Performance profiling of minimum quantity lubrication in machining

Abstract

This study develops the analytical understanding of mechanical and environmental effects of minimum quantity lubrication (MQL) in machining and profiles the MQL performance as functions of machining and fluid application parameters. Physics-based predictive models are formulated to quantitatively describe the resulting contact stress and temperature distributions under completely dry, MQL (under boundary lubrication), and flood cooling conditions in cylindrical turning. On that basis, the air quality effects in terms of cutting fluid aerosol emission rate and droplet size distribution have been derived through the modeling of evaporation, runaway aerosol atomization, and dissipation processes. Additionally, the abrasion, adhesion, and diffusion wear mechanisms under time-evolving cutter geometry have been quantitatively evaluated for the development of a tool wear and tool life relationship with the fluid application condition. Experimental measurements of force, temperature, aerosol concentration, and tool flank wear rate in dry, MQL, and fluid cooling cases has also been pursued to calibrate and validate the predictive models. The MQL performance profile is assessed through the sensitive analysis of tool utilization, power consumption, and air quality with respect to MQL application parameters; and it serves as a basis to support the overall optimization of machining process by incorporating both mechanical and environmental considerations.