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Digital twin of composite assembly manufacturing process

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  • Wilma Polini
  • Andrea Corrado

Abstract

Industry is facing the management of geometrical deviations along the entire lifecycle of the product. It is helped by digital twin tools that may minimise the geometrical deviations from nominal of products. The new digital twin tools allow to manage geometrical variations through a set of steps fully related by modern information and communication technologies that establish a continuous and unambiguous flow of information among the different steps of this digital process along the whole product lifecycle. They are based on data coming from manufacturing, assembly and inspection. The available large data sets from manufacturing and inspection allow to develop new and more accurate simulation models that realistically consider form deviations and process signature, i.e. the pattern left by the manufacturing process on the produced part surfaces. The present work introduces a digital twin tool to support the lightweight design of assemblies in composite material. It establishes a continuous and unambiguous flow of variation information from the part design to assembly, passing through manufacturing by considering the manufacturing signature. It was applied to a case study and the obtained results agree with the experimental ones.

Suggested Citation

  • Wilma Polini & Andrea Corrado, 2020. "Digital twin of composite assembly manufacturing process," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5238-5252, September.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:17:p:5238-5252
    DOI: 10.1080/00207543.2020.1714091
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    Cited by:

    1. Nguyen, Tiep & Duong, Quang Huy & Nguyen, Truong Van & Zhu, You & Zhou, Li, 2022. "Knowledge mapping of digital twin and physical internet in Supply Chain Management: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 244(C).
    2. Hazrathosseini, Arman & Moradi Afrapoli, Ali, 2023. "The advent of digital twins in surface mining: Its time has finally arrived," Resources Policy, Elsevier, vol. 80(C).
    3. Fuwen Hu & Song Bi & Yuanzhi Zhu, 2024. "Cooperative Game-Based Digital Twin Drives Decision Making: Overall Framework, Basic Formalization and Application Case," Mathematics, MDPI, vol. 12(2), pages 1-22, January.
    4. Kamble, Sachin S & Gunasekaran, Angappa & Parekh, Harsh & Mani, Venkatesh & Belhadi, Amine & Sharma, Rohit, 2022. "Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework," Technological Forecasting and Social Change, Elsevier, vol. 176(C).

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