定制化产品智能设计关键技术研究综述

工程(英文) ›› 2017, Vol. 3 ›› Issue (5) : 631-640.

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PDF(4339 KB)
工程(英文) ›› 2017, Vol. 3 ›› Issue (5) : 631-640. DOI: 10.1016/J.ENG.2017.04.005
研究论文
Research

定制化产品智能设计关键技术研究综述

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A Research Review on the Key Technologies of Intelligent Design for Customized Products

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History +

Abstract

The development of technologies such as big data and cyber-physical systems (CPSs) has increased the demand for product design. Product digital design involves completing the product design process using advanced digital technologies such as geometry modeling, kinematic and dynamic simulation, multi-disciplinary coupling, virtual assembly, virtual reality (VR), multi-objective optimization (MOO), and human-computer interaction. The key technologies of intelligent design for customized products include: a description and analysis of customer requirements (CRs), product family design (PFD) for the customer base, configuration and modular design for customized products, variant design for customized products, and a knowledge push for product intelligent design. The development trends in intelligent design for customized products include big-data-driven intelligent design technology for customized products and customized design tools and applications. The proposed method is verified by the design of precision computer numerical control (CNC) machine tools.

Keywords

Customized products / Customer requirements / Variant design / Intelligent design / Knowledge push

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. . Engineering. 2017, 3(5): 631-640 https://doi.org/10.1016/J.ENG.2017.04.005

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Acknowledgements

The work presented in this article is funded by the National Natural Science Foundation of China (51375012 and 51675478), the Science and Technology Plan Project of Zhejiang Province (2017C31002), and the Fundamental Research Funds for the Central Universities (2017FZA4003).

Compliance with ethics guidelines

Shuyou Zhang, Jinghua Xu, Huawei Gou, and Jianrong Tan declare that they have no conflict of interest or financial conflicts to disclose.

版权

2017 2017 THE AUTHORS. Published by Elsevier LTD on behalf of the Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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