面向航空智能制造的DT与AI融合应用

隋少春; 许艾明; 黎小华; 刘顺涛; 黄伟

doi:10.7527/S1000-6893.2020.24173

航空学报 >

2020 , Vol. 41 >Issue 7: 624173 - 624173

DOI: https://doi.org/10.7527/S1000-6893.2020.24173

先进制造技术与装备专栏

面向航空智能制造的DT与AI融合应用

隋少春 ,
许艾明 ,
黎小华 ,
刘顺涛 ,
黄伟

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航空工业成都飞机工业(集团)有限责任公司, 成都 610091

收稿日期: 2020-04-30

修回日期: 2020-05-04

网络出版日期: 2020-06-04

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Fusion application of DT and AI for aviation intelligent manufacturing

SUI Shaochun ,
XU Aiming ,
LI Xiaohua ,
LIU Shuntao ,
HUANG Wei

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AVIC Chengdu Aircraft Industrial(Group) Co., Ltd., Chengdu 610091, China

Received date: 2020-04-30

Revised date: 2020-05-04

Online published: 2020-06-04

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摘要

针对航空装备复杂制造场景下制造过程管控维度多尺度大、制造资源组成复杂性高、质量问题跟踪定位难度大等问题，结合数字孪生（DT）与人工智能（AI）技术特点，开展了面向航空智能制造的DT与AI融合应用研究。基于数字孪生与人工智能应用现状，系统性地阐述了数字孪生与人工智能融合机理，分析了支撑数字孪生与人工智能融合驱动航空智能制造的关键技术和数字孪生与人工智能融合驱动的AI控制中心构建涉及的关键问题，在此基础上重点讨论了加工制造过程自适应控制、智能车间生产过程智能管控、制造过程资源调度与优化决策、产品智能质量控制等应用场景，为数字孪生与人工智能在航空智能制造融合应用提供参考。

关键词： 航空装备; 智能制造; 数字孪生; 人工智能; 融合应用

本文引用格式

隋少春 , 许艾明 , 黎小华 , 刘顺涛 , 黄伟 . 面向航空智能制造的DT与AI融合应用[J]. 航空学报, 2020 , 41(7) : 624173 -624173 . DOI: 10.7527/S1000-6893.2020.24173

Abstract

Aiming at the problems of multi-dimensional and multi-scale manufacturing process management and control, high complexity of manufacturing resources composition, and difficulty in tracking and locating quality problems in complex manufacturing scenarios of aviation equipment, combined with the technical characteristics of Digital Twin (DT) and Artificial Intelligence (AI), the research on the fusion application of DT and AI for aviation intelligent manufacturing is carried out. Based on the application status of digital twin and artificial intelligence, this paper systematically expounded the fusion mechanism of digital twin and artificial intelligence, analyzed the key technologies that support the fusion of digital twin and artificial intelligence to drive the aviation intelligent manufacturing and the key issues involved in the construction of AI control center driven by the fusion of digital twin and artificial intelligence. On this basis, the application scenarios such as adaptive control of manufacturing process, intelligent control of production process in intelligent workshop, resource scheduling and optimization decision-making in manufacturing process, and product intelligent quality control are discussed, which could provide reference for the fusion of digital twin and artificial intelligence in aviation intelligent manufacturing.

Key words： aviation equipment; intelligent manufacturing; DT; AI; fusion application

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