Wear performance analysis and optimization of process parameters of novel AA7178/nTiO₂ using ANN-GRA method

Abstract

The current research investigates the microstructural and wear behaviour of nano TiO2 particles with concentrations of 1%, 2%, and 3%, which were reinforced with an AA7178 metal matrix composite using a stir casting method. Artificial Neural Network (ANN) and Grey Relational Analysis (GRA) methods were used to model the wear characteristics and attain the optimal values of the input process parameters such as load, sliding speed, nanoparticles’ weight percentage, and sliding distance. An L16 orthogonal array was used for the design of the experiment. An investigation of the variance of grey relationship grade revealed that the wt.% of nano-size TiO2 particle had a substantial impact on both the friction coefficient and wear rate i.e.,70.30%. Analysis of the nano-composite's wear behaviour was carried out effectively using an ANN model. The main reason for the worn-out surface was micro-cutting and micro-ploughing, as evidenced by scanning electron microscope (SEM) micrographs obtained at load (40 N), weight percentage of nano TiO2 (3 wt.%), sliding speed (1 m/s) and sliding distance (2000 m).

Optimization on the electrical discharge machining (EDM) process parameters of aged AA7075/TiC metal matrix composites

“…The obtained adj R square value is 99.96, indicating high reliability of the experimental data and accuracy of the experiment. The confirmation test was conducted for the best combination of 8 g⋅l -1 chromium concentration, 240 µs, and 5 amps current EDM input parameters, and the obtained TWR and SR are 0.198 and 1.56, respectively (Bharat N et al, 2023). The SEM image of aged AA7075 confirmed that TiC reinforcement was uniformly dispersed in the matrix AA7075 material.…”

“…The constituents of Keller's reagent were 2.5 ml HNO 3 , 1.5 ml HCl, 1 ml HF and 95 ml Distilled Water (Kumar et al, 2023). The enhancement of micro hardness causes it to be very hard to machine, and hence the determination of the optimized parameters of machining is needed (Bharat and Bose, 2023). The EDM parameters were optimized for best aged AA7075/TiC composite.…”

“…Based on the experimental results, it is indicated that the key factors impacting the material removal rate are the pulse ON time and pulse current. As for surface roughness and the electrode wear ratio, the most influential parameters are identified as pulse ON time and electrode material (Alagarsamy and Ravichandran, 2021;Bharat and Bose, 2023). The addition of titanium carbide improves the mechanical properties of the AA2024 based composites.…”

“…The hybrid Taguchi-GRA-PCA strategy for optimizing wear behavior process factors has been painstakingly created to overcome the constraints of single-objective methodologies in issues with numerous performance characteristics (Prianza et al, 2020;Bharat and Bose, 2023). The use of Taguchi and GRA techniques considerably proves that the effect of speed as beahviour element is greater than load, which is a stronger factor than wt.% of reinforcements (Ikubanni et al, 2021) Based on the literature review, it is concluded that there has been no research conducted on the fabrication and aging of AA7075/TiC MMCs using stir casting equipment and a furnace.…”