GOALI: Micro/Meso Scale Characterization of Interface Phenomena in Environmentally Clean Machining

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The objective of this proposed Grant Opportunity for Academic Liaison with Industry (GOALI)research is to characterize interface phenomena and friction boundary conditions along the tool-chip interface at unprecedented resolution. The research objectives include a determination of the strain and strain rate distribution in the deformation zones, measurement of fluid film thickness in the tool-chip contact zone along the rake face, and estimation of temperature in the rake face region and secondary deformation zone. By assembling these measurements in the appropriate topology, a model will be developed to describe the friction boundary condition. The approach includes enhancement of a Particle Image Velocimetry technique to estimate the strain and strain rate; development of measurement techniques using luminescent molecule sensors to estimate the fluid film thickness and temperature distribution along the tool rake face; and coupling the measured strain and temperature data with machining simulations to derive the friction boundary condition. The results will enhance predictive capability of software tools for machining and enable analytical design of near-dry machining processes through a collaborative effort involving Purdue University, Third Wave Systems, Inc and General Motors R&D Center.There is widespread interest in developing complete predictive capabilities for industrial machining processes. The proposed research will provide a vital bridge between fundamental understanding of friction and deformation at machining interfaces and a quantitative model of the friction boundary condition, a major step in development of advanced machining software tools. The research will also generate the detailed micro/meso scale data needed for validation of machining models and answer long-standing questions about contact conditions and lubrication of machining interfaces. Software tools incorporating the developed friction models will enable analytical design and optimization of industrial machining processes, including near-dry machining capabilities with obvious environmental and economic benefits. Lastly, the high-resolution imaging techniques to be developed offer a cost-effective system solution that can be implemented effectively in industrial settings. Complementing the research is an education and training program that includes short-term student/researcher visits to the industrial partners; joint industry-university short-courses for practitioners; and summer undergraduate research internships with focus on students from under-represented sectors.