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On Web Digital Twins: an use case for a Gerotor pump

Published: 09 October 2023 Publication History

Abstract

In the current wave of digital industry, Digital Twins play a major role in the virtualization of manufacturing processes. Digital Twins are virtual entities that mirror the behavior of physical entitites. They are used to predict or monitor the information of a product or a process. In recent years, virtualization technologies have benefited from cloud computing and web-based services to enhance the capabilities of industrial Digital Twins. These Web Digital Twins enable greater degree of distribution and collaboration between the users of the Digital Twin. In this article we present an use case of web-based Digital Twins for the design and monitoring of Gerotor pumps. The novelties of the present article are: i) it highlights the advantages that result from applying the Digital Twin methodology to the case of Gerotor pumps, ii) it describes the implementation of a web-based Digital Twin tool for a Gerotor pump. Our tool allows the user to design a Gerotor pump using a parametric interface, visualize the 3D model of the pump, visualize its expected performance using fast simulation routines and obtain the optimum design for a set of desired performance parameters. This article focuses on the technological overview of the Digital Twin tool and its web-based architecture, as the simulation and optimization details were addressed in different publications.

References

[1]
Juuso Autiosalo, Riku Ala-Laurinaho, Joel Mattila, Miika Valtonen, Valtteri Peltoranta, and Kari Tammi. 2021. Towards integrated digital twins for industrial products: Case study on an overhead crane. Applied Sciences 11, 2 (2021), 683.
[2]
Roman Bambura, Marek Šolc, Miroslav Dado, and Luboš Kotek. 2020. Implementation of Digital Twin for Engine Block Manufacturing Processes. Applied Sciences 10, 18 (2020). https://www.mdpi.com/2076-3417/10/18/6578
[3]
Janet Barnabas and Pethuru Raj. 2020. The human body: A digital twin of the cyber physical systems. In Advances in Computers. Vol. 117. Elsevier, 219–246.
[4]
Peter Bauer, Bjorn Stevens, and Wilco Hazeleger. 2021. A digital twin of Earth for the green transition. Nature Climate Change 11, 2 (2021), 80–83.
[5]
Gordon S Blair. 2021. Digital twins of the natural environment. Patterns 2, 10 (2021), 100359.
[6]
Carlos A Bonilla, Ariele Zanfei, Bruno Brentan, Idel Montalvo, and Joaquín Izquierdo. 2022. A digital twin of a water distribution system by using graph convolutional networks for pump speed-based state estimation. Water 14, 4 (2022), 514.
[7]
Darya Botkina, Mikael Hedlind, Bengt Olsson, Jannik Henser, and Thomas Lundholm. 2018. Digital Twin of a Cutting Tool. Procedia CIRP 72 (2018), 215–218. https://doi.org/10.1016/j.procir.2018.03.178 51st CIRP Conference on Manufacturing Systems.
[8]
Alessandro Costantini, Giuseppe Di Modica, Jean Christian Ahouangonou, Doina Cristina Duma, Barbara Martelli, Matteo Galletti, Marica Antonacci, Daniel Nehls, Paolo Bellavista, Cedric Delamarre, 2022. IoTwins: Toward Implementation of Distributed Digital Twins in Industry 4.0 Settings. Computers 11, 5 (2022), 67.
[9]
Tianhu Deng, Keren Zhang, and Zuo-Jun Max Shen. 2021. A systematic review of a digital twin city: A new pattern of urban governance toward smart cities. Journal of Management Science and Engineering 6, 2 (2021), 125–134.
[10]
John Ahmet Erkoyuncu, Peter Butala, Rajkumar Roy, 2018. Digital twins: Understanding the added value of integrated models for through-life engineering services. Procedia Manufacturing 16 (2018), 139–146.
[11]
Tolga Erol, Arif Furkan Mendi, and Dilara Doğan. 2020. The digital twin revolution in healthcare. In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE, 1–7.
[12]
Pedro Javier Gamez-Montero, Esteve Codina, and Robert Castilla. 2019. A review of gerotor technology in hydraulic machines. Energies 12, 12 (2019), 2423.
[13]
Edward Glaessgen and David Stargel. 2012. The digital twin paradigm for future NASA and US Air Force vehicles. In 53rd AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics and materials conference 20th AIAA/ASME/AHS adaptive structures conference 14th AIAA. 1818.
[14]
Michael W Grieves. 2005. Product lifecycle management: the new paradigm for enterprises. International Journal of Product Development 2, 1-2 (2005), 71–84.
[15]
