scholarly journals Wear Resistivity of Al7075/6wt.%Sic Composite by using Grey-Fuzzy Optimization Technique

2021 ◽  
Author(s):  
ABHIJIT BHOWMIK ◽  
Ajay Biswas
Keyword(s):  
Optimization Technique ◽  
Oxidation Stability ◽  
Fuzzy Optimization ◽  
Stir Casting ◽  
Dry Sliding Wear ◽  
Aluminium Matrix Composite ◽  
Sliding Speed ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Sliding Distance

Abstract Application of SiC particulate reinforcement impact greatly for making aluminium matrix composite because of its superb heat conductivity, oxidation stability and highly resistance to mechanical erosion. Present work based on dry sliding wear analysis of Al7075/6wt.%SiC composite fabricated by liquid state stir casting method. To acquire a productive wear rate, three major process parameters viz. load, sliding speed and covering sliding distance were compared four different levels. ANOVA analysis showed that the probability rate of load is less than 0.05 that revealed their significant factor. From the study, the highest GRG and GFG values are found 0.914 and 0.854 respectively for the optimal operating parameters of 10 Newton load, 2 metre/second sliding speed and 500 metre sliding distance. Finally, it is revealed that the grey-fuzzy technique effectively authenticate the decision making of wear performance characteristics rather than a plain grey relational grade.

scholarly journals Taguchi Grey Relational Analysis for Multi-Response Optimization of Wear in Co-Continuous Composite

Materials ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 1743 ◽  
Author(s):  
Prasanth Achuthamenon Sylajakumari ◽  
Ramesh Ramakrishnasamy ◽  
Gopalakrishnan Palaniappan
Keyword(s):  
Grey Relational Analysis ◽  
Applied Load ◽  
Dry Sliding Wear ◽  
Optimal Parameters ◽  
Sliding Speed ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Predominant Factor ◽  
Grey Relational ◽  
Sliding Distance

Co-continuous composites have potential in friction and braking applications due to their unique tribological characteristics. The present study involves Taguchi grey relational analysis-based optimization of wear parameters such as applied load, sliding speed and sliding distance, and their effect on dry sliding wear performance of AA6063/SiC co-continuous composite manufactured by gravity infiltration. A Taguchi L9 orthogonal array was designed and nine experimental runs were performed based on the designed experiments. The coefficient of wear and specific wear rate were recorded for each experiment. Based on the average responses computed from Taguchi grey relational analysis, an applied load of 60 N, sliding speed of 1 m/s and sliding distance of 1000 m were estimated to be the optimal parameters. An Analysis of Variance (ANOVA) was conducted to identify the predominant factor and established all the three factors as being significant. The sliding distance was found to have the highest significant influence of 61.05% on the wear of the C4 composite. Confirmation experiments conducted using the optimal parameters indicated an improvement of 35.25% in grey relational grade. Analysis of the worn surfaces of the confirmation experiment revealed adhesive and abrasive wear as the governing mechanisms.

Experimental Investigation, Modeling and Optimization of Tribological Parameters of AA6061/SiC/B4C Hybrid Nano Composites

2019 ◽  
Vol 801 ◽  
pp. 83-88
Author(s):  
Shubhajit Das ◽  
Santosh K. Tamang ◽  
M. Chandrasekaran ◽  
Sutanu Samanta
Keyword(s):  
Experimental Investigation ◽  
Stir Casting ◽  
Hybrid Nanocomposites ◽  
Nano Composites ◽  
Multi Objective Optimization ◽  
Sliding Speed ◽  
Casting Technique ◽  
Desirability Analysis ◽  
Sliding Distance ◽  
Tribological Parameters

The present work investigates the tribological properties of AA6061/1.5 wt.% SiC/1.5 wt.% B4C hybrid nanocomposites prepared using stir casting technique. The effect of sliding distance, sliding speed and load were investigated on wear rate (WR) and coefficient of friction (COF). Response surface methodology was used to predict and model the responses. Analysis of variance showed that sliding speed and load were the significant factor affecting WR and COF respectively. Desirability analysis was performed for both single and multi-objective optimization. The minimum WR and COF were found to be 0.0015 mm3/m and 0.2430 at sliding distance of 1939.39 m, sliding speed of 1.99 m/s and load of 10 N.

scholarly journals Dry Sliding Wear Behaviour of Titanium (Grade 5) Alloy by Using Response Surface Methodology

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
S. R. Chauhan ◽  
Kali Dass
Keyword(s):  
Sliding Wear ◽  
Normal Load ◽  
Wear Behaviour ◽  
Dry Sliding Wear ◽  
Dry Sliding ◽  
Sliding Speed ◽  
Grade 5 ◽  
Titanium Grade ◽  
Sliding Distance ◽  
Sliding Wear Behaviour

The dry sliding wear behaviour of titanium (Grade 5) alloy has been investigated in order to highlight the mechanisms responsible for the poor wear resistance under different applied normal load, sliding speed, and sliding distance conditions. Design of experimental technique, that is, response surface methodology (RSM), has been used to accomplish the objective of the experimental study. The experimental plan for three factors at three levels using face-centre central composite design (CCD) has been employed. The results indicated that the specific wear rate increases with an increase in the applied normal load and sliding speed. However, it decreases with an increase in the sliding distance and a decrease in the sliding speed. The worn surfaces of the titanium alloy specimens were analyzed with the help of scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), and X-ray diffraction (XRD) techniques. The predicted result also shows the close agreement with the experimental results and hence the developed models could be used for prediction of wear behaviour satisfactorily.

