scholarly journals Multi-Performance Characteristics of AA5052 + 10% SiC Surface Composite by Friction Stir Processing

2020 ◽  
Vol 4 (2) ◽  
pp. 36 ◽  
Author(s):  
Rungwasun Kraiklang ◽  
Jariyaporn Onwong ◽  
Charuayporn Santhaweesuk
Keyword(s):  
Tensile Strength ◽  
Wear Rate ◽  
Tool Wear ◽  
Rotational Speed ◽  
Performance Characteristics ◽  
Aluminum Surface ◽  
Tool Wear Rate ◽  
Friction Stir ◽  
Surface Composite ◽  
Fabrication Parameters

In this paper, optimization of the fabrication parameters of an aluminum surface composite with respect to tensile strength and tool wear rate is reported. The surface layer was reinforced with SiC particles to improve the tribological properties of AA-5052. The Taguchi design with orthogonal array L8 was used for the experimental design, which included three processing parameters: the number of passes, rotational speed, and traversal speed. The experiment used optimal fabrication parameter searching to produce a multi-response prediction of both the tensile strength and tool wear rate. The experimental result was determined by grey relational analysis for multi-performance characteristics. Afterward, the prediction result of the optimal fabrication parameters was confirmed by repeated experiments to confirm the selection of optimal process parameters. The results revealed that the optimal fabrication parameters for multi-performance characteristics are two passes, rotational speed of 1000 revolutions per minute (RPM), and traversal speed of 30 mm/min (condition N2R1T2). These showed high tensile strength (229.90 MPa), low tool wear rate (0.0851), and a uniform distribution of SiC particles in the matrix. In addition, grey relational analysis showed that the parameter priority was 51.68% for rotational speed (the most significant process parameter), 36.18% for transversal speed, and 7.05% for the number of passes. Therefore, the grey-based orthogonal array Taguchi method can optimize multi-performance characteristics through the setting of process parameters for friction stir processing of an aluminum surface composite.

Prediction and optimization of mechanical properties of PA6/NBR/graphene nanocomposites fabricated by friction stir processing

2021 ◽  
pp. 009524432110200
Author(s):  
Ali Ghorbankhan ◽  
Mohammad Reza Nakhaei ◽  
Ghasem Naderi
Keyword(s):  
Tensile Strength ◽  
Impact Strength ◽  
Rotational Speed ◽  
Traverse Speed ◽  
Differential Scanning Calorimetric ◽  
Butadiene Rubber ◽  
Friction Stir ◽  
Graphene Nanocomposite ◽  
Graphene Nanoparticles ◽  
Input Variables

The friction stir process (FSP) method used to prepare polyamide 6 (PA6)/nitrile-butadiene rubber (NBR) nanocomposites with 1 wt% Graphene nanoparticles. Response surface methodology (RSM) and Box-Behnken design were used to study the effects of four input variables including tool rotational speed (ω), shoulder temperature (T), traverse speed (S), and the number of passes (N) on tensile strength and impact strength of PA6/NBR/Graphene nanocomposite. In order to investigate the dispersion state of Graphene and the morphology of the PA6/NBR blend in the presence of Graphene, wide x-ray patterns (WAX), scanning electron microscopy (SEM) were performed. Furthermore and differential scanning calorimetric (DSC) was used to investigate the thermal properties of PA6/NBR containing 1 wt% Graphene nanoparticles. The results confirmed that at the optimum range of input variables, PA6/NBR/Graphene nanocomposite provided good thermal stability as well as the highest tensile strength, and impact strength. This is caused by the large surface area to volume ratio of the dispersed layered Graphene in PA6/NBR blends. Under optimal conditions of the rotational speed of 1200 rpm, traverse speed of 20 mm/min, shoulder temperature of 125°C, and number pass of 3, the maximum tensile strength and impact strength are 70.4 MPa and 70.3 J/m, respectively.

CHARACTERIZATION OF ZrB2-SiC COMPOSITES WITH AN ANALYTICAL STUDY ON MATERIAL REMOVAL RATE AND TOOL WEAR RATE DURING ELECTRICAL DISCHARGE MACHINING

2016 ◽  
Vol 40 (3) ◽  
pp. 331-349 ◽  
Author(s):  
S. Sivasankar ◽  
R. Jeyapaul
Keyword(s):  
Wear Rate ◽  
Tool Wear ◽  
Relative Density ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Tool Materials

This research work concentrates on Electrical Discharge Machining (EDM) performance evaluation of ZrB2- SiC ceramic matrix composites with different tool materials at various machining parameters. Monolithic ZrB2 possesses lower relative density (98.72%) than composites. ZrB2 with 20 Vol.% of SiC possesses 99.74% of the relative density with improved hardness values. Bend strength and Young’s modulus increase with SiC addition until it reaches 20 Vol% and then decreasing. EDM performance on tool materials of tungsten, niobium, tantalum, graphite and titanium at various levels of pulse on time and pulse off time are analyzed. Graphite produces the best Material removal rate (MRR) for all the workpieces. Tool wear rate decreases with melting point and thermal conductivity of the tool material.

