Multi Tribo-Performance Optimization of AA7075–Al2O3 Composites by Grey Based Response Surface Methodology

Abstract

Any engineering surface, even a highly polished one, is prone to abrasion which incurs most of the wear related expenses. Two-body abrasion causes severe material and dimensional losses and is affected by a variety of extrinsic and intrinsic variables. Furthermore, tribo-responses like wear resistance (WR), coefficient of friction (COF) and abraded surface roughness (ASR) are three distinct characteristics in nature, and therefore, multi-objective optimization is necessary for design and selection of engineering systems. In the present article, tribo-performances of stir-cast alumina reinforced Al–Zn–Mg–Cu matrix composites in terms of WR, COF and ASR were evaluated under two-body abrasion with varying abrasive size, load and sliding distance. Irrespective of abrasion conditions, the developed composites exhibited superior WR ability with substantially lower COF but much greater ASR than alloy. All three tribo-responses were first converted into a single response of grey relational grade (GRG); afterwards, response surface based central composite design was adopted to improve tribo-performances of the composites through optimal factor setting by which WR would become the greatest, and COF and ASR would be the lowest. Abrasive size followed by reinforcement quantity was evaluated as the preeminent one among all the factors on GRG. The role of different control factors on observed tribo-characteristics was explained via identification of various micro-mechanisms of abrasion.