scholarly journals An investigation on dry sliding wear behavior of Al6061/ Titanium carbide/ Basalt hybrid metal matrix composites

2021 ◽  
Vol 13 (4) ◽  
pp. 139-150
Author(s):  
P. MUTHU
Keyword(s):  
Wear Rate ◽  
Sliding Wear ◽  
Wear Behavior ◽  
Principal Component ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Matrix Composites ◽  
Relational Analysis ◽  
Grey Relational ◽  
Sliding Distance

Dry sliding wear plays an important role in selecting material for automotive and aerospace applications. Researchers have been exploring novel aluminum matrix composites (AMC), which offer minimum wear rate for various tribological applications. The present work involves multi-objective optimization for dry sliding wear behavior of Al6061 reinforced with 6 % of Titanium carbide and 4% of basalt hybrid metal matrix composites using principal component analysis (PCA)-based grey relational analysis (GRA). In this article, the effects of input variables of wear parameters such as applied load, sliding speed and sliding distance were investigated on different output responses, namely the wear rate, friction force and specific wear rate. Taguchi’s L9 orthogonal array with three-level settings was chosen for conducting experiments. Three output responses in each experiment were normalized into a weighted grey relational grade using grey relational analysis coupled with the principal component analysis. The analysis of variance indicated that sliding distance is the most influential parameter followed by load and sliding velocity that contributes to the quality characteristics. Optimal results have been verified through additional experiments.

Taguchi Grey Relational Analysis of Dry Sliding Wear Behaviour of Annealed AA7075-TiC Metal Matrix Composites

2014 ◽  
Vol 541-542 ◽  
pp. 258-262 ◽  
Author(s):  
S. Baskaran ◽  
V. Anandakrishnan ◽  
Muthukannan Durai Selvam ◽  
S. Raghuraman ◽  
V.M. Illayaraja Muthaiyaa
Keyword(s):  
Wear Rate ◽  
Metal Matrix Composites ◽  
Grey Relational Analysis ◽  
Metal Matrix ◽  
Sliding Wear ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Matrix Composites ◽  
Relational Analysis ◽  
Grey Relational

The optimization of dry sliding wear process parameters of in-situ aluminium based metal matrix composites to obtain multiple objectives to minimize wear rate, specific wear rate, co-efficient of friction and maximize wear resistance was attempted by Taguchi Grey Relational Analysis. Moreover to identify the significance of the parameters, a statistical analysis was performed using analysis of variance. Based on the analysis, the sliding speed was identified as the major contributor with 71.41% followed by percentage of reinforcement with 8.13% and other parameters load and sliding distance are found to be insignificant. The optimum parameters identified by the Grey Relational Analysis are verified through experimental confirmation test.

Dry Sliding Wear Behavior of 2218 Al-Alloy-Al2O3(TiO2) Hybrid Composites

2017 ◽  
Vol 140 (2) ◽  
Author(s):  
Vineet Tirth
Keyword(s):  
Wear Rate ◽  
Sliding Wear ◽  
Hybrid Composites ◽  
Wear Behavior ◽  
Dry Sliding Wear ◽  
Aged Alloy ◽  
Dry Sliding ◽  
Al Alloy ◽  
Mathematical Relationship ◽  
Sliding Distance

AA2218–Al2O3(TiO2) composites are synthesized by stirring 2, 5, and 7 wt % of 1:2 mixture of Al2O3:TiO2 powders in molten AA2218 alloy. T61 heat-treated composites characterized for microstructure and hardness. Dry sliding wear tests conducted on pin-on-disk setup at available loads 4.91–13.24 N, sliding speed of 1.26 m/s up to sliding distance of 3770 m. Stir cast AA2218 alloy (unreinforced, 0 wt % composite) wears quickly by adhesion, following Archard's law. Aged alloy exhibits lesser wear rate than unaged (solutionized). Mathematical relationship between wear rate and load proposed for solutionized and peak aged alloy. Volume loss in wear increases linearly with sliding distance but drops with the increase in particle wt % at a given load, attributed to the increase in hardness due to matrix reinforcement. Minimum wear rate is recorded in 5 wt % composite due to increased particles retention, lesser porosity, and uniform particle distribution. In composites, wear phenomenon is complex, combination of adhesive and abrasive wear which includes the effect of shear rate, due to sliding action in composite, and abrasive effect (three body wear) of particles. General mathematical relationship for wear rate of T61 aged composite as a function of particle wt % load is suggested. Fe content on worn surface increases with the increase in particle content and counterface temperature increases with the increase in load. Coefficient of friction decreases with particle addition but increases in 7 wt % composite due to change in microstructure.

