邓建新, 刘光明, 王令, 袁邦颐, 黄海宾. 制造工艺参数的智能优化设计方法进展[J]. 制造技术与机床, 2023, (5): 74-80. DOI: 10.19287/j.mtmt.1005-2402.2023.05.010
引用本文: 邓建新, 刘光明, 王令, 袁邦颐, 黄海宾. 制造工艺参数的智能优化设计方法进展[J]. 制造技术与机床, 2023, (5): 74-80. DOI: 10.19287/j.mtmt.1005-2402.2023.05.010
DENG Jianxin, LIU Guangming, WANG Ling, YUAN Bangyi, HUANG Haibin. Research progress of intelligent optimization design of manufacturing process parameters[J]. Manufacturing Technology & Machine Tool, 2023, (5): 74-80. DOI: 10.19287/j.mtmt.1005-2402.2023.05.010
Citation: DENG Jianxin, LIU Guangming, WANG Ling, YUAN Bangyi, HUANG Haibin. Research progress of intelligent optimization design of manufacturing process parameters[J]. Manufacturing Technology & Machine Tool, 2023, (5): 74-80. DOI: 10.19287/j.mtmt.1005-2402.2023.05.010

制造工艺参数的智能优化设计方法进展

Research progress of intelligent optimization design of manufacturing process parameters

  • 摘要: 工艺参数是影响零件成形质量、性能、效率和成本的关键因素。对工艺参数进行智能优化设计是当前智能制造中的基础内容。综合对近年工艺参数智能优化的研究热点、发文量等分析,将近年来工艺参数智能优化设计的方法路径分为基于神经网络的智能优化设计、基于数学模型+智能算法的优化设计和基于专家系统(知识)的智能设计三种,分析了三种方法的国内外研究进展和特点,归纳和分析了优劣势,并提出了今后工艺参数智能优化设计的发展趋势。为工艺参数智能优化的研究提供参考基础和方向指引。

     

    Abstract: Process parameters are the key factors affecting the forming quality, performance, efficiency and cost of parts. The intelligent optimization design of process parameters is the basic task of current intelligent manufacturing. According to the analysis of the research hotspots and literature on intelligent optimization design of process parameters in recent years, the method of intelligent optimization design of process parameters is divided into three categories, including intelligent optimization design based on neural network, explicit mathematical model and intelligent algorithms, and expert system (knowledge), Then, the research progress and features of the three methods are analyzed, their advantages and disadvantages are summarized and compared, and the development trend of intelligent optimization design of process parameters in the future is proposed. It can provide a basis and direction guidance for the research on intelligent optimization of process parameters.

     

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