Exploring the Effect of Dimensional Tolerance of the Inserts During Multi-Objective Optimization of Face Hard Milling Using Genetic Algorithm

Abstract

Surface roughness and dimensional deviation are critical quality dimensions of machined products and several machining parameters including tool insert dimensional tolerance affect them. Machining performance studies involving dimensional tolerance of the insert during machining, particularly hard face milling do not have considerable attention of the researchers. Therefore, the aim of the present work is to investigate the effect of the dimensional tolerance of the insert along with other machining parameters such as spindle speed, feed per tooth, and depth of cut on the roughness and dimensional deviation simultaneously. Experiments were conducted as per standard L18 mixed orthogonal array on a CNC vertical milling machine. Significance of machining parameters with respect to roughness and dimensional deviation was determined using Analysis of variance (ANOVA). Results revealed that among several machining parameters, feed per tooth greatly affects surface roughness and dimensional deviation. Optimum machining parameters that give minimum values of surface roughness and dimensional deviation simultaneously was obtained using Genetic Algorithm (GA).