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Engineering    2017, Vol. 3 Issue (5) : 631-640     https://doi.org/10.1016/J.ENG.2017.04.005
Research |
定制化产品智能设计关键技术研究综述
张树有,徐敬华(),苟华伟,谭建荣
State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
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摘要 大数据和信息物理系统(CPS)等技术的发展使人们对产品设计的需求增加。产品数字设计包括使用先进的数字技术完成产品设计过程,如几何建模、运动学和动态仿真、多学科耦合、虚拟装配、虚拟现实(VR)、多目标优化(MOO)以及人机交互。定制产品智能设计的关键技术包括:客户需求的描述与分析、客户基础的产品族设计(PFD)、定制产品的配置和模块化设计、定制产品的变型设计,以及产品智能设计的知识推送。定制产品智能设计的发展趋势包括定制产品的大数据驱动智能设计技术和定制的设计工具和应用。通过计算机的高精度数控机床设计,我们验证了该方法的有效性。
关键词 定制化产品用户需求变形设计智能设计知识推送    
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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Shuyou Zhang
Jinghua Xu
Huawei Gou
Jianrong Tan
引用本文:   
Shuyou Zhang,Jinghua Xu,Huawei Gou, et al. A Research Review on the Key Technologies of Intelligent Design for Customized Products[J]. Engineering, 2017, 3(5): 631-640.
网址:  
http://engineering.org.cn/EN/10.1016/J.ENG.2017.04.005     OR     http://engineering.org.cn/EN/Y2017/V3/I5/631
Fig.1  Layout scheme design for a lathe-mill cutting center.
Fig.2  Structural deformation of the third order modal of a gantry.
Fig.3  Structural deformation of the fourth order modal of a gantry.
Scheme 1 Scheme 2
Traverse path X/Y/Z (mm) 500/380/380 500/450/400
Drive power (40%/100% DC) (kW) 35/25 35/25
Maximum speed (r·min−1) 18?000 18?000
Torque (40% DC) (N·m) 130 121
Rapid traverse X/Y/Z (m·min−1) 80/50/50 60/60/30
Feed power (kN) 5.0 4.8
Fixed table-clamping area (mm) 800 × 500 700 × 500
Fixed table-clamping area maximum load (kg) 500 500
Rotary table-clamping area (mm) ϕ500 × 380 ϕ630 × 500
A swivel range (°) +90–−18 +110–−5
C swivel range (°) 360 360
Rotary table-clamping area maximum load (kg) 200 200/300
Control system Heidenhain iTNC 530 Heidenhain iTNC 530
Siemens 840D
Tab.1  A comparison of two design schemes for multi-axis machine tools.
Fig.4  Scheme 1 of a lathe-mill cutting center.
Fig.5  Scheme 2 of a lathe-mill cutting center.
Fig.6  An intelligent design for machine tools. DC: direct current.
Fig.7  The GUI for measuring EEGs.
Fig.8  (a) The relative voltage of the EEG and (b) spectral analysis for knowledge push.
Fig.9  The GUI of an accuracy allocation design among hierarchy kinematic chains.
Fig.10  The GUI of the intelligent design of a component and the complete machine of a lathe-mill cutting center.
Fig.11  Surface machining using a five-axis NC machine center with a 45° tilt head.
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