ANALYZING STRATEGIES OF THE PRODUCTION EFFICIENCY ENHANCEMENT BY MOBILE ROBOTS INTEGRATION
DOI:
https://doi.org/10.35546/kntu2078-4481.2023.4.9Keywords:
Mobile Robots, Automated Manufacturing, Automation, Industry 4.0, Efficiency Enhancement Strategies, Unmanned Aerial Vehicles (UAV).Abstract
The contemporary industry is undergoing active development due to the utilization of advanced technologies and innovative approaches. One of the key methods to enhance productivity and competitiveness of enterprises involves the integration of mobile robots into the manufacturing processes, aiming to reduce human involvement or even exclude it entirely. This approach constitutes a crucial element of the Industry 4.0 concept. The article seeks to synthesize modern approaches and strategies for automating industrial production to determine the role of mobile robots in enhancing the efficiency of these processes. To comprehend the tasks and challenges of contemporary automation, the research defines primary objectives, including an analysis of the current state and prospects of integrating mobile robots into the production process, an assessment of their effectiveness, and their significance for modern industry. Furthermore, the study identifies directions for further research and development in this field. The analysis of the current state of mobile robot integration into the production process, based on specific examples, reveals factors determining the success of this approach. Among these factors, noteworthy are the technical reliability of robots, their ability to adapt to diverse manufacturing conditions, and their interaction and collaboration with human personnel. The process of adapting and educating personnel to use new technologies is a pivotal stage in the implementation of mobile robots. Ethical and safety aspects also need consideration, as the interaction between robots and humans requires coordinated standards to prevent potential risks and misunderstandings. Conducted research underscores the relevance of utilizing mobile robots in contemporary manufacturing and outlines the tasks ahead of them. The primary emphasis is on improving the productivity and sustainability of production processes. In the context of Industry 4.0, mobile robots highlight the significance of research and integration of advanced technologies to achieve the necessary quality and efficiency in production.
References
Bai, C. et al. (2020) ‘Industry 4.0 technologies assessment: A sustainability perspective’, International Journal of Production Economics, 229, p. 107776. doi:10.1016/j.ijpe.2020.107776.
Park, H.-A. (2016) ‘Are we ready for the fourth industrial revolution?’, Yearbook of Medical Informatics, 25(01), pp. 1–3. doi:10.15265/iy-2016-052.
Mobile robots market size, share, industry report, Revenue Trends and Growth Drivers MarketsandMarkets. Available at: https://www.marketsandmarkets.com/Market-Reports/mobile-robots-market-43703276.html (Accessed: 17 October 2023).
Market Research Future, Mobile Robotics Market Size, trends and forecast- 2030, Mobile Robotics Market Size, Trends and Forecast- 2030. Available at: https://www.marketresearchfuture.com/reports/mobile-robotics-market-1946 (Accessed: 17 October 2023).
Vathos GmbH (2023). https://www.vathos-robotics.de/. Accessed 11 Oct 2023
Verosim Solutions (2023). https://www.verosim-solutions.com/. Accessed 11 Oct 2023
Müller, R., Hörauf, L., Vette-Steinkamp, M., Kanso, A., Koch, J.: The assist-by-X system: calibration and application of a modular production equipment for visual assistance. Proc. CIRP 86, 179–184 (2019). https://doi.org/10.1016/j.procir.2020.01.021
SQRP: Sensing Quality-aware robot programming system for … – arxiv.org. Available at: https://arxiv.org/pdf/2107.00127 (Accessed: 11 October 2023).
K. He, A. M. Wells, L. E. Kavraki, and M. Y. Vardi, “Efficient symbolic reactive synthesis for finite-horizon tasks,” in 2019 International Conference on Robotics and Automation (ICRA). IEEE, 2019, pp. 8993–8999.
Global Industrial Automation Market Report and forecast 2024–2032 (2023) Industrial Automation Market Analysis, Size, Share, Report 2024–2032. Available at: https://www.expertmarketresearch.com/reports/industrialautomation-market (Accessed: 06 October 2023).
Facts and Factors (2023) Industrial Robotics Market Size, growth, trends analysis & forecast 2030, Facts and Factors. Available at: https://www.fnfresearch.com/industrial-robotics-market (Accessed: 11 October 2023).
Mobile Robots Market Size & Share Analysis – Industry Research Report – Growth Trends. Available at: https://www.mordorintelligence.com/industry-reports/global-mobile-robots-market (Accessed: 17 October 2023).
D. Hüsener, M. Schluse, D. Kaufmann, J. Roßmann, The Digital Twin as a Mediator for the Digitalization and Conservation of Expert Knowledge. (2022) Annals of scientific society for assembly, handling and Industrial Robotics 2021. Cham: Springer International Publishing.
Dzedzickis, A. et al. (2021) Advanced applications of industrial robotics: New trends and possibilities, MDPI. Available at: https://www.mdpi.com/2076-3417/12/1/135/htm (Accessed: 11 October 2023).
Müller R., Scholer, M., Karkowski, M.: Generic automation task description for flexible assembly systems. Proc. CIRP 81, 730–735 (2019). https://doi.org/10.1016/j.procir.2019.03.185
D. Shen, Y. Chen, L. Li, and S. Chien, “Collision-free path planning for automated vehicles risk assessment via predictive occupancy map,” in 2020 IEEE Intelligent Vehicles Symposium (IV), pp. 985–991, IEEE, 2020.
