Abstract
With the development and application of cyber-physical systems (CPS) in Smart manufacturing, a broad spectrum of possible improvements has emerged, thereby a big step forward can be made in hydraulic systems. This paper presents an approach for implementing artificial intelligence (AI) in the concept of smart hydraulic press with regard to I4.0 technology. Conceptual solutions for greater system flexibility and improved blanket formability focus on designing a suitable concept for cyber-physical systems in combination with the digital twin. The main challenge is to develop a suitable AI-based algorithm in the manufacturing execution system (MES) so that the system is able to improve the forming process and avoid disturbances in real time. The concept of visualization and data analysis based on real-time monitoring of parameters of a smart hydraulic press is presented. With a continuous quality control of the products a more sophisticated system can be achieved. The main advantage to take into account in terms of hydraulics and Manufacturing as a Service (MaaS) are the new trends in energy efficiency of the systems and rapid automatic tool exchange.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bauernhansel, T., et al.: WGP-Standpunkt Industrie 4.0. Available via DIALOG (2016). https://wgp.de/wp-content/uploads/WGP-Standpunkt_Industrie_4-0.pdf. Accessed 14 Apr 2020
Tao, F., et al.: Digital twins and cyber-physical systems toward smart manufacturing and industry 4.0: correlation and comparison. Engineering 5, 653–661 (2019)
Barasuol, V., et al.: Highly-integrated hydraulic smart actuators and smart manifolds for high-bandwidth force control. Front. Robot. AI 5, 137–150 (2018)
Schuler (2020). https://www.schulergroup.com. Accessed 14 Apr 2020
Bosch Rexroth (2020). https://www.boschrexroth.com/en/xc. Accessed 14 Apr 2020
Nord, J.H., et al.: The internet of things: review and theoretical framework. Expert Syst. Appl. 133, 97–108 (2019)
Parrott, A., Warshaw, L.: Industry 4.0 and the digital twin, p. 17. Deloitte University Press (2017)
Ferreira, J.A., et al.: Close loop control of a hydraulic press for springback analysis. J. Mater. Process. Technol. 177, 377–381 (2006)
Zhang, Z. et al.: Research on Springback control in stretch bending based on iterative compensation method. Math. Prob. Eng. (2019). ID 2025717
Dion, B.: Creating a Digital Twin for a Pump. Available vie DIALOG (2017). https://www.ansys.com/-/media/ansys/corporate/resourcelibrary/article/creating-a-digital-twin-for-a-pump-aa-v11-i1.pdf. Accessed 14 Apr 2020
Xie, J., et al.: Virtual monitoring method for hydraulic supports based on digital twin theory. Mining Technol. 128, 77–87 (2019)
Mittal, S. et al.: Smart manufacturing: Characteristics, technologies and enabling factors. Proc. Inst. Mech. Eng. Part B. J. Eng. Manuf. (2017). January 2019. Special Section: Smart Manufacturing and Digital Factory, Vol. 233(5), ResearchGate, pp. 1342–1361
Linjama, M. et al.: High-performance digital hydraulic tracking control of a mobile boom Mockup Adj. In: 10th International Fluid Power Conference, Dresden, Germany, March 2016, Digital Hydraulics, Paper A-1, pp. 37–48 (2016)
Wang, S., et al.: Implementing smart factory of industrie 4.0: an outlook. Int. J. Distrib. Sensor Netw. 12(1) (20116). ID: 3159805
Resman, M., et al.: A new architecture model for smart manufacturing: a performance analysis and comparison with the RAMI 4.0 reference model. Adv. Prod. Eng. Manag. 14, 153–165 (2019)
Tao, F., et al.: Digital twin-driven product design framework. Int. J. Prod. Res. 57, 3935–3953 (2019)
Glaessgen, E.H., Stargel, D.S.: The digital twin paradigm for future NASA and U.S. Air force vehicles. 53rd Structures, Structural Dynamics, and Materials Conference, Hawaii, April 2012. Special session on the Digital Twin, US, NASA Technical Reports Server (2012)
Lee, J. et al.: Recent advances and trends in predictive manufacturing systems in big data environment. In: Conference on Industrial Informatics, Germany, July 2013, Manufacturing Letter, vol. 1, pp. 38–41. Elsevier, US (2013)
Rojko, A.: Industry 4.0 concept: background and overview. Int. J. Interact. Mobile Technol. (iJIM) 11, 77–90 (2008)
Alcácer, V., Cruz-Machado, V.: Scanning the Industry 4.0: a literature review on technologies for manufacturing systems. Eng. Sci. Technol. Int. J. 22, 899–919 (2019)
Fillatreau, P., et al.: Sheet metal forming global control system based on artificial vision system and force-acoustic sensors. Robot Comput. Integr. Manuf. 24, 780–787 (2008)
Li, L., et al.: An energy-saving method to solve the mismatch between installed and demanded power in hydraulic press. J. Cleaner Prod. 139, 636–645 (2016)
Meermann, L., et al.: Sensors as drivers of Industry 4.0. Available via DIALOG (2019). https://assets.ey.com/content/dam/ey-sites/ey-com/de_de/topics/industrial-products/ey-study-sensors-as-drivers-of-industry-4-0.pdf?download. Accessed 12 Feb 2020
Acknowledgment
The work was carried out in the framework of the GOSTOP program (OP20.00361), which is partially financed by the Republic of Slovenia – Ministry of Education, Science and Sport, and the European Union – European Regional Development Fund. The authors also acknowledge the financial support from the Slovenian Research Agency (research core funding No. (P2–0248)).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Jankovič, D., Šimic, M., Herakovič, N. (2021). The Concept of Smart Hydraulic Press. In: Borangiu, T., Trentesaux, D., Leitão, P., Cardin, O., Lamouri, S. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2020. Studies in Computational Intelligence, vol 952. Springer, Cham. https://doi.org/10.1007/978-3-030-69373-2_29
Download citation
DOI: https://doi.org/10.1007/978-3-030-69373-2_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-69372-5
Online ISBN: 978-3-030-69373-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)