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A rolling mill process control system calculates the setup for the mill's actuators based on models of the technological process. Neural networks are applied as components of hybrid neuro/analytical process models. They are the key to fit the general physical models to the needs of the automation of a specific mill. Present applications include the calculation of the rolling force and strip temperature (hot and cold rolling); prediction of width-spread in the finishing mill; control of strip width shape; and control of the coiling temperature in a cooling train (hot rolling). The authors outline how significant benefits are achieved in rolling mill technology by using neural networks. The work presented here is the result of a close cooperation between Siemens Corporate Technology in Munich and the Industrial Projects and Technical Services Group in Erlangen.

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