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.

Study on Mechanical and Wear Behaviour of AA7075/TaC/Si3N4/Ti Hybrid Metal Matrix Composites

2022 ◽  
Vol 10 (1) ◽  
pp. 1-16
Author(s):  
J. Pradeep Kumar ◽  
D. S. Robinson Smart
Keyword(s):  
Elevated Temperatures ◽  
Optimization Technique ◽  
Matrix Material ◽  
Frictional Coefficient ◽  
Stir Casting ◽  
Tantalum Carbide ◽  
Wear Behaviour ◽  
Sliding Speed ◽  
Control Factors ◽  
Mechanical And Tribological Characteristics

This research article focuses on the development of AA7075 alloy reinforced with different wt% of Tantalum Carbide (TaC), Silicon Nitride (Si3N4) and Titanium (Ti) particulates using stir casting. Mechanical characteristics like tensile, compression and microhardness of the developed composites were analysed. High temperature tribological properties of the hybrid MMCs were studied for various input control factors like sliding speed, load and temperature. Design analysis has been executed by Taguchi orthogonal array and ANOVA (Analysis of Variance). The incorporated reinforcements exhibited improved wear resistance at ambient temperature along with elevated temperatures. Monolithic dissemination of reinforcement’s in the prepared composites magnifies the mechanical and tribological characteristics for composites compared to matrix material. From the optimization technique, it was witnessed that Wear Rate and Frictional Coefficient are afflicted by temperature go after load & sliding speed. The optimal amalgamation of control parameters of distinct tribo-responses has been detected.

scholarly journals Multi response parameters optimization of ZA-27 nanocomposites

2021 ◽  
Vol 46 (1) ◽  
pp. 11-18
Author(s):  
Sandra Gajević ◽  
Slavica Miladinović ◽  
Onur Güler ◽  
Hamdullah Çuvalcı ◽  
Nenad Miloradović ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Base Alloy ◽  
Optimal Combination ◽  
Parameters Optimization ◽  
Dry Sliding Wear ◽  
Al2o3 Nanoparticles ◽  
Sliding Speed ◽  
Relational Analysis ◽  
Reinforcement Content ◽  
Grey Relational

In this study, Taguchi-Grey relational analysis was used to investigate and optimize wear parameters such as sliding speed, reinforcement of Gr and reinforcement of Al2O3, and their effect on dry sliding wear performance of ZA-27 nanocomposites. Nanocomposites were synthesized via hot pressing process with pre-processing mechanical milling. Sixteen experimental tests were performed based on design of experiments which was created with the help of Taguchi L16 orthogonal array. Grey relational analysis (GRA) was applied for determination of optimal combination of parameters in order to improve tribological characteristics. Optimal combination of factors, obtained with Taguchi Grey relational analysis was sliding speed of 100 rpm, reinforcement content of 1 vol.% Gr and reinforcement content of 4 vol.% Al2O3. Validation of results was done by using Artificial Neural Network (ANN). Developed model had overall regression coefficient 0.99836, and output values showed good correlation with experimental results. Based on this research, it can be observed that nanocomposites with reinforcement of Gr and Al2O3 can be potentially employed in many industries as a good substitute for the base alloy. In addition, as a result of the analysis of the worn surfaces, it was determined that with the increase of the Al2O3 ratio, the hard Al2O3 nanoparticles turned the dominant wear mechanism into abrasive. Also, it was determined that the Gr nanoparticles appeared on the abrasive wear lines.

scholarly journals Multi objective optimization of wear behaviour of Aluminum MMCs using Grey-Taguchi method

2020 ◽  
Vol 7 ◽  
pp. 16
Author(s):  
Poovalingam Muthu
Keyword(s):  
Wear Rate ◽  
Coefficient Of Friction ◽  
Weight Ratio ◽  
Stir Casting ◽  
Sem Analysis ◽  
Wear Behaviour ◽  
Dry Sliding Wear ◽  
Specific Strength ◽  
Pin On Disc ◽  
Grey Relational

In recent years, metal matrix composite (MMCs) have been receiving worldwide attention on account of their superior strength-to-weight ratio and stiffness. Among the several classes of composite materials, Aluminium matrix ceramic reinforcement composites have attracted increasing attention due to their unique properties such as better specific strength, specific stiffness, wear resistance, excellent corrosion resistance, high elastic modulus and light weight. The aim of the present investigation is to optimize the dry sliding wear parameters of Aluminum LM25 matrix reinforced with silicon carbide (SiC) (5 wt.%) and Copper (Cu) (3 wt.%) using Taguchi based grey relational analysis. In this work, the composite is prepared using stir casting method. The specimens are prepared according to ASTM standard. Using pin-on-disc apparatus, wear tests are conducted as per Taguchi's L9 orthogonal array and optimum wear parameters are identified with an objective to minimise the wear rate and coefficient of friction based on the grey relational grade. The effect of parameters on the wear rate and coefficient of friction was determined using Analysis of variance (ANOVA). Finally, the experimental results were verified using confirmation tests and the SEM analysis was carried out to study the wear mechanism.

