Optimizing the Tribological Behavior of Hybrid Copper Surface Composites Using Statistical and Machine Learning Techniques

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Titus Thankachan ◽  
K. Soorya Prakash ◽  
Mujiburrahman Kamarthin

Copper-based surface composite dispersed with varying fractions of hybrid reinforcement was fabricated through friction stir processing (FSP). Hybrid reinforcement particles were prepared from aluminum nitride (AIN) and boron nitride (BN) particles of equal weight proportion. Based on design of experiments, wear characteristics of the developed copper surface composites were estimated using pin-on-disk tribometer. Experimental parameters include volumetric fraction of hybrid reinforcement particles (5, 10, and 15 vol %), load (10, 20, 30 N), sliding velocity (1, 1.5, and 2 m/s), and sliding distance (500, 1000, and 1500 m). Microstructural characterization demonstrated uniform dispersion of hybrid reinforcement particles onto the copper surface along with good bonding. Hardness of the developed surface composites increased with respect to increase in hybrid particle dispersion when compared with copper substrate while a reduction in density values was revealed. Analysis on wear rate values proved that wear rate decreased with increase in hybrid particle dispersion and increased with increase in load, sliding velocity, and distance. Analysis of variance (ANOVA) specified load as the most significant factor over wear rate values followed by volume fractions of particle dispersion, sliding velocity, and distance. Regression model constructed was found efficient in predicting wear rate values. Analysis of worn out surfaces through scanning electron microscopy (SEM) revealed the transition of severe to mild wear with respect to increase in hybrid reinforcement particle dispersion. A feed forward back propagation algorithm-based artificial neural network (ANN) model with topology 4-7-1 was developed to predict wear rate of copper surface composites based on its control factors.

Coatings ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 830 ◽  
Author(s):  
Namdev Ashok Patil ◽  
Srinivasa Rao Pedapati ◽  
Othman Bin Mamat ◽  
Abdul Munir Hidayat Syah Lubis

Friction stir processing (FSP) has evolved as an important technique in fabrication of metal matrix composites. The surface properties enhancement is obtainable by insertion of desired discontinuous particular reinforcements into base alloy using FSP. Despite having high specific strength, more applications of Al alloys are restricted due to their poor surface properties under various loading conditions. In this study, the main focus is on enhancing the microhardness and wear properties of Al 7075 base alloy by means of uniform dispersion of silicon carbide and graphite (SiC/Gr) nano particles into the base alloy using the FSP technique. The tool rotational speed (w: 500, 1000, 1500 rpm), tool traverse speed (v: 20, 30, 40 mm/min), reinforcement particles hybrid ratio (HR: 60:40, 75:25, 90:10) and volume percentage (vol%: 4%, 8%, 12%) are used as independent parameters. The effect of these parameters on microstructure, micro hardness and wear properties of surface composites are studied in detail. For desired wear rate and microhardness as responses, the aforementioned independent parameters are optimized using response surface methodology (RSM). The significance of factors and their interactions for maximizing hardness and minimizing wear rate and coefficient of friction (COF) were determined. Analysis of variance (ANOVA) for responses has been carried out, and the models were found to be significant in all three responses. The minimum wear rate of 0.01194 mg/m was obtained for parameters w 1500 rpm, v 40 mm/min, HR 60:40, vol% 4 (Run 10). The maximum micro hardness of 300 HV obtained for parameters w 1000 rpm, v 30 mm/min, HR 75:25, vol% 12 (Run 14). The presence and uniform distribution of SiC and Gr into the base alloy was confirmed through field-emission scanning electron microscopy (FESEM) imaging, energy-dispersive X-ray spectroscopy (EDX) and mapping tests. The wear rate and COF decreased significantly due to graphitized mechanically mixed layer developed at the sliding contacts. The microhardness of resultant composites observed to be dependent on effect of the independent parameters on extent of inherent precipitates dissolution and grain size strengthening in the resultant materials.


Author(s):  
G Girish ◽  
V Anandakrishnan

In this work, the dry sliding wear behaviour of recursively friction stir processed AA7075 was investigated using a pin-on-disc wear testing apparatus. The microstructure of the processed specimen was probed using optical microscopy, transmission electron microscopy and atomic force microscopy. Experiments were conducted using Taguchi experimental design by varying three different parameters like load, sliding velocity and sliding distance, and the analysis of variance was performed to identify the influence of the parameters over the wear rate. From the main effect plot, the combination of 9.81 N of load, 2 m/s of sliding velocity and a sliding distance of 2000 m was identified as the optimum levels that minimize the wear rate. The regression model was developed to calculate the wear rate, and the validation test was performed with the optimum parameter combination and compared with the experimental results. Wear tracks were examined using field-emission scanning electron microscopy to identify the type of wear mechanism.


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