基于密炼MES生产数据的橡胶质量预测研究与实践

Research and practice of rubber quality prediction based on MES production data

为提高密炼机产出胶料的门尼黏度抽检准确度,提出了一种基于制造执行系统生产数据的门尼黏度预测方法,给出了基于制造执行系统生产历史数据与胶料质量质检数据的统计方法。对密炼机产出胶料质量影响因素进行分析并建立了质量预测神经网络,为胶料质量门尼检测的提供抽检依据,使被抽检的对象更具有代表性,提高质检部门对整个橡胶生产计划质量的可控性。

In order to improve the sampling accuracy of Mooney viscosity produced by mixer, this paper described Mooney viscosity prediction method based on the production data of manufacturing execution system, and gave a statistical method based on the data of the production execution system and the quality data of the compound. The author analyzed the influencing factors of the quality and established the quality prediction neural network to provide the sampling basis for the rubber quality Mennon test.