인공신경망을 활용한 후판 압연 조건에 따른 두께오차 예측 Prediction of Thickness Error in Plate Mill rolling using Artificial Neural Network
한국기계기술학회지
(韓國機械技術學會誌)
제26권 제2호
(2024.04)
pp.338-342
pp.338-342
한국기계기술학회
(Korean Society of Mechanical Technology)
초록
In this study, a new model using artificial neural networks is proposed to improve the thickness error between the plates, which occurs when the rolling conditions change a lot during the thick rolling. The model was developed by using Python, and the input values are the change in the finish rolling temperature between the plates, the change in target tensile strength, the change in target thickness, and the change in rolling force. The new model is 31.76% better than the existing model based on the standard deviation value of the thickness error. This result is expected to reduce quality costs when applied to online models at actual production sites in the future.
저자