A New Method to Improve the Mechanism Model of Carburizing by Multivariate Linear Regression

Heat treatment is one of the essential technologies in industrial manufacturing, and carburization processes heat-treatment technology. With increase technological requirements production, optimization carburizing technology desired. However, most mechanism models are derived from material properties related physical principles, which involved huge amounts parameters. Some parameters (such as diffusion constant, thermal conductivity, interface transfer coefficient, etc.) difficult to measure correctly, this an extremely unfavorable issue cause results model inaccurate. In paper, a new method raised improve model. The function reduce error by combining multivariate linear regression with small amount sample data. At last, author paper will perform experiments prove correctness method.