基于数据挖掘的质量成本分析与控制

摘要

To realize the quality control and improvement in production process based on quality cost,by means of the regression analysis method,the horizontal analysis on quality cost was carried out to determine the quality level of the enterprise,and the quality cost structure was optimized.The relevancy rules hidden in the dynamic quality cost data were regressed by combining with the production processes information included in the quality cost data.Additionally the feature data of production process was handled and the fuzzy neural network was employed to analyze and predict quality cost on the basis of the experience and the relevancy analysis results.The system method of quality control and improvement was set up based on the analysis results.%为实现基于质量成本的生产过程质量控制与改进,基于回归分析方法对质量成本进行水平分析,确定企业的质量水平,进而对其进行优化分析；结合质量成本数据中包含的质量信息,挖掘隐藏于质量成本动态数据之间的关联规则；基于企业积累的经验数据和关联分析的结果,模糊化生产制造过程的特征数据,利用模糊神经网络对质量成本进行预测性分析；最后根据分析结果,提出质量成本控制与改进的系统方法.