Comparison of black-, white-, and grey-box models to predict ultimate tensile strength of high-strength hot rolled coils at the Port Talbot hot strip mill

Abstract

In the manufacture of rolled steel from a hot strip mill (HSM), the final mechanical properties, such as ultimate tensile strength, are important requirements specified by the customer. Traditional, physically based models are now being challenged by the development of black-box techniques such as artificial neural networks. In this present paper, an existing white-box physical equation for predicting ultimate tensile strength in high-strength steels is compared to an optimized black-box neural network model using the same model inputs. The predictive accuracy of both models is compared through the use of previously unseen data from a validation coil where the ultimate tensile strength throughout its length is known. In addition, a combination of the white-box equation and a black-box neural network connected in parallel, whose role is to predict the white-box approximation error, provides a grey-box solution for ultimate tensile strength prediction for high-strength coils at the Port Talbot HSM. It was found that this grey-box solution outperformed the stand-alone white-and black-box models in terms of predictive accuracy.