Reduced-Order Modeling in the Manufacturing Process of Wire Rod: Applications for Fast Temperature Predictions and Optimal Selection of Process Parameters

The number of operational variables that determines the cooling process of steel wire, given by the conveyor velocity and the different fan sections powers (controlled independently), lead to a dependency of the cooling on a high multidimensional parameter space whose potential combinations are impossible to be analyzed, either experimentally or by numerical simulation of a thermal–metallurgical model. To tackle this problem, an efficient strategy, based on the use of Higher Order Singular Value Decomposition (HOSVD), is presented. The approach presented provides a Reduced-Order Model (ROM) capable of predicting quite accurately the cooling curve for any combination of the process parameters. Fast online predictions of the cooling rates allow to incorporate accurate modeling results in many Engineering tools, such as model predictive control algorithms or plant simulation software. Also, the ROM in combination with an optimization tool finds the adequate operational parameters with significant reduction of energy consumption.