Top

Published in:

2024 | OriginalPaper | Chapter

Exploring the Potential of Digital Twins for New Product Design and Development: A Review of Research Gaps

Authors : Adeniyi Sobowale, Helena Lopes, Justyna Trojanowska, Ana Lima, Pedro Marujo, Jose Machado

Published in: Advances in Manufacturing IV

Publisher: Springer Nature Switzerland

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

A rapidly developing technology, digital twins have the potential to completely change how products are designed and developed. Digital twins enable the simulation of the performance of various design concepts, the identification of potential issues with a design, and the optimization of the design for certain performance needs. However, in terms of digital twins and their utilization in product development, there are some gaps in the existing literature. There is also a lack of a standardized digital twin framework. There is currently no structure for creating and utilizing digital twins that is universally approved. Because of this, it is challenging for many organizations to share and work together on digital twin initiatives. Another aspect to consider is the huge investment of putting digital twin technology into practice. Implementing digital twin technology can be costly, particularly for large and complicated products. This may prevent small and medium-sized firms from adopting the technology. Real-time data integration is also lacking. For digital twins to be accurate, the physical product must provide real-time data. Getting real-time data from sensors and other devices might, however, be challenging to include into the digital twin. This paper examines the bibliographic research gaps concerning the use of digital twins specifically for new product design and development. The report also addresses some solutions and how the limitations might affect the development of digital twin technologies in the future.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

next chapter Innovation of the Manufacturing Company by Using of Digitization Tools

Ke, G., et al.: Intelligent machine plus production line digital twin model construction technology. In: Journal of Physics: Conference Series, vol. 2478, no. 10, p. 102011 (2023). https://doi.org/10.1088/1742-6596/2478/10/102011

Lo, C.K., Chen, C.H., Zhong, R.Y.: A review of digital twin in product design and development. Adv. Eng. Inf. 48, 101297 (2021). https://doi.org/10.1016/j.aei.2021.101297CrossRef

Liu, M., Fang, S., Dong, H., Xu, C.: Review of digital twin about concepts, technologies, and industrial applications. J. Manuf. Syst. 58, 346–361 (2021). https://doi.org/10.1016/j.jmsy.2020.06.017CrossRef

Böttjer, T., et al.: A review of unit level digital twin applications in the manufacturing industry. CIRP J. Manuf. Sci. Technol. 45, 162–189 (2023). https://doi.org/10.1016/j.cirpj.2023.06.011CrossRef

Schleich, B., Anwer, N., Mathieu, L., Wartzack, S.: Shaping the digital twin for design and production engineering. CIRP Ann. 66(1), 141–144 (2017). https://doi.org/10.1016/j.cirp.2017.04.040CrossRef

Grieves, M.W.: Product lifecycle management: the new paradigm for enterprises. Int. J. Prod. Dev. 2(1–2), 71–84 (2005). https://doi.org/10.1504/IJPD.2005.006669CrossRef

Grieves, M.: Product lifecycle management: driving the next generation of lean thinking | CiNii Research (2006). Accessed 17 July 2023. https://cir.nii.ac.jp/crid/1130000796648190464

Grieves, M.: Origins of the Digital Twin Concept (2016). https://doi.org/10.13140/RG.2.2.26367.61609

Hribernik, K.A., Rabe, L., Thoben, K.D., Schumacher, J.: The product avatar as a product-instance-centric information management concept. Int. J. Prod. Lifecycle Manag. 1(4), 367–379 (2006). https://doi.org/10.1504/IJPLM.2006.011055CrossRef

10.

Garner, T., Powell, W., Carr, V.: Virtual carers for the elderly: a case study review of ethical responsibilities (2016). Accessed 10 July 2023. https://doi.org/10.1177/2055207616681173

11.

Hribernik, K., Wuest, T., Thorben, K.-D.: Towards product avatars representing middle-of-life information for improving design, development and manufacturing processes (2013). Accessed 07 July 2023. https://doi.org/10.1007/978-3-642-41329-2_10

12.

Rios, J., Hernandez, J.C., Oliva, M., Mas, F.: Product avatar as digital counterpart of a physical individual product: literature review and implications in an aircraft. In: Transdisciplinary Lifecycle Analysis of Systems, pp. 657–666. IOS Press (2015). https://doi.org/10.3233/978-1-61499-544-9-657

13.

