Abstract: To improve the efficiency of process planning for Body In White(BIW), data mining technology is applied to capture useful process information. Manufacturing resource database, process principle database and process example database are built respectively. Reasoning system based on data mining is constructed. Semantic matching method is used to query parts and welding robots. The association rules are used to select the most reasonable welding type. The Genetic Algorithm(GA) is used to optimize welding path. Application results show the system can manage process information for BIW effectively.

Key words: Body In White(BIW), process planning, data mining, Genetic Algorithm(GA), association rules

摘要： 为有效提取白车身工艺规划中的信息，将数据挖掘技术应用于白车身工艺规划系统。分别建立制造资源数据库、工艺规则数据库和工艺实例库，同时建立基于数据挖掘的工艺规划推理系统，采用语义匹配方法实现对机器人的分配和对实例库的查询，使用关联规则搜寻最合理的焊接类型，利用遗传算法优化机器人焊接路径。应用结果表明，该系统能对白车身工艺信息进行有效管理。

关键词: 白车身, 工艺规划, 数据挖掘, 遗传算法, 关联规则

CLC Number: 

• N945