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research article

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

Zheng, Xiaochen  
•
Hu, Xiaodu
•
Arista, Rebeca
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October 25, 2022
Journal Of Intelligent Manufacturing

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.

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Type
research article
DOI
10.1007/s10845-022-02043-7
Web of Science ID

WOS:000871859200001

Author(s)
Zheng, Xiaochen  
Hu, Xiaodu
Arista, Rebeca
Lu, Jinzhi  
Sorvari, Jyri
Lentes, Joachim
Ubis, Fernando
Kiritsis, Dimitris  
Date Issued

2022-10-25

Publisher

SPRINGER

Published in
Journal Of Intelligent Manufacturing
Subjects

Computer Science, Artificial Intelligence

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Engineering, Manufacturing

•

Computer Science

•

Engineering

•

semantic

•

ontology

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manufacturing system

•

aircraft assembly system

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systems engineering

•

cognitive digital twin

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assembly system

•

models

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
SCI-STI-DK  
Available on Infoscience
November 7, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/192001
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