Wuest, T., Hribernik, K., Thoben, K.D.: Accessing servitisation potential of PLM data by applying the product avatar concept. Prod. Plan. Control 26(14–15), 1198–1218 (2015). https://doi.org/10.1080/09537287.2015.1033494CrossRef

14.

Fuller, A., Fan, Z., Day, C., Barlow, C.: Digital twin: enabling technologies, challenges and open research. IEEE Access 8, 108952–108971 (2020). https://doi.org/10.1109/ACCESS.2020.2998358CrossRef

15.

Schuh, G., Rebentisch, E., Riesener, M., Ipers, T., Tönnes, C., Jank, M.H.: Data quality program management for digital shadows of products. Procedia CIRP 86, 43–48 (2019). https://doi.org/10.1016/j.procir.2020.01.027CrossRef

16.

Ploeger, D.: Digital Parts/Modular Doubles: fragmenting the ‘digital double’. Body Space Technol. 10(1) (2011). https://doi.org/10.16995/bst.92

17.

Glaessgen, E., Stargel, D.: The digital twin paradigm for future NASA and U.S. air force vehicles. In: 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, American Institute of Aeronautics and Astronautics (2012). https://doi.org/10.2514/6.2012-1818

18.

Loaiza, J.H., Cloutier, R.J.: Analyzing the implementation of a digital twin manufacturing system: using a systems thinking approach. Systems 10(2), 22 (2022). https://doi.org/10.3390/systems10020022CrossRef

19.

Luo, W., Tianliang, H., Wendan, Z., Fei, T.: Digital twin modeling method for CNC machine tool. IEEE Conference Publication | IEEE Xplore (2018). Accessed 06 July 2023. https://ieeexplore.ieee.org/abstract/document/8361285?casa_token=Laaxv5POraQAAAAA:6MWesh-wTmhcY_5R482yC-4sFr5edcUFtJ_KCDe7-0hPlU9eQJAB_6RqufbFFaouzwYbilYiTA

20.

Semeraro, C., Lezoche, M., Panetto, H., Dassisti, M.: Digital twin paradigm: a systematic literature review. Comput. Ind. 130, 103469 (2021). https://doi.org/10.1016/j.compind.2021.103469CrossRef

21.

Söderberg, R., Wärmefjord, K., Carlson, J.S., Lindkvist, L.: Toward a Digital Twin for real-time geometry assurance in individualized production. CIRP annals 66(1), 137–140 (2017). https://doi.org/10.1016/j.cirp.2017.04.038CrossRef

22.

Schweigert-Recksiek, S., Trauer, J., Engel, C., Spreitzer, K., Zimmermann, M.: Conception of a digital twin in mechanical engineering–a case study in technical product development. In: Proceedings of the Design Society: DESIGN Conference, vol. 1, pp. 383–392 (2020). https://doi.org/10.1017/dsd.2020.23

23.

Yao, J.F., Yang, Y., Wang, X.C., Zhang, X.P.: Systematic review of digital twin technology and applications. Visual Comput. Ind. Biomed. Art 6(1), 10 (2023). https://doi.org/10.1186/s42492-023-00137-4CrossRef

24.

Abramovici, M., Göbel, J.C., Savarino, P.: Reconfiguration of smart products during their use phase based on virtual product twins. CIRP Annals 66(1), 165–168 (2017). https://doi.org/10.1016/j.cirp.2017.04.042CrossRef

25.

Alcácer, V., Cruz-Machado, V.: Scanning the industry 4.0: a literature review on technologies for manufacturing systems. Eng. Sci. Technol. Int. J. 22(3), 899–919 (2019). https://doi.org/10.1016/j.jestch.2019.01.006CrossRef

26.

Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., Sui, F.: Digital twin-driven product design, manufacturing and service with big data. Int. J. Adv. Manuf. Technol. 94, 3563–3576 (2018). https://doi.org/10.1007/s00170-017-0233-1CrossRef

27.

Tao, F., et al.: Digital twin-driven product design framework. Int. J. Prod. Res. 57(12), 3935–3953 (2019). https://doi.org/10.1080/00207543.2018.1443229CrossRef

28.

