基于用户大数据的关联零件搜索方法  

Related Parts Search Method Based on User Big Data

作　　者：江志 叶靖雄 张今 顾复[1] 陈芨熙[1] 顾新建[1] JIANG Zhi;YE Jingxiong;ZHANG Jin;GU Fu;CHEN Jixi;GU Xinjian(School of Mechanical Engineering,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]浙江大学机械工程学院,浙江杭州310027

出　　处：《成组技术与生产现代化》2020年第2期6-11,共6页Group Technology & Production Modernization

基　　金：国家自然科学基金资助项目(51775493);宁波市科技创新2025重大专项计划资助项目(2019B10030)。

摘　　要：鉴于零件库能够有效支持专业化协同设计和制造,提高效率,降低成本,而用户在使用零件库时希望快速搜索到实现某一功能、组成某一部件的一组关联零件,以免分头搜索各种零件,提出了基于用户大数据的关联零件搜索方法。该方法主要包括:对关联关系挖掘算法FP-Growth进行优化;提出基于用户大数据的关联零件集成搜索方法;通过模具零件数据搜索完成实验验证。Parts library can effectively support specialized collaborative design and manufacturing,improve efficiency and reduce cost.When using parts library,users often want to find a group of related parts which can realize a certain function and make up a certain assembly quickly,instead of searching various parts separately.A search method for related parts based on user big data is proposed,which mainly includes:the association relationship mining algorithm FP-Growth is optimized;the related part search method based on user big data is put forward;the verification of the method is realized through mold parts data search experimental.

关 键 词：零件关联性 关联关系挖掘 FP-GROWTH 零件库 工业大数据 

分 类 号：TB472[一般工业技术—工业设计]