Lei He, Kai Wen, Jing Gong, and Changchun Wu. 2022. A multi-model ensemble digital twin solution for real-time unsteady flow state estimation of a pumping station. ISA transactions 126 (2022), 242–253.
[16]
Jani Hietala 2020. Real-time two-way data transfer with a digital twin via web interface. (2020).
[17]
Wei Hu, Kendrik Yan Hong Lim, and Yiyu Cai. 2022. Digital Twin and Industry 4.0 Enablers in Building and Construction: A Survey. Buildings 12, 11 (2022), 2004.
[18]
Yuchen Jiang, Shen Yin, Kuan Li, Hao Luo, and Okyay Kaynak. 2021. Industrial applications of digital twins. Philosophical Transactions of the Royal Society A 379, 2207 (2021), 20200360.
[19]
Pratik Kasat, Mrunal Kulkarni, Karthik Gundeti, Kunal Kangale, BB Deshmukh, and RD Mistry. 2023. Developing a digital twin of centrifugal pump for performance evaluation. Materials Today: Proceedings 72 (2023), 1798–1802.
[20]
Furkan Kosova and Hakki Ozgur Unver. 2023. A digital twin framework for aircraft hydraulic systems failure detection using machine learning techniques. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 237, 7 (2023), 1563–1580.
[21]
Zhongcheng Lei, Hong Zhou, Wenshan Hu, Guo-Ping Liu, Shiqi Guan, and Xingle Feng. 2021. Toward a web-based digital twin thermal power plant. IEEE Transactions on Industrial Informatics 18, 3 (2021), 1716–1725.
[22]
Deqing Li, Honghui Mei, Yi Shen, Shuang Su, Wenli Zhang, Junting Wang, Ming Zu, and Wei Chen. 2018. ECharts: a declarative framework for rapid construction of web-based visualization. Visual Informatics 2, 2 (2018), 136–146.
[23]
Weichao Luo, Tianliang Hu, Yingxin Ye, Chengrui Zhang, and Yongli Wei. 2020. A hybrid predictive maintenance approach for CNC machine tool driven by Digital Twin. Robotics and Computer-Integrated Manufacturing 65 (2020), 101974. https://doi.org/10.1016/j.rcim.2020.101974
[24]
Chris MacDonald, Bernard Dion, and Mohammad Davoudabadi. 2017. Creating a Digital Twin for a Pump. Ansys Advantage 1 (2017), 8–10.
[25]
M Mateev. 2020. Industry 4.0 and the digital twin for building industry. Industry 4.0 5, 1 (2020), 29–32.
[26]
Juan Pareja-Corcho, Aitor Moreno, Bruno Simoes, Asier Pedrera-Busselo, Ekain San-Jose, Oscar Ruiz-Salguero, and Jorge Posada. 2021. A Virtual Prototype for Fast Design and Visualization of Gerotor Pumps. Applied Sciences 11, 3 (2021), 1190.
[27]
Yangho Park, Jungyub Woo, and SangSu Choi. 2020. A cloud-based digital twin manufacturing system based on an interoperable data schema for smart manufacturing. International Journal of Computer Integrated Manufacturing 33, 12 (2020), 1259–1276.
[28]
Alessandro Ricci, Angelo Croatti, Stefano Mariani, Sara Montagna, and Marco Picone. 2022. Web of digital twins. ACM Transactions on Internet Technology 22, 4 (2022), 1–30.
[29]
Ehab Shahat, Chang T Hyun, and Chunho Yeom. 2021. City digital twin potentials: A review and research agenda. Sustainability 13, 6 (2021), 3386.
[30]
Liliana Stan, Adrian Florin Nicolescu, Cristina Pupăză, and Gabriel Jiga. 2022. Digital Twin and web services for robotic deburring in intelligent manufacturing. Journal of Intelligent Manufacturing (2022), 1–17.
[31]
Jan-Frederik Uhlenkamp, Jannicke Baalsrud Hauge, Eike Broda, Michael Lütjen, Michael Freitag, and Klaus-Dieter Thoben. 2022. Digital twins: A maturity model for their classification and evaluation. IEEE Access 10 (2022), 69605–69635.
[32]
Ján Vachálek, Lukás Bartalskỳ, Oliver Rovnỳ, Dana Šišmišová, Martin Morháč, and Milan Lokšík. 2017. The digital twin of an industrial production line within the industry 4.0 concept. In 2017 21st international conference on process control (PC). IEEE, 258–262.
[33]
Minglan Xiong and Huawei Wang. 2022. Digital twin applications in aviation industry: A review. The International Journal of Advanced Manufacturing Technology 121, 9-10 (2022), 5677–5692.
[34]
Bin Yang, Shuang Yang, Zhihan Lv, Faming Wang, and Thomas Olofsson. 2022. Application of digital twins and metaverse in the field of fluid machinery pumps and fans: A review. Sensors 22, 23 (2022), 9294.

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cover image ACM Conferences
Web3D '23: Proceedings of the 28th International ACM Conference on 3D Web Technology
October 2023
244 pages
ISBN:9798400703249
DOI:10.1145/3611314
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 09 October 2023

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Author Tags

  1. digital twins
  2. gerotor pumps
  3. industry 4.0
  4. simulation
  5. visualization
  6. web

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