Durão, L.F.C.S., Haag, S., Anderl, R., Schützer, K., Zancul, E.: Digital twin requirements in the context of Industry 4.0. In: Chiabert, P., Bouras, A., Noël, F., Ríos, J. (eds.) PLM 2018. IAICT, vol. 540, pp. 204–214. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01614-2_19CrossRef

29.

Neto, A. A., da Silva, E.R., Deschamps, F., do Nascimento Junior, L.A., de Lima, E.P.: Modeling production disorder: procedures for digital twins of flexibility-driven manufacturing systems. Int. J. Prod. Econ. 260, 108846 (2023). https://doi.org/10.1016/j.ijpe.2023.108846

30.

Longo, F., Nicoletti, L., Padovano, A.: Ubiquitous knowledge empowers the smart factory: the impacts of a service-oriented digital twin on enterprises’ performance. Ann. Rev. Control 47, 221–236 (2019). https://doi.org/10.1016/j.arcontrol.2019.01.001CrossRef

31.

Stark, R., Fresemann, C., Lindow, K.: Development and operation of Digital Twins for technical systems and services. CIRP Ann. 68(1), 129–132 (2019). https://doi.org/10.1016/j.cirp.2019.04.024CrossRef

32.

Luo, W., Hu, T., Zhang, C., Wei, Y.: Digital twin for CNC machine tool: modeling and using strategy. J. Ambient Intell. Humanized Comput. 10, 1129–1140 (2019). https://doi.org/10.1007/s12652-018-0946-5CrossRef

33.

Aivaliotis, P., Georgoulias, K., Arkouli, Z., Makris, S.: Methodology for enabling Digital Twin using advanced physics-based modelling in predictive maintenance. Procedia Cirp 81, 417–422 (2019). https://doi.org/10.1016/j.procir.2019.03.072CrossRef

34.

Bao, J., Guo, D., Li, J., Zhang, J.: The modelling and operations for the digital twin in the context of manufacturing. Enterp. Inf. Syst. 13(4), 534–556 (2019). https://doi.org/10.1080/17517575.2018.1526324CrossRef

35.

Ghosh, A.K., Ullah, A.S., Teti, R., Kubo, A.: Developing sensor signal-based digital twins for intelligent machine tools. J. Ind. Inf. Integrat. 24, 100242 (2021). https://doi.org/10.1016/j.jii.2021.100242CrossRef

36.

Sudarsan, R., Fenves, S.J., Sriram, R.D., Wang, F.: A product information modeling framework for product lifecycle management. Comput.-Aided Des. 37(13), 1399–1411 (2005). https://doi.org/10.1016/j.cad.2005.02.010CrossRef

37.

Ming, X.G., et al.: Collaborative process planning and manufacturing in product lifecycle management (2008). Accessed 10 July 2023. https://www.sciencedirect.com/science/article/pii/S0166361507001005

38.

Alam, M.D., Kabir, G., Mirmohammadsadeghi, S.: A digital twin framework development for apparel manufacturing industry. Decis. Anal. J. 7, 100252 (2023). https://doi.org/10.1016/j.dajour.2023.100252CrossRef

39.

Campi, F., Favi, C., Germani, M., Mandolini, M.: CAD-integrated design for manufacturing and assembly in mechanical design. Int. J. Comput. Integr. Manuf. 35(3), 282–325 (2022). https://doi.org/10.1080/0951192X.2021.1992659CrossRef

40.

Zhang, S., et al.: Digital Twin of a Generic Jack-Up Platform (2023). https://doi.org/10.4043/32221-MS

41.

Classens, K., Heemels, W.M., Oomen, T.: Digital twins in mechatronics: from model-based control to predictive maintenance. In: 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI), pp. 336–339 (2021). https://doi.org/10.1109/DTPI52967.2021.9540144

42.

Monsone, C., Mercier-Laurent, E., János, J.: The overview of digital twins in Industry 4.0: managing the whole ecosystem. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, pp. 271–276 (2019). SCITEPRESS - Science and Technology Publications, Vienna. doi: https://doi.org/10.5220/0008348202710276

43.

Lim, K.Y.H., Zheng, P., Chen, C.H.: A state-of-the-art survey of Digital Twin: techniques, engineering product lifecycle management and business innovation perspectives. J. Intell. Manuf. 31, 1313–1337 (2020). https://doi.org/10.1007/s10845-019-01512-wCrossRef

44.

