Experimental Analysis of Thermal Energy Deburring Process by Design of Experiment
Ashley Virginia Fritz, Lisa Sekol, Jim Koroskenyi, Bill Walch, Jeff Minear, Vernon Fernandez, Liping Liu
Abstract
Ashley Virginia Fritz, Lisa Sekol, Jim Koroskenyi, Bill Walch, Jeff Minear, Vernon Fernandez, Liping Liu
Abstract
The present work aims to conduct an experimental study through Design of Experiment (DOE) to develop a better understanding of the important variables and their impact during the Thermal Energy Method deburring process. The designed experiment was based on an L9 orthogonal array using Taguchi method and tests were conducted with an S-250 Kennametal-Extrude Hone machine. The variables tested were the chamber pressure, fuel to oxygen ratio, burr thickness and material type of the specimen. Based on variance analysis, the chamber pressure was found to have the largest variance value and was therefore concluded to have the largest impact on the deburring process. A linear regression model was developed from the experiment which can help predict the deburring outcome based on various input parameters.
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The present work aims to conduct an experimental study through Design of Experiment (DOE) to develop a better understanding of the important variables and their impact during the Thermal Energy Method deburring process. The designed experiment was based on an L9 orthogonal array using Taguchi method and tests were conducted with an S-250 Kennametal-Extrude Hone machine. The variables tested were the chamber pressure, fuel to oxygen ratio, burr thickness and material type of the specimen. Based on variance analysis, the chamber pressure was found to have the largest variance value and was therefore concluded to have the largest impact on the deburring process. A linear regression model was developed from the experiment which can help predict the deburring outcome based on various input parameters.
Key concepts: Taguchi methods, Orthogonal array, Design of experiments, Process (computing), Energy (signal processing), Work (physics), Mechanical engineering, Regression analysis