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工程设计学报
Chinese Journal of Engineering Design  2007, Vol. 14 Issue (3): 199-203    DOI:
    
Configuration design based on BP neural network for ETO product
DING  Jun-Jian,TAN  Shi-Li,SONG  Xiao-Feng,SUN  Ya-Jie
School of Mechanical & Electronic Engineering and Automation, Shanghai University, Shanghai 200072, China
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Abstract  Customized product of ETO (engineering-to-order) is hard to program and realize to automation due to the complex structure of its product family, bigdifference between product structures, involvement of personal experience and inspiration during design process, and a large amount of interaction between human and machine. Artificial neural network can simulate the structure of human brain and intelligent behavior, and have the ability of parallel processing, redundancy, self-organization, self-adaptation and association, which accords with the features of configuration design. Through analysis of ETO customized product requirements, a BP artificial neural network with some structure and function isestablished and trained. The trained network contains rules and experiences of ETO configuration design. Illustrations have demonstrated its feasibility.

Key words： engineering-to-order      artifical neural networks      configuration design     
Published: 28 June 2007
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Cite this article:

DING Jun-Jian,TAN Shi-Li,SONG Xiao-Feng,SUN Ya-Jie. Configuration design based on BP neural network for ETO product. Chinese Journal of Engineering Design, 2007, 14(3): 199-203.

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https://www.zjujournals.com/gcsjxb/     OR     https://www.zjujournals.com/gcsjxb/Y2007/V14/I3/199


基于BP神经网络的ETO产品配置设计方法

按订单设计(engineering-to-order, ETO)的定制产品因产品族结构比较复杂，产品间结构差异较大，设计过程涉及个人经验和灵感，并大量应用人机交互处理，难以实现设计自动化、程序化。人工神经网络模仿人脑结构及智能行为，具有大规模并行处理、容错、自组织和自适应能力及联想功能，符合ETO配置设计的特点。通过对ETO定制产品需求的分析，构建并训练具有一定结构和功能的BP神经网络，训练好的网络蕴含着ETO配置设计规则和经验。实例证明了该方法的可行性。

关键词： 按订单设计,  人工神经网络,  配置设计 
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