Confrontation of linear versus nonlinear approach in Fe2B boridelayer thickness predictions

Kinetic studies of boride layers focus on trying to accurately predict their thicknesses according to some variables using different approaches. In this paper, an approach that is reliant on a multilinear regression is investigated. In doing so, with an engineering perspective, temperature  and time  are used as the sole variables in predicting a boride layer thickness u. The approach uses experimental data from a boriding process performed on iron substrates of the XC38 steel. A comparison between the proposed linear model and a nonlinear one is seen afterward to scrutinize the results. That nonlinear approach is known as the diffusion model and is based on Fick’s second law, where it uses more variables than the linear approach to estimate its predictions. Ultimately, the comparison elucidated that the use of a linear regression-based model can be an accurate engineering tool to identify boride layer thicknesses, but without interpolating the results outside the scope of the studied interval.