Abstract：Thickness accuracy is one of the important indicators of cold-rolled strip quality. For improving strip quality and stability of production, it is of great significance to quickly diagnose the abnormal thickness and locate the root cause of thickness anomaly. The influencing factors of thickness was determined by the rolling mechanism model, and the residual model of thickness increment was constructed by the multivariable linear regression method. Then the kernel density estimation of the residuals was utilized for detecting thickness anomaly. The causal effect of influencing factors was calculated based on causal inference to identify the root cause of thickness anomaly. The results in-practice show that the proposed method can accurately diagnose thickness anomaly and identify the root cause of anomaly, and the method is more effective than conventional method for cold rolling conditions with high correlation between the variables.
周军, 杨荃, 王晓晨. 基于因果推断的冷轧带钢厚度异常根因分析[J]. 中国冶金, 2023, 33(5): 94-101.
ZHOU Jun, YANG Quan, WANG Xiao-chen. Root cause analysis of thickness anomaly for cold rolled strip based on cause inference[J]. China Metallurgy, 2023, 33(5): 94-101.
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2023, Vol. 33 
