Modeling of Tool-Wear Based on Tool Temperatures and Decomposed Cutting Forces in Turning with Grooved Tools

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This grant is aimed at modeling tool-wear in grooved tools based on its relationships with cutting forces, stresses, temperatures and tool-chip contact in 2-D machining and turning. Experimental work involves measurement of tool temperature distributions, tool-chip contact length and tool-wear parameters. The results from the experimental work will provide important modeling parameters and boundary conditions for a predictive 2-D model (numerical) for forces, stresses and temperatures. The first phase of the project is focused on establishing comprehensive relationships among tool-wear and tool temperatures, stresses and tool geometry parameters. The effects of a finite cutting edge radius on tool-wear and tool temperatures will also be investigated. In the second phase, turning experiments with grooved tools will be performed to collect data on 3-D tool-wear, temperatures, forces and tool-chip contact. A modeling approach based on decomposition of cutting forces at different wear regions of a grooved tool will be extended to correlate tool-wear with forces and temperatures using the effective 2-D chip-flow direction. The results from this approach will be used in developing an integrated hybrid 3-D predictive model, involving analytical-numerical-empirical approaches. The anticipated major benefit from this project is the development of a new, fundamental modeling approach for tool-wear. Machining operations constitute a large segment of the manufacturing sector in the US. There has been a growing need for developing robust models and methodologies to enable reliable and accurate predictions of machining performance measures in process planning to ensure the highest quality of machined products with maximized productivity. The tool-wear rate has significant correlation with other important machining performance measures such as chip-form/chip breakability, surface roughness/surface integrity and part accuracy. Traditional models for tool-life/tool-wear have been heavily empirical due to the complexity of the problem; hence, the current project advocates the use of a hybrid modeling methodology. The expected results from this project will provide fundamental new knowledge for tool-wear predictions in machining with grooved tools. The results will also serve process planners in selecting the most appropriate cutting tools and cutting conditions for maximized machining performance, especially with respect to tool-wear/tool-life.