Multi-Objective Optimization of Machining Performance Characteristics using Grey Relational Grade Analysis

Abstract

High performance materials are now preferred by the manufacturing sector over conventional graded materials. Only composites and their hybrid varieties are capable of this. The researchers found it challenging to machine these hybrid composite pieces with varied mechanical characteristics. In the current work, an effort has been made to machine a hybrid composite made of aluminum-grade AA2024, SiC, and B4C that was mixed at various compositions. Using carbide tools and the L18 orthogonal design, the machining was carried out on a CNC turret lathe. Grey analysis is used to optimize the experimental responses to material removal rate, surface roughness, and tool wear. According to the findings, the feed has the greatest impact on the multi-response.