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

被引:0
作者
Xiaochen Zheng
Xiaodu Hu
Rebeca Arista
Jinzhi Lu
Jyri Sorvari
Joachim Lentes
Fernando Ubis
Dimitris Kiritsis
机构
[1] Ecole Polytechnique Fédérale de Lausanne (EPFL),
[2] Fraunhofer IAO,undefined
[3] Airbus SAS,undefined
[4] Universidad de Sevilla,undefined
[5] Visual Components,undefined
来源
Journal of Intelligent Manufacturing | 2024年 / 35卷
关键词
Semantic; Ontology; Manufacturing system; Aircraft assembly system; Systems engineering; Cognitive Digital Twin;
D O I
暂无
中图分类号
学科分类号
摘要
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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页码:175 / 198
页数:23
相关论文
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