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A semantic-driven tradespace framework to accelerate aircraft manufacturing system design

Author

Listed:
  • Xiaochen Zheng

    (Ecole Polytechnique Fédérale de Lausanne (EPFL))

  • Xiaodu Hu

    (Fraunhofer IAO)

  • Rebeca Arista

    (Airbus SAS
    Universidad de Sevilla)

  • Jinzhi Lu

    (Ecole Polytechnique Fédérale de Lausanne (EPFL))

  • Jyri Sorvari

    (Visual Components)

  • Joachim Lentes

    (Fraunhofer IAO)

  • Fernando Ubis

    (Visual Components)

  • Dimitris Kiritsis

    (Ecole Polytechnique Fédérale de Lausanne (EPFL))

Abstract

During the design phase of an aircraft manufacturing system, different industrial scenarios need to be evaluated according to key performance indicators to achieve the optimal system performance. It is a highly complex process involving multidisciplinary stakeholders, various digital tools and protocols. To address the digital discontinuity challenge during this process, this paper proposes a tradespace framework based on semantic technology and model-based systems engineering. It aims at functionality integration of requirement management, architecture definition, manufacturing system design, solution verification and visualization. An application ontology is developed to integrate assembly system domain knowledge, industrial requirements and system architecture model information. The proposed framework is implemented in a case study to support the fuselage orbital joint process design, which is part of the aircraft final assembly line. A toolchain is presented to support the implementation, which consists of a set of enabling software corresponding to the functional modules of the framework. Different manufacturing system architectures are first designed by industrial system engineers supported by the application ontology stored in a graph database. They are then analyzed through Discrete Event Simulations and 3D simulations. The simulation results are presented through a web-based portal to show the key performance values of each architecture. This study serves as a part of the proof-of-concept of the recently proposed Cognitive Digital Twin concept.

Suggested Citation

  • Xiaochen Zheng & Xiaodu Hu & Rebeca Arista & Jinzhi Lu & Jyri Sorvari & Joachim Lentes & Fernando Ubis & Dimitris Kiritsis, 2024. "A semantic-driven tradespace framework to accelerate aircraft manufacturing system design," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 175-198, January.
    • Handle: RePEc:spr:joinma:v:35:y:2024:i:1:d:10.1007_s10845-022-02043-7
    DOI: 10.1007/s10845-022-02043-7
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    References listed on IDEAS

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    1. Peter Chhim & Ratna Babu Chinnam & Noureddin Sadawi, 2019. "Product design and manufacturing process based ontology for manufacturing knowledge reuse," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 905-916, February.
    2. Asma Talhi & Virginie Fortineau & Jean-Charles Huet & Samir Lamouri, 2019. "Ontology for cloud manufacturing based Product Lifecycle Management," Journal of Intelligent Manufacturing, Springer, vol. 30(5), pages 2171-2192, June.
    3. Soumaya El Kadiri & Dimitris Kiritsis, 2015. "Ontologies in the context of product lifecycle management: state of the art literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(18), pages 5657-5668, September.
    4. Eeva Järvenpää & Niko Siltala & Otto Hylli & Minna Lanz, 2019. "The development of an ontology for describing the capabilities of manufacturing resources," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 959-978, February.
    5. Malik Khalfallah & Nicolas Figay & Catarina Ferreira Da Silva & Parisa Ghodous, 2016. "A cloud-based platform to ensure interoperability in aerospace industry," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 119-129, February.
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