Multilinear Regression Predictive Analysis of Additive Manufactured High-Carbon Steel Powder

High Carbon Steel was additively manufactured through laser cladding techniques. The laser power processing parameter varied between 1.0 KW and 2.0 KW while the scanning speed, gas, and powder flow rate were kept constant. Mechanical properties of microhardness were experimentally derived. The microhardness profiling was performed at a load of 500g and a dwelling of 15s with the indenter 20m distance in-between indentation. Multilinear Regression was conducted in the prediction of its yield strength and the ultimate tensile stress with the microhardness and varying the processing parameters of the laser power. Python 3.9 of Google Collab was used in the code derivative for the predictions. The highest obtained microhardness results show the optimum value at a laser power of 1.3KW. The multilinear predictive model equation was also stated.