Optimising the automated plasma cutting process by design of experiments

Abstract

Automated plasma cutting is an effective process for building complex, two-dimensional metallic parts in a short period of time. Because the plasma cutting machine has several factors or input variables to control (e.g., current, cutting speed, torch height, etc.) and the process requires compliance with a variety of part quality characteristics or response variables (e.g., flatness, clean cut, bevel angle, etc.), it is difficult to find a machine setting that improves the overall quality of the manufactured parts. This research was conducted to discover the relevant factors that affect the part's surface quality characteristics and the optimum machine settings by implementing a design of experiments and following a response surface methodology approach. Desirability functions were used to optimise the automated plasma cutting process. Final results identified an optimal machine configuration that facilitates the fabrication of parts with close-to-perfect quality for all the 18 quality responses considered.