Numerical and experimental optimizations of nozzle distance in minimum quantity lubrication (MQL) milling process

Abstract

Minimum quantity lubrication (MQL) is the efficient and environmentally friendly technology, which is desirable to achieve sustainability during machining process. The nozzle distance has its significance in dominating the MQL spray and the related droplet transportation and penetration. In this paper, the nozzle distance has been optimized for MQL milling process through numerical and experimental methods. A two-way computational method has been employed to solve for the comprehensive flow field and particle trajectories, with the wall condition established on the spray impingement theory. The interactions of air flow rates and spindle rotational speeds on droplet penetration are investigated in details. The optimal ranges of nozzle distance setup obtained by simulation for different conditions were verified via slot milling tests, in which the nozzle distances were selected according to the key points obtained in the numerical process. The cutting force and surface roughness were recorded for the verification of adhesion ability and the related cutting performance. The comparison between numerical simulations and milling experiments has shown great consistency. This paper has achieved better understanding of the nozzle orientation setup and device development in MQL milling process, especially for external MQL. The theoretical basis and scientific instruction have been provided for the optimization of MQL operating parameters in industrial applications.