基于注塑过程数据的制品尺寸合格性判定

针对注塑生产过程中人工质量检测存在的效率低、成本高等问题，提出了一种基于注塑加工过程数据来对产品尺寸是否合格进行预测判定的方法。先对清洗后的数据集采用5折交叉验证筛选出LR(logistic regression)模型、SVM(support vector machine)模型等5个分类模型，再以ROC(receiver operating characteristic)曲线和AUC(area under curve)值作为性能评估指标，综合比较和分析了5个分类模型在不同特征选取方法下的分类性能。结果表明：基于树模型特征选取与LR分类模型组合对本文的数据集表现出了优良的分类性能，准确率可达96.42%,具有一定的工程应用价值。

Research on dimensional qualification determination of injection molding products based on process data

Aiming at the problems of low efficiency and high cost of manual quality inspection in injection molding production process, a method for predicting and judging whether the product size is qualified based on injection molding process data is proposed. Firstly, for the cleaned data set, five classification models such as LR model and SVM model are selected by 5-fold cross validation, and then ROC curve and AUC value are used as performance evaluation indexes, The classification performance of five classification models under different feature selection methods is comprehensively compared and analyzed. The results show that the combination of tree model feature selection and LR algorithm shows excellent classification performance for the data set in this paper, and the accuracy can reach 96.42%, which has a certain engineering application value.