021). Automation Pyramid as Constructor for a Complete Digital Twin, Case Study: A Didactic Manufacturing System. Sensors, 21.","DOI":"10.3390\/s21144656"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bamunuarachchi, D., Georgakopoulos, D., Banerjee, A., and Jayaraman, P.P. (2021). Digital Twins Supporting Efficient Digital Industrial Transformation. Sensors, 21.","DOI":"10.3390\/s21206829"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Vach\u00e1lek, J., \u0160i\u0161mi\u0161ov\u00e1, D., Va\u0161ek, P., Fi\u0165ka, I., Slov\u00e1k, J., and \u0160imovec, M. (2021). Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line\u2019s Digital Twin by Using Color Sensor. Sensors, 21.","DOI":"10.3390\/s21051842"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gallala, A., Kumar, A.A., Hichri, B., and Plapper, P. (2022). Digital Twin for Human\u2013Robot Interactions by Means of Industry 4.0 Enabling Technologies. Sensors, 22.","DOI":"10.3390\/s22134950"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"St\u0105czek, P., Pizo\u0144, J., Danilczuk, W., and Gola, A. (2021). A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR\u2019s) Operating Environment\u2014A Case Study. Sensors, 21.","DOI":"10.3390\/s21237830"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Abdul Hadi, M., Kraus, D., Kajmakovic, A., Suschnigg, J., Guiza, O., Gashi, M., Sopidis, G., Vukovic, M., Milenkovic, K., and Haslgruebler, M. (2022). Towards Flexible and Cognitive Production\u2014Addressing the Production Challenges. Appl. Sci., 12.","DOI":"10.3390\/app12178696"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Angelopoulos, J., and Mourtzis, D. (2022). An Intelligent Product Service System for Adaptive Maintenance of Engineered-to-Order Manufacturing Equipment Assisted by Augmented Reality. Appl. Sci., 12.","DOI":"10.3390\/app12115349"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Barczak, A., Dembi\u0144ska, I., and Marzantowicz, \u0141. (2019). Analysis of the Risk Impact of Implementing Digital Innovations for Logistics Management. Processes, 7.","DOI":"10.3390\/pr7110815"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Fan, Y., Lv, X., Lin, J., Ma, J., Zhang, G., and Zhang, L. (2019). Autonomous Operation Method of Multi-DOF Robotic Arm Based on Binocular Vision. Appl. Sci., 9.","DOI":"10.3390\/app9245294"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ravankar, A., Ravankar, A.A., Kobayashi, Y., Hoshino, Y., and Peng, C.-C. (2018). Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges. Sensors, 18.","DOI":"10.3390\/s18093170"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Corke, P.I., Spindler, F., and Chaumette, F. (2009, January 11). Combining Cartesian and polar coordinates in IBVS. Proceedings of the 2009 IEEE\/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, USA.","DOI":"10.1109\/IROS.2009.5354569"},{"key":"ref_22","unstructured":"Copot, C. (2012). Control Techniques for Visual Servoing Systems. [Ph.D. Thesis, Technical University of Iasi]."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Petrea, G., Filipescu, A., Solea, R., and Filipescu, A. (2018, January 10\u201312). Visual Servoing Systems Based Control of Complex Autonomous Systems Serving a P\/RML. Proceedings of the 22nd IEEE, International Conference on System Theory, Control and Computing (ICSTCC), Sinaia, Romania.","DOI":"10.1109\/ICSTCC.2018.8540749"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Song, R., Li, F., Fu, T., and Zhao, J. (2020). A Robotic Automatic Assembly System Based on Vision. Appl. Sci., 10.","DOI":"10.3390\/app10031157"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lan, C.-W., and Chang, C.-Y. (2020). Development of a Low Cost and Path-free Autonomous Patrol System Based on Stereo Vision System and Checking Flags. Appl. Sci., 10.","DOI":"10.3390\/app10030974"},{"key":"ref_26","unstructured":"Deng, L., Wilson, W., and Janabi-Sharifi, F. (2003, January 27\u201331). Dynamic performance of the position-based visual servoing method in the Cartesian and image spaces. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, USA."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1177\/027836490302210011","article-title":"Performance tests for visual servo control systems, with application to partitioned approaches to visual servo control","volume":"22","author":"Gans","year":"2003","journal-title":"Int. J. Robot. Res."},{"key":"ref_28","unstructured":"(2024, October 11). Node-RED Web-Based Flow Editor for Remote Control, Node-RED 4.0 Released\u2014News\u2014Node-RED Forum (nodered.org). Available online: https:\/\/discourse.nodered.org\/t\/node-red-4-0-released\/88815."},{"key":"ref_29","unstructured":"(2024, October 11). Sirphyco Simulateur de R\u00e9seaux de Petri, Sirphyco-Simulateur-de-Reseaux-de-Petri. Available online: https:\/\/www.toucharger.com."},{"key":"ref_30","unstructured":"(2024, October 11). MathWorks. Available online: https:\/\/www.mathworks.com."},{"key":"ref_31","unstructured":"(2024, October 11). Totally Integrated Automation Portal, TIA Portal V17. Available online: https:\/\/www.siemens.com\/tia-portal."},{"key":"ref_32","unstructured":"(2024, October 11). OpenCV. Available online: https:\/\/opencv.org."},{"key":"ref_33","unstructured":"(2024, October 11). Microsoft Visual Studio. Available online: https:\/\/www.visualstudio.com\/vs\/cplusplus."},{"key":"ref_34","unstructured":"(2024, October 11). SCADA System SIMATIC, WinCC SIMATIC WinCC V7\/V8\u2014Siemens Xcelerator Global. Available online: https:\/\/xcelerator.siemens.com\/global\/en\/all-offerings\/products\/s\/simatic-wincc-v7-v8.html."},{"key":"ref_35","unstructured":"(2024, October 11). VNC (Virtual Network Computing), RealVNC\u00ae Remote Access Software for Desktop and Mobile|RealVNC. Available online: https:\/\/www.realvnc.com."},{"key":"ref_36","unstructured":"(2024, October 11). Advanced Robotics Interface for Applications (ARIA). Available online: https:\/\/web.archive.org\/web\/20180205212122\/http:\/\/robots.mobilerobots.com\/wiki\/Aria."},{"key":"ref_37","unstructured":"(2024, October 11). MobileSim, Simulator for Mobile Robots. Available online: http:\/\/robots.mobilerobots.com\/MobileSim."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"102412","DOI":"10.1016\/j.rcim.2022.102412","article-title":"Dynamic job shop scheduling based on deep reinforcement learning for multi-agent manufacturing systems","volume":"78","author":"Zhang","year":"2022","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Tang, D., Zhu, H., Zhou, S., and Zhao, Z. (2022). An Efficient IIoT Gateway for Cloud\u2013Edge Collaboration in Cloud Manufacturing. Machines, 10.","DOI":"10.3390\/machines10100850"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"102357","DOI":"10.1016\/j.rcim.2022.102357","article-title":"Probing an intelligent predictive maintenance approach with deep learning and augmented reality for machine tools in IoT-enabled manufacturing","volume":"77","author":"Liu","year":"2022","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Li, Q., Yang, Y., and Jiang, P. (2023). Remote Monitoring and Maintenance for Equipment and Production Lines on Industrial Internet: A Literature Review. Machines, 11.","DOI":"10.3390\/machines11010012"},{"key":"ref_42","first-page":"37","article-title":"An Industry 4.0 Platform for Equipment Monitoring and Maintaining in Carbon Anode Production","volume":"55","author":"Li","year":"2022","journal-title":"IFAC-Pap. 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