数据挖掘在质量管理中的应用

传统的质量管理方法,始终是致力于质量的控制和诊断,主要关注事后处理.本文介绍了应用数据挖掘技术针对生产过程中的质量问题建立预测模型,进行产品质量预测的方法.该方法以生产加工的历史数据为基础,利用关联分析挖掘出生产过程中影响质量的关键因素及其内在联系,进行质量控制和诊断,并使用分类分析建立预测模型,模拟计划排产后的产品质量情况,从而对企业计划排产提供决策支持.

The Application of Data Mining in Quality Management

Traditional methods of quality management took up with the control and diagnosis of quality, which focused on the treatment after the event. This paper proposes a quality forecast method that uses the data mining technologies to build the forecast model of quality management. This method is based on the historical manufacturing records, which uses association rule to find out the inner associations among the quality related factors in order to realize the control and diagnosis of quality. The method applies classfication to predict the quality results according to the simulate planning in order to supply the decision support for the enterprise planning.