Optimization of dry sliding wear conditions for AlSi10Mg/SiCp composites using response surface: genetic algorithm approach

Abstract

Purpose – The purpose of this research paper is to find the optimum parameters, namely, the sliding speed, applied load and percentage of silicon carbide particles (SiCp), under which AlSi10Mg/SiCp composites experience minimum wear. Design/methodology/approach – Wear rate (WR) of AlSi10Mg, AlSi10Mg/10SiC and AlSi10Mg/20SiC was measured using pin-on-disk equipment according to ASTM G99 standards. Response surface method was used to design the experiments, model and analyze the tribological behaviour. Tests were conducted as per Box–Beheken design of experiments. The wear mechanisms were observed using scanning electron microscope. Genetic algorithm was used to find the optimum parameters for minimum WR. Findings – Wear mechanisms underwent changes with variation in applied load, sliding speed and per cent SiCp. An optimum wear condition was obtained when the process parameters, namely, the sliding speed, applied load and percentage of SiCp, were at 4 m/s, 10 N and 20 per cent, respectively. Combined GA-RSM approach was successfully used to predict the minimum WR condition of AlSi10Mg/SiCp composites with an accuracy of 94 per cent. Originality/value – The tribological behaviour of AlSi10Mg/SiCp composites has been investigated in detail. A statistical WR model is proposed. This paper provides an optimum condition to design the tribo contact between steel and AlSi10Mg/SiCp composites.