This award develops knowledge required to design cutting tools and select flow parameters for minimum quantity lubrication (MQL) machining. MQL is known for its advantages of significant reduction in water waste, energy use, and overall costs as compared to traditional wet processes. This research project will investigate the science behind MQL machining and rapidly implement the results into production-level operations through the collaboration with Ford Motor Company. Since the project has broad applicability to automotive, aerospace, electronics and defense industries, it directly and positively impacts American economic welfare and national security. Additionally, the project includes plans for hands-on training and research experience on advanced machining processes for undergraduate students via course integration, summer internship, and Research Experience for Undergraduates (REU) programs. By leveraging an on-going Research Experience for Teachers (RET) program at Texas A&M, this project also includes outreach activities to high schools on design of modern cutting tools to promote STEM field. The close collaboration with the industrial partner also provides a unique environment to align these plans with the needs in the manufacturing industry.
This research incorporates experimental and numerical approaches that address the fundamental science of minimum quantity lubrication. Drilling is the target process as it is common in manufacturing, whereas drilling is complex and cannot be observed visually. The project has three main objectives: Objective 1 characterizes the flow out of internal channels based on geometrical, system, and machining parameters. An MQL flow testbed will be used to emulate the mist flow in machining and allow visual access to the cutting zone with a high-speed camera. Objective 2 addresses interactions between flow structure and drill-workpiece motion and thus will predict the fluid coverage on the tool edges and faces. The flow test results will be compared with computational fluid dynamics (CFD) using both single- and dual-phase flow analyses. Objective 3 will determine the effects of mist flow on drilling performance, including torque, thrust force, built-up edge, and wear, on production systems at the Ford AME MQL laboratory. The knowledge generated will enable MQL-specific tool design and selection, adaptive MQL systems, and process development. The broader impacts include improved MQL implementation in the manufacturing industry and collaborative activities between the industry and academia for the workforce development.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