Active Collision Avoidance System for E-Scooters in Pedestrian Environment. Xuke Yan, Dan Shen. arXiv:2311.04383v1 [cs.RO] 7 Nov 2023
MROS: A framework for robot self-adaptation. Gustavo Rezende Silva, Darko Bozhinoski Mario Garzon Oviedo, Mariano Ramírez Montero, Nadia Hammoudeh Garcia. arXiv:2303.09227v1 [cs.RO] 16 Mar 2023
Mobile Robot Motion Control Using a Combination of Fuzzy Logic Method and Kinematic Model. Anh-Tu Nguyen, Cong-Thanh Vu. N. L. Anh et al. (Eds.): Intelligent Systems and Networks, LNNS 471, pp. 495–503, 2022. https://doi.org/10.1007/978-981-19-3394-3_56
A. Meduri, P. Shah, J. Viereck, M. Khadiv, I. Havoutis, and L. Righetti, “Biconmp: A nonlinear model predictive control framework for whole body motion planning,” IEEE Transactions on Robotics, vol. 39, no. 2, pp. 905–922, 2023.
F. Hoffmann, V. Wesskamp, R. Bleck, J. Deuse. Scalability of Assembly Line Automation Based on the Integrated Product Development Approach. (2022) Annals of scientific society for assembly, handling and Industrial Robotics 2021. Cham: Springer International Publishing.
Müller R., Kanso, A. and Adler, F. An approach to integrate a blockchain-based payment model and independent secure documentation for a robot as a Service, SpringerLink. Available at: https://link.springer.com/chapter/10.1007/978-3-030-74032-0_15 (Accessed: 11 October 2023).
Enes K. Web Service for Point Cloud Supported Robot Programming Using Machine Learning. (2022) Annals of scientific society for assembly, handling and Industrial Robotics 2021. Cham: Springer International Publishing.
John, J. et al. (2023) Industry 4.0 and Beyond: The role of 5g, WIFI 7, and TSN in enabling Smart Manufacturing, arXiv.org. Available at: https://arxiv.org/abs/2310.02379v1 (Accessed: 11 October 2023).
Cichon, T., Rossmann, J.: Digital twins: assisting and supporting cooperation in human-robot teams. In: Proceedings of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV 2018), November 18–21, 2018, Singapore, pp. 1–6 (2019)
Kawamura, K. and Browne, W. (2009) ‘Cognitive robotics’, Encyclopedia of Complexity and Systems Science, pp. 1109–1126. doi:10.1007/978-0-387-30440-3_74.
Katiyar, S. and Katiyar, K. (2021) ‘Recent trends towards Cognitive Science: From Robots to humanoids’, Cognitive Computing for Human-Robot Interaction, pp. 19–49. doi:10.1016/b978-0-323-85769-7.00012-4.
Tawiah, T. (2022) ‘Machine Learning and Cognitive Robotics: Opportunities and challenges’, Cognitive Robotics and Adaptive Behaviors [Preprint]. doi:10.5772/intechopen.107147.
Grieves, M., Vickers, J.: Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary Perspectives on Complex Systems, pp. 85–113. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-38756-7_4
Tao, F., Zhang, H., Liu, A., Nee, A.Y.C.: Digital twin in industry: state-of-the-art. IEEE Trans. Ind. Informat. 15, 2405–2415 (2019). https://doi.org/10.1109/TII.2018.2873186
Malm, T. et al. (2022) ‘Safety risk sources of autonomous mobile machines’, Open Engineering, 12(1), pp. 977–990. doi:10.1515/eng-2022-0377.
Bostelman, R. and Messina, E. (2019) ‘A-UGV capabilities’, 2019 Third IEEE International Conference on Robotic Computing (IRC) [Preprint]. doi:10.1109/irc.2019.00130.
Staff, R. 24/7 (2022) Decathlon deploys geek+ mobile robots in European e-commerce expansion, Robotics 24/7. Available at: https://www.robotics247.com/article/decathlon_deploys_geek_mobile_robots_european_ecommerce_expansion (Accessed: 29 November 2023).
Staff, A. (2022) Look back on 10 years of Amazon Robotics, US About Amazon. Available at: https://www.aboutamazon.com/news/operations/10-years-of-amazon-robotics-how-robots-help-sort-packages-move-product-andimprove-
safety (Accessed: 09 November 2023).
Joseph Quinlivan, V.P.F.T. and R. at A. (2023) How Amazon deploys collaborative robots in its operations to benefit employees and customers, US About Amazon. Available at: https://www.aboutamazon.com/news/operations/howamazon-deploys-robots-in-its-operations-facilities (Accessed: 09 November 2023).
Lambert, F. (2020) Tesla Gigafactory: A look at the robots and ‘machine building the machine’ at the Battery Factory, Electrek. Available at: https://electrek.co/2016/07/31/tesla-gigafactory-robots-machines-battery-factory/ (Accessed: 09 November 2023).
2022 top Article – How Tesla used robotics to survive (no date) RoboticsTomorrow. Available at: https://www. roboticstomorrow.com/article/2022/06/2022-top-article-how-tesla-used-robotics-to-survive-production-hell-andbecame-the-worlds-most-advanced-car-manufacturer/18908 (Accessed: 09 November 2023).
