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

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...

Asymmetric Risk Injection Molding Product Size Prediction ModelBased on LightGBM#br#

 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.