计算机集成制造系统 ›› 2016, Vol. 22 ›› Issue (第5期): 1179-1186.DOI: 10.13196/j.cims.2016.05.002

• 产品创新开发技术 • 上一篇    下一篇

基于序列模式挖掘的变型设计知识推送

徐荣振1,2,高琦1,2+,王昊1,2,徐廷1,2   

  1. 1.山东大学机械工程学院
    2.山东大学高效洁净机械制造教育部重点实验室
  • 出版日期:2016-05-31 发布日期:2016-05-31
  • 基金资助:
    国家自然科学基金资助项目(51375277);山东省自然科学基金资助项目(ZR2012GM015)

Product design knowledge recommendation based on sequential pattern mining

  • Online:2016-05-31 Published:2016-05-31
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.51375277),and the Shandong Provincial Natural Science Foundation,China(No.ZR2012GM015)

摘要: 为提高产品变型设计中知识推送的自动化程度、减少人力投入,提出一种新的知识推送方法。利用频繁序列模式挖掘技术分析知识的历史使用数据,识别设计任务所对应的频繁知识序列;在产品设计过程中,结合设计师的知识使用行为、频繁知识序列的支持度和当前任务知识序列与频繁知识序列的相似度实现知识的推送;根据所提出的知识推送方法开发了基于产品数据管理系统的知识推送构件,并在某防爆电机生产企业中得到应用。应用后的统计数据表明,该构件提高了产品设计效率。

关键词: 变型设计, 知识推送, 序列模式挖掘, 知识使用行为

Abstract: To increase the automaticity of recommendation and reduce the labor costs in product variant design,a new method of knowledge recommendation was presented.The frequent knowledge sequence technology was used to analyze historical knowledge usage data of designers with sequential pattern mining technique,and the corresponding frequent knowledge sequence of design task was recognized.In the process of product design,the knowledge recommendation was realized by combining the designers knowledge usage behavior with the support degree of frequent knowledge sequences and the similarity between current knowledge sequence and frequent knowledge sequences.According to the proposed knowledge recommending method,a component was developed based on Product Data Management (PDM),which was applied in a company which produces explosion-proof electric machine.The statistics showed that the component was helpful to increase the design efficiency.

Key words: variant design, knowledge recommendation, sequential pattern mining, knowledge usage behavior

中图分类号: