The Taguchi method is a powerful tool for the design of high-quality systems which provides a simple, efficient, and systematic approach to optimize designs for performance, quality, and cost. On the other end, the most important nonconventional machining process is the plasma arc cutting (PAC) due to its good dimensional accuracy cut and high quality of work piece. In this entry, the Taguchi method is applied for optimization of PAC parameters. The appropriate orthogonal array has been selected per a number of factors and their levels to perform minimal experimentation. The material for the work piece has been taken as stainless steel 316 L for different 16 experimental tests. The best combination for cutting parameters has been found using signal to noise ratio and also has been validated the same with the experimental work. The optimum values for material removal rate (MRR) and surface roughness (SR) have been determined with the help of main effect plot and analysis of variance table. The response table for optimum setting parameter has been derived from Minitab software. Using this technique, one can increase the productivity in minimal time by reducing the numbers of experiments in the plasma-cutting process. A confirmation test has been performed to confirm the value estimated through the software. Regression analysis is a mathematical measure of the average relationship between two or more variables. The regression equation for MRR and SR has been developed with the help of Minitab software. Using regression analysis, the mathematical models of the first order for MRR and SR present significant effects.