A neural network-based shape control system for cold rolling operations

In cold steel rolling, strip shape is crucial to product quality. For modern rolling mills, there are a number of different ways to control the strip shape, including adjusting the side depression, bending the work rolls and axial shifting the middle roll. However, these controls are not independent and hence, must be used with great care. This paper introduces a new method for strip shape control. It takes two steps: the first step is to use an Artificial Neural Network (ANN) to recognize the strip shape pattern. The second step is to apply one or a combination of several controls accordingly. This process may take several iterative steps. The new method is validated on an 8000 KN HC mill. The results demonstrated the new method could reduce the strip shape error step by step.