摘要
企业生产的非标产品具有种类多、批量小、相似度高等特点,设计人员在非标产品的三维设计及工艺设计过程中,存在重复工作量大、编制效率低、工艺一致性差等问题。针对以上问题,为了提高非标产品工艺设计效率,提出了一种基于STEP AP242的MBD模型及工艺重用方法。该方法构建了由MBD模型和工艺文件组成的产品模版数据库;设计了基于STEP AP242的MBD模型重用算法,通过该算法修改模版的stp文件生成新产品的stp文件;构造了基于工艺知识图谱的工艺重用算法,通过工艺知识图谱判定对模版中的工艺文件进行修改生成新产品的工艺文件;最后,应用上述方法对某企业非标PCD刀具的设计过程进行验证,验证了该方法的可行性。后续将通过深度学习等技术,实现具有不同几何结构的MBD模型及工艺的重用,增强该方法的通用性。
In the process of 3D design and process design of non-standard products,the designers encounter problems such as heavy repetitive workload,low efficiency of preparation and poor process consistency.To solve these problems and improve the efficiency of non-standard product design,a MBD model and a process reuse method based on STEP AP242 are proposed.In this method,a product template database composed of a MBD model and process files is constructed.The MBD model reuse algorithm based on STEP AP242 is designed,and the stp file of the new product is generated by modifying the template stp file.The process reuse algorithm based on the process knowledge graph is constructed,and the process files in the template are modified to generate the process files of new products by judging the process knowledge graph.Finally,the design process of a non-standard PCD tool in an enterprise is verified by the above method,and the feasibility of the method is confirmed.In the future,the reuse of MBD models and processes with different geometric structures will be realized through deep learning and other technologies to enhance the versatility of the method.
作者
郭亮
沈文平
李心灵
王四宝
杨德存
李本杰
GUO Liang;SHEN Wenping;LI Xinling;WANG Sibao;YANG Decun;LI Benjie(School of Mechanical Engineering,Southwest Petroleum University,Chengdu 610500,China;Sichuan Science and Technology Rresource Shared Service Platform for Oil and Gas Equipment Technology,Chengdu 610500,China;College of Mechanical and Vehicle Engineering,Chongqing University,Chongqing 400044,China;Dongfang Turbine Co.,Ltd.,Deyang Sichuan 618000,China)
出处
《机械设计与研究》
CSCD
北大核心
2024年第5期57-64,共8页
Machine Design And Research
基金
四川省重点研发项目(2022YFQ0016)
四川省自然科学基金资助项目(2022NSFSC)。