Caesar, B., Hanel, A., Wenkler, E., Corinth, C., Ihlenfeldt, S., Fay, A.: Information model of a digital process twin for machining processes. In: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) pp. 1765–1772. IEEE, Vienna (2020). https://doi.org/10.1109/ETFA46521.2020.9212085

45.

Liu, J., Du, X., Zhou, H., Liu, X., Ei Li, L., Feng, F.: A digital twin-based approach for dynamic clamping and positioning of the flexible tooling system. Procedia CIRP 80, 746–749 (2019). https://doi.org/10.1016/j.procir.2019.01.063CrossRef

46.

Mabkhot, M.M., Al-Ahmari, A.M., Salah, B., Alkhalefah, H.: Requirements of the smart factory system: a survey and perspective. Machines 6(2), 23 (2018). https://doi.org/10.3390/machines6020023CrossRef

47.

Bianconi, C., Bonci, A., Monteriù, A., Pirani, M., Prist, M., Taccari, L.: System thinking approach for digital twin analysis. In: 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), pp. 1–7 (2020). https://doi.org/10.1109/ICE/ITMC49519.2020.9198392

48.

Howard, D.: The digital twin: virtual validation in electronics development and design. In: 2019 Pan Pacific Microelectronics Symposium (Pan Pacific), pp. 1–9 (2019). https://doi.org/10.23919/PanPacific.2019.8696712

49.

Lee, D., et al.: Digital twin-based analysis and optimization for design and planning of production lines. Machines 10(12), 1147 (2022). https://doi.org/10.3390/machines10121147CrossRef

50.

Pires, F., Ahmad, B., Moreira, A.P., Leitão, P.: Recommendation system using reinforcement learning for what-if simulation in digital twin. In: 2021 IEEE 19th International Conference on Industrial Informatics (INDIN), pp. 1–6 (2021). https://doi.org/10.1109/INDIN45523.2021.9557372

51.

Bao, Q., Zhao, G., Yu, Y., Dai, S., Wang, W.: Ontology-based modeling of part digital twin oriented to assembly. Proc. Inst. Mech. Engineers Part B: J. Eng. Manuf. 236(1–2), 16–28 (2022). https://doi.org/10.1177/0954405420941160CrossRef

52.

Somers, R.J., Douthwaite, J.A., Wagg, D.J., Walkinshaw, N., Hierons, R.M.: Digital-twin-based testing for cyber–physical systems: a systematic literature review. Inf. Softw. Technol. 156, 107145 (2023). https://doi.org/10.1016/j.infsof.2022.107145CrossRef

53.

Qi, Q., et al.: Enabling technologies and tools for digital twin. J. Manuf. Syst. 58, 3–21 (2021). https://doi.org/10.1016/j.jmsy.2019.10.001CrossRef

54.

Ritto, T.G., Rochinha, F.A.: Digital twin, physics-based model, and machine learning applied to damage detection in structures. Mech. Syst. Signal Process. 155, 107614 (2021). https://doi.org/10.1016/j.ymssp.2021.107614CrossRef

55.

Archana, K., Saranya, K.G.: Crop yield prediction, forecasting and fertilizer recommendation using voting based ensemble classifier. SSRG Int. J. Comput. Sci. Eng. 7(5), 1–4 (2020). https://doi.org/10.14445/23488387/IJCSE-V7I5P101

56.

Kapteyn, M.G., Knezevic, D.J., Huynh, D.B.P., Tran, M., Willcox, K.E.: Data-driven physics-based digital twins via a library of component-based reduced-order models. Int. J. Numer. Methods Eng. 123(13), 2986–3003 (2022). https://doi.org/10.1002/nme.6423CrossRef

Title: Exploring the Potential of Digital Twins for New Product Design and Development: A Review of Research Gaps
Authors: Adeniyi Sobowale
Helena Lopes
Justyna Trojanowska
Ana Lima
Pedro Marujo
Jose Machado
Publisher: Springer Nature Switzerland
Book: Advances in Manufacturing IV
Print ISBN: 978-3-031-56446-8

Electronic ISBN: 978-3-031-56444-4

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-56444-4_1

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner