Statistical Modeling of Strain-Hardening Exponent and Grain Size of Nb-Microalloyed Steels Using a Two-Level Factorial Design of Experiment

Abstract

A factorial design of experiment (DOE) was used to statistically model the strain-hardening exponent and grain size of Nb-microalloyed steel sheets following hot rolling. The objective of the statistical model was to develop a method to simultaneously increase the strain-hardening exponent and refine the grain size of Nb-microalloyed steels by controlling three hot rolling process parameters: roughing temperature (RT), finishing temperature (FT), and coiling temperature (CT). The factorial DOE used two levels for the above temperatures and three replicates to obtain a reliable and precise estimate of the strain-hardening exponent and grain size. Analysis of variance was used to determine the most significant factors (individual parameters and their interactions) affecting the responses and develop appropriate regression equations. The regression equations predicted that optimal formability is obtained under the following conditions: RT = 1150 °C, FT = 800 °C, and CT = 700 °C. Validation of the statistical model using microstructural characterization showed that the predicted value of the grain size was close to the experimental value.