基于轻量级梯度提升机的非对称风险注塑成形产品尺寸预测模型  

Asymmetric Risk Injection Molding Product Size Prediction Model Based on LightGBM

作　　者：刘永兴 唐小琦[1] 钟靖龙 钟震宇 周向东[1] LIU Yongxing;TANG Xiaoqi;ZHONG Jinglong;ZHONG Zhenyu;ZHOU Xiangdong(School of Mechanical Science and Engineering,Huazhong University of Science and Technology,Wuhan,430074;Institute of Intelligent Manufacturing,GDAS,Guangzhou,510070)

机构地区：[1]华中科技大学机械科学与工程学院,武汉430074 [2]广东省科学院智能制造研究所,广州510070

出　　处：《中国机械工程》2022年第8期965-969,共5页China Mechanical Engineering

基　　金：国家重点研发计划(SQ2019YFB1707300);广东省科学院建设国内一流研究机构行动专项资金(2019GDASYL-0502007)。

摘　　要：受温度、气压等环境不稳定因素的影响,注塑成形加工过程中工艺参数发生变化,从而导致产品精度下降,产品降级或报废。针对类似环境不稳定因素影响问题,利用加工过程中的数据进行注塑成形尺寸预测,有助于不合格产品的及时发现,减少不合格品的产生。基于轻量级梯度提升机(LightGBM)框架设计了基于加工过程数据及参数的注塑成形产品尺寸预测模型,通过特征提取、异常数据处理、数据集划分、模型训练、模型验证等步骤,建立了具有非对称风险特征的产品尺寸预测模型。针对产品尺寸超规的非对称风险问题,在模型训练过程中引入了基于尺寸范围的加权修正方法,以提高预测模型对超规尺寸的预测精度。最后利用富士康注塑成形尺寸预测数据集进行了验证,结果表明,该模型对超规尺寸具有更高的预测精度,尺寸预测结果平均误差为0.015 mm,考虑非对称风险的加权平均误差为5×10^(-6) mm。Due to the influences of environmental instability factors such as temperature and air pressure during the injection molding processes,the processing parameters were changed during the molding processes,resulting in a decrease in product accuracy,product degradation or scrap.Aiming at the problems of similar environmental instability factors,using the data in the molding processes to predict the sizes of injection molding was helpful for the timely detection of unqualified products and reducing the occurrence of unqualified products.Based on the LightGBM framework,an injection molding product size prediction model was designed based on processing data and parameters.Through feature extraction,abnormal data processing,data set division,model training,model verification,and other steps,a product size prediction model with asymmetric risk characteristics was established.Because of the asymmetric risk of product size exceeding the specification,a weighted correction method was introduced to improve the prediction accuracy of the prediction model for the abnormal size based on the size range in the model training processes.Finally,the Foxconn injection molding size prediction data set was used to verify the prediction model,the results show that the model has higher prediction accuracy for out-of-specification dimensions.The average error of the verification set size prediction results is as 0.015 mm,and the weighted average error considering the asymmetry risk is as 5×10^(-6) mm.

关 键 词：注塑成形 非对称风险 机器学习 尺寸预测 轻量级梯度提升机 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]