数据挖掘在生产过程质量管理中的应用

Application of data mining in the production process quality management

针对离散型制造业生产过程的产品质量管理只注重事后处理,缺少对质量数据做进一步分析的情况,采用事先预警的管理理念,利用决策树C4.5算法,对大量生产加工与检验数据进行数据挖掘,建立一种生产过程质量分析模型。该模型结合生产过程产品质量关键影响因素,为质量管理提供数据支持。采用该算法对某公司制造数据的挖掘结果进行分析发现,所建模型提高了产品质量,降低了生产的不合格率,为企业持续改进质量提供决策支持。

The product quality management of discrete manufacturing industry production process pays attention to the after process management, in which mode quality data for further analysis are lacked, so the idea of prior warning management was ap- plied. It using C4.5 decision tree algorithm to mine mass production processing and testing data and set up a production process quality analysis model. The model, combining with the essential production process quality influencing factors, provides support to the data quality management. Through mining and analysis of this algorithm in one company＇ s manufacturing data,it is found that this model enhanced the product quality, reduced the reject ratio of production and provided decision support for the enterprise＇ s continuous quality improvement.