Gray relational analysis of performance characteristics in MQL milling of 7075 Al alloy

Abstract

This paper presents the optimization of the face milling process of 7075 aluminum alloy by using the gray relational analysis for both cooling techniques of conventional cooling and minimum quantity lubrication (MQL), considering the performance characteristics such as surface roughness and material removal rate. Experiments were performed under different cutting conditions, such as spindle speed, feed rate, cooling technique, and cutting tool material. The cutting fluid in MQL machining was supplied to the interface of work piece and cutting tool as pulverize. An orthogonal array was used for the experimental design. Optimum machining parameters were determined by the gray relational grade obtained from the gray relational analysis.