Fabrication and Sliding Wear Behaviour of Metal Matrix Composites

2014 ◽  
Vol 612 ◽  
pp. 157-162 ◽  
Author(s):  
J. Udaya Prakash ◽  
T.V. Moorthy ◽  
S. Ananth
Keyword(s):  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Matrix Material ◽  
Wear Test ◽  
Stir Casting ◽  
Wear Behaviour ◽  
Matrix Composites ◽  
Sliding Speed ◽  
Weight Percentage ◽  
Sliding Distance

Wear behaviour of aluminium matrix composites are characterized by pin on disc wear test using various parameters such as sliding distance, sliding speed and load. MMC consists of aluminium alloy (A356) as the matrix material and particulate alumina of 5% and 10% by weight as the reinforcement was fabricated using stir casting. Wear resistance of composites are improved by the presence of reinforcements. Experiments were conducted based on the plan of experiments generated through Taguchi Technique. L9 orthogonal array was selected for analysis of data. The objective of this investigation is to study the influence of sliding speed, sliding distance, load and weight percentage reinforcement on wear rate of fabricated metal matrix composites.

scholarly journals Mathematical Modeling and Analysis of Wear Behavior of AlTiN Coating on Titanium Alloy (Ti-6Al-4V)

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
P. Sivaprakasam ◽  
A. Kirubel ◽  
G. Elias ◽  
P. Maheandera Prabu ◽  
P. Balasubramani
Keyword(s):  
Titanium Alloy ◽  
Physical Vapor Deposition ◽  
Wear Behavior ◽  
Biomedical Application ◽  
Optimization Technique ◽  
Titanium Implants ◽  
Empirical Modeling ◽  
Quadratic Term ◽  
Sliding Speed ◽  
Sliding Distance

In this study, the wear behavior of a physical vapor deposition (PVD) AlTiN coated on the titanium alloy was investigated. Response surface methodology (RSM) was used to analyze input factors, such as load (A), sliding speed (B), and sliding distance (C), while wear mass loss (WML) and coefficient of driction (COF) were considered as the response parameters. The statistical analysis shows that main factors, that is, interaction of AC and pure quadratic terms B2 and C2, have maximum influences on WML. However, COF was highly affected by load, sliding speed, and interaction of AB and quadratic term A2. The present work attempts to carry out empirical modeling to predict output response on WML and COF. Desirability-based optimization technique was employed to obtain minimum WML and COF. Microscopy images of the wear tracks reveal visible grooves and scratches that confirm abrasive wear to be the primary wear mechanism accompanied by adhesive wear. The investigation concluded that AlTiN has better wear resistance properties and can be used to coat titanium implants for biomedical application. The result shows that the minimum WML and COF have been found at applied load 15 N, sliding speed at 0.5 m/s, and sliding distance 500 m.

Dry sliding wear behaviour of AA6082-T6/SiC/B4C hybrid metal matrix composites using response surface methodology

2016 ◽  
Vol 232 (11) ◽  
pp. 952-964 ◽  
Author(s):  
Gurpreet Singh ◽  
Sanjeev Goyal
Keyword(s):  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Hybrid Composites ◽  
Wear Behaviour ◽  
Dry Sliding Wear ◽  
Matrix Composites ◽  
Sliding Speed ◽  
Weight Percentage ◽  
Sliding Distance ◽  
Sliding Wear Behaviour

In the present work, dry sliding wear behaviour of hybrid aluminum metal matrix composites is carried out. A mixture of silicon carbide and boron carbide is used in equal fraction as reinforcement with base material AA6082-T6 to prepare AA6082-T6/SiC/B4C hybrid metal matrix composites using stir casting technique. The weight percentage of silicon carbide and boron carbide mixture taken to prepare hybrid composites is 5, 10, 15 and 20. The wear behaviour of Al-SiC-B4C composites is investigated using a pin-on-disc apparatus at room temperature, and optimization of process parameters is done using response surface methodology. The weight percentage of reinforcement, sliding speed, load and sliding distance are selected as process parameters with five levels of each. Analysis of variance shows that wear increases with increase of load or sliding distance and decreases with an increase in reinforcement or sliding speed. The experimental results revealed that the wear of Al-SiC-B4C hybrid composites has been influenced most by the sliding distance and least by weight percentage of reinforcement. The interaction between load–sliding speed is the only significant two-factor interaction in the present model which increases wear rate in fabricated hybrid composites. Further, the experimental results obtained are verified by conducting confirmation tests, and the errors found are within 3 to 7%.

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