Multi-response optimization of tribological characteristics of aluminum MMCs using PCA

2014 ◽  
Vol 10 (2) ◽  
pp. 276-287
Author(s):  
Rajesh Siriyala ◽  
A. Gopala Krishna ◽  
P. Rama Murthy Raju ◽  
M. Duraiselvam
Keyword(s):  
Sliding Wear ◽  
Wear Behavior ◽  
Principal Component ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Sliding Velocity ◽  
Content Type ◽  
Wear Process ◽  
Response Optimization ◽  
Sliding Distance

Purpose – Since, wear is the one of the most commonly encountered industrial problems leading to frequent replacement of components there is a need to develop metal matrix composites (MMCs) for achieving better wear properties. The purpose of this paper is to fabricate aluminum MMCs to improve the dry sliding wear characteristics. An effective multi-response optimization approach called the principal component analysis (PCA) was used to identify the sets of optimal parameters in dry sliding wear process. Design/methodology/approach – The present work investigates the dry sliding wear behavior of graphite reinforced aluminum composites produced by the molten metal mixing method by means of a pin-on-disc type wear set up. Dry sliding wear tests were carried on graphite reinforced MMCs and its matrix alloy sliding against a steel counter face. Different contact stress, reinforcement percentage, sliding distance and sliding velocity were selected as the control variables and the response selected was wear volume loss (WVL) and coefficient of friction (COF) to evaluate the dry sliding performance. An L25 orthogonal array was employed for the experimental design. Optimization of dry sliding performance of the graphite reinforced MMCs was performed using PCA. Findings – Based on the PCA, the optimum level parameters for overall principal component (PC) of WVL and COF have been identified. Moreover, analysis of variance was performed to know the impact of individual factors on overall PC of WVL and COF. The results indicated that the reinforcement percentage was found to be most effective factor among the other control parameters on dry sliding wear followed by sliding distance, sliding velocity and contact stress. Finally the wear surface morphology of the composites has been investigated using scanning electron microscopy. Practical implications – Various manufacturing techniques are available for processing of MMCs. Each technique has its own advantages and disadvantages. In particular, some techniques are significantly expensive compared to others. Generally the manufacturer prefers the low cost technique. Therefore stir casting technique which was used in this paper for manufacturing of Aluminum MMCs is the best alternative for processing of MMCs in the present commercial sectors. Since the most important criteria of a dry sliding wear behavior is to provide lower WVL and COF, this study has intended to prove the application of PCA technique for solving multi objective optimization problem in wear applications like piston rings, piston rods, cylinder heads and brake rotors, etc. Originality/value – Application of multi-response optimization technique for evaluation of tribological characteristics for Aluminum MMCs made up of graphite particulates is a first-of-its-kind approach in literature. Hence PCA method can be successfully used for multi-response optimization of dry sliding wear process.

scholarly journals Process Optimization and Wear Behavior of Red Mud Reinforced Aluminum Composites

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Rajesh Shanmugavel ◽  
Thirumalai Kumaran Sundaresan ◽  
Uthayakumar Marimuthu ◽  
Pethuraj Manickaraj
Keyword(s):  
Wear Rate ◽  
Red Mud ◽  
Sliding Wear ◽  
Wear Behavior ◽  
Specific Wear Rate ◽  
Experimental Result ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Sliding Velocity ◽  
Grey Relational

This work presents the application of hybrid approach for optimizing the dry sliding wear behavior of red mud based aluminum metal matrix composites (MMCs). The essential input parameters are identified as applied load, sliding velocity, wt.% of reinforcement, and hardness of the counterpart material, whereas the output responses are specific wear rate and Coefficient of Friction (COF). The Grey Relational Analysis (GRA) is performed to optimize the multiple performance characteristics simultaneously. The Principle Component Analysis (PCA) and entropy methods are applied to evaluate the values of weights corresponding to each output response. The experimental result shows that the wt.% of reinforcements (Q=34.9%) followed by the sliding velocity (Q=34.5%) contributed more to affecting the dry sliding wear behavior. The optimized conditions are verified through the confirmation test, which exhibited an improvement in the grey relational grade of specific wear rate and COF by 0.3 and 0.034, respectively.

scholarly journals Comparative study on dry sliding wear behavior of mono (Al2219/B4C) and hybrid (Al2219/B4C/Gr) metal matrix composites using statistical technique

2020 ◽  
Vol 29 (1) ◽  
pp. 57-68
Author(s):  
R. Suresh
Keyword(s):  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Sliding Wear ◽  
Applied Load ◽  
Wear Behavior ◽  
Base Alloy ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Matrix Composites ◽  
Sliding Distance

