基于贝叶斯网的制造工艺质量建模方法  

Modeling method of manufacturing process quality based on Bayesian networks

作　　者：董晔弘[1] 向东[1] 龙旦风[1] 刘畅[1] 段广洪[1] 

机构地区：[1]清华大学精密仪器与机械学系制造工程研究所,北京100084

出　　处：《计算机集成制造系统》2010年第12期2564-2569,共6页Computer Integrated Manufacturing Systems

基　　金：国家科技支撑计划资助项目(2006BAF02A01;2006BAF02A02)~~

摘　　要：针对多品种小批量制造模式下,工艺质量建模面临的模型维度高、数据稀疏的问题,提出了基于贝叶斯网的工艺质量建模方法。该方法以工艺机理知识为基础构建贝叶斯网结构,在构建时采用删除法保证结构的完备性与简洁性。设计实验获得均衡分布的实验数据,并通过实验数据的学习获得条件概率表。在应用中,模型利用生产线的数据更新条件概率表,来体现生产过程中不确定性因素的影响。以印刷线路板微小孔钻孔工艺为例进行了建模方法的应用与对比,结果验证了该方法对多品种小批量制造工艺的质量建模具有适用性,并且能够获得更高的模型精度。To solve the problem of high-dimension and sparse data faced by process quality modeling in multi-type small-batch manufacturing mode,a modeling method based on Bayesian Network（BN） was proposed.The BN structure was constructed on the basis of manufacturing process mechanism knowledge and elimination method was used to ensure integrity and simplicity of the model structure.Then a set of balanced data was achieved from experiments organized by Design of Experiment（DOE）,and Conditional Probability Table（CPT） of BN-model was obtained by machine learning with this data set.The CPT was updated in application with the data obtained from production line to model the effect of uncertain factors during process.This modeling method was testified in Printed Circuit Board（PCB） micro-hole drilling process and compared to other methods.The result verified that this modeling method was applicable in multi-type small-batch manufacturing mode with higher modeling precision.

关 键 词：贝叶斯网 工艺质量建模 多品种小批量 机理知识 机器学习 印刷线路板 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]