Optimizing the Automated Plasma Cutting Process by Design of Experiment
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Building complex two–dimensional metallic parts is difficult due to the physical properties of the metal, such as its solid nature, thickness, etc. Automated Plasma Cutting is an effective process for building complex parts in a short period of time. It cuts the metallic parts up to one inch thick with any given complexity, and with no usage of physical man power. Since, there are several possible machine settings (i.e., current, pressure, cutting speed, torch height, etc.), parts cut by using the plasma cutting process often lack good quality. Sometimes, these parts are not completely cut because the plasma gas does not penetrate all the way through the sheet metal due to insufficient pressure or excessive torch height, pressure, cutting speed or current. This research was conducted to discover the optimum machine settings by implementing a Design of Experiments approach (DOE) to find those relevant factors that affect the part’s surface quality characteristics (i.e., surface roughness, flatness, accumulation underneath the work piece, bevel angles, and dimensional accuracy of the metal work piece). These important characteristics of part quality were considered as response variables. In this research, a response surface methodology approach and Desirability functions were used to optimize the automated plasma cutting settings. Final results identified an optimal machine configuration that facilitates the fabrication of parts with close-to-perfect quality for all 18 quality measurement responses.