AbstractIn the present study, aluminium metal matrix composites (AMMC’s) reinforced with boron carbide (B4C) and graphite (Gr) particles were prepared by stir casting method. Dry sliding wear behavior of developed composites was conducted on pin on disc apparatus with variation in sliding distance, applied load and sliding speed. Taguchi method was employed to optimize the data in a controlled way. Analysis of variance was employed to examine the wear behavior of base alloy (Al2219), mono (Al/B4C) and hybrid (Al/B4C/Gr) metal matrix composites. The correlations were established by linear regression models and validated using confirmation tests. The obtained results indicated that B4C content, sliding distance is highly affected by the dry sliding wear followed by sliding speed and applied load. The incorporation of B4C and Gr particles in aluminium improves the tribological characteristics. The SEM images of mono composite shows the deep grooves on worn surface. It demonstrates the signs of abrasive wear of mono composite. The hybrid composite exhibits excellent wear resistance when compared to mono composite and base alloy. The main reason of that is the Gr particles act as a solid lubricating material in the hybrid composite (Al/B4C/Gr).

OPTIMIZATION AND ANALYSIS OF DRY SLIDING WEAR BEHAVIOR OF STIR CASTED AlSi6Cu4–TiO2 COMPOSITE USING CENTRAL COMPOSITE DESIGN

2019 ◽  
Vol 26 (09) ◽  
pp. 1950052
Author(s):  
SUBBARAYAN SIVASANKARAN
Keyword(s):  
Wear Rate ◽  
Sliding Wear ◽  
Wear Behavior ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Wear Performance ◽  
Microstructural Investigation ◽  
Confirmation Test ◽  
The Matrix ◽  
Sliding Distance

The present research paperfocusses on manufacture of AlSi6Cu4–3 wt.% TiO2 metal matrix composite (MMC) through liquid metallurgy route, and the manufactured composites are tested for their dry sliding wear behavior using response surface methodology (RSM). The extensive microstructural investigation is carried out to examine the dispersion of Titania particles, its bonding ability, and embedment characteristics with the matrix. The wear rate on the developed MMC is investigated and predicted using regression model. Further, the confirmation test is conducted to validate the model. The microstructures of the composite had revealed that TiO2 particles are dispersed in the Al matrix. Further, the surface plots show that the wear rate started to vary linearly with the function of load whereas the wear rate starts to vary nonlinearly with the function of the sliding velocity and the sliding distance. In addition, the worn surfaces were investigated through the scanning electron microscopewhich addressed the wear mechanisms and revealed that TiO2 particles enhance the wear performance of aluminum alloy by a reduction in material removal at all wear conditions.

Investigation on Mechanical Properties and Analysis of Dry Sliding Wear Behavior of Al LM13/AlN Metal Matrix Composite Based on Taguchi's Technique

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
N. Radhika ◽  
R. Raghu
Keyword(s):  
Regression Analysis ◽  
Aluminum Alloy ◽  
Tensile Test ◽  
Metal Matrix ◽  
Sliding Wear ◽  
Wear Behavior ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Ratio Analysis ◽  
Sliding Distance

LM13/AlN (10 wt. %) metal matrix composites (MMC) and unreinforced aluminum alloy were produced under stir casting route. Microstructural characteristics were examined on the developed composite using optical microscope. The hardness and tensile test were carried out on both unreinforced aluminum alloy and composite using Vickers hardness tester and universal testing machine (UTM), respectively. Dry sliding wear behavior of the composite and unreinforced aluminum alloy was evaluated using pin-on-disk tribometer based on the design of experiments approach. Experimental parameters such as applied load (10, 20, and 30 N), velocity (1, 2, and 3 m/s), and sliding distance (500, 1000, and 1500 m) were varied for three levels. Signal-to-noise (S/N) ratio analysis, analysis of variance, and regression analysis were also performed. The characterization results showed that reinforcement particles were uniformly distributed in the composite. The hardness and tensile test revealed greater improvement of property in composite compared to that of unreinforced alloy. Wear plot showed that wear was increased with increase in load and decreased with increase in velocity and sliding distance. S/N ratio analysis and analysis of variance (ANOVA) indicated that load has greater significance over the wear rate followed by velocity and sliding distance. Regression analysis revealed greater adequacy with the constructed model in predicting the wear behavior of composite and unreinforced aluminum alloy. Scanning electron microscopy (SEM) analysis is evident that the transition of wear from mild to severe occurred on increase of the load in the composite.

Sign in / Sign up

Export Citation Format

Share Document