Experimental studies on graphite powder-mixed electro-discharge machining of Inconel 718 super alloys: Comparison with conventional electro-discharge machining

2018 ◽  
Vol 233 (2) ◽  
pp. 384-402 ◽  
Author(s):  
Santosh Kumar Sahu ◽  
Saurav Datta
Keyword(s):  
Thermal Conductivity ◽  
Residual Stress ◽  
Wear Rate ◽  
Tool Wear ◽  
Inconel 718 ◽  
Material Removal ◽  
Graphite Powder ◽  
Tool Wear Rate ◽  
Machined Surface ◽  
Electro Discharge Machining

Inconel 718 is a nickel-based super alloy widely applied in aerospace, automotive, and defense industries. Low thermal conductivity, extreme high temperature strength, strong work-hardening tendency make the alloy difficult-to-cut. In contrast to traditional machining, nonconventional route like electro-discharge machining is relatively more advantageous to machine this alloy. However, low thermal conductivity of Inconel 718 restricts electro-discharge machining from performing well. In order to improve the electro-discharge machining performance of Inconel 718, powder-mixed electro-discharge machining was reported in this paper. It was carried out by adding graphite powder to the dielectric media in consideration with varied peak discharge current. The morphology and topographical features of the machined surface including surface roughness, crack density, white layer thickness, metallurgical aspects (phase transformation, crystallite size, microstrain, and dislocation density), material migration, residual stress, microindentation hardness, etc. were studied and compared with that of the conventional electro-discharge machining. Additionally, effects of peak discharge current were discussed on influencing different performance measures of powder-mixed electro-discharge machining. Material removal efficiency and tool wear rate were also examined. Use of graphite powder-mixed electro-discharge machining was found to be better in performance for improved material removal rate, superior surface finish, reduced tool wear rate, and reduced intensity as well as severity of surface cracking. Lesser extent of carbon migration onto the machined surface as observed in powder-mixed electro-discharge machining in turn reduced the formation of hard carbide layers. As compared to the conventional electro-discharge machining, graphite powder-mixed electro-discharge machining exhibited relatively less microhardness and residual stress at the machined surface.

Comparison of response surface methodology with artificial neural network for prediction of the tensile properties of friction stir-processed surface composites

2021 ◽  
pp. 095440892110368
Author(s):  
Ravi Butola ◽  
Ranganath M. Singari ◽  
Qasim Murtaza ◽  
Lakshay Tyagi
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Tensile Strength ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Rotational Speed ◽  
Total Elongation ◽  
Tool Rotational Speed ◽  
Friction Stir ◽  
Artificial Neural

In the present work, nanoboron carbide is integrated in the aluminum matrix using friction stir processing: by varying process parameters, that is, tool pin profile, tool rotational speed and tool traverse speed, based on Taguchi L16 design of experiment. A self-assembled monolayer is successfully developed on the substrate to homogeneously and uniformly distribute the reinforcement particles. Response surface methodology and artificial neural network models are developed using ultimate tensile strength and total elongation as responses. Percentage absolute error between the experimental and predicted values of ultimate tensile strength and total elongation for the response surface methodology model is 3.537 and 2.865, respectively, and for artificial neural network is 2.788 and 2.578, respectively. For both the developed models experimental and forecasted values are in close approximation. The artificial neural network model showed slightly better predictive capacity compared to the response surface methodology model. From the scanning electron microscopy micrograph, it is evident that throughout the matrix B4C reinforcement particles are well distributed also; with increasing tool rotational speed grain size decreases up to 1200 r/min; on further increasing the tool rotational speed particles starts clustering.

Effect of Al2O3 nanoparticles on microstructure and mechanical properties of friction stir-welded dissimilar aluminum alloys AA7075-T6 and AA6061-T6

2021 ◽  
pp. 095440892110655
Author(s):  
Sumit Jain ◽  
R.S. Mishra
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Rotational Speed ◽  
Traverse Speed ◽  
Particle Dispersion ◽  
Al2o3 Nanoparticles ◽  
Tool Rotational Speed ◽  
Micro Hardness ◽  
Friction Stir ◽  
Dissimilar Aluminum Alloys

In this research, a defect-free dissimilar weld joint of AA7075-T6 and AA6061-T6 reinforced with Al2O3 nanoparticles was fabricated via friction stir welding (FSW). The influence of tool rotational speed (700, 900 and 1100 rpm), traverse speed (40, 50 and 60 mm/min) with varying volume fractions of Al2O3 nanoparticles (4%, 7% and 10%) on microstructural evolution and mechanical properties were investigated. The augmentation of various mechanical properties is based on the homogeneity of particle dispersion and grains refinement in the SZ of the FSWed joint. The findings revealed that the remarkable reduction in grain size in the SZ was observed owing to the incorporation of Al2O3 nanoparticles produces the pinning effect, which prevents the growth of grain boundaries by dynamic recrystallization (DRX). The increasing volume fraction of Al2O3 nanoparticles enhanced the mechanical properties such as tensile strength, % elongation and micro-hardness. Agglomeration of particles was observed in the SZ of the FSWed joints produced at lower tool rotational speed of 700 rpm and higher traverse speed of 60 mm/min due to unusual material flow. Homogenous particle dispersion and enhanced material mixing ensue at higher rotational speed of 1100 rpm and lower traverse speed of 40 mm/min exhibit higher tensile strength and micro-hardness.

Fabrication and experimental investigation of magnetic field assisted powder mixed electrical discharge machining on machining of aluminum 6061 alloy

2019 ◽  
Vol 233 (12) ◽  
pp. 2283-2291 ◽  
Author(s):  
Arun Kumar Rouniyar ◽  
Pragya Shandilya
Keyword(s):  
Magnetic Field ◽  
Wear Rate ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Pulse On Time

Magnetic field assisted powder mixed electrical discharge machining is a hybrid machining process with suitable modification in electrical discharge machining combining the use of magnetic field and fine powder in the dielectric fluid. Aluminum 6061 alloy has found highly significance for the advanced industries like automotive, aerospace, electrical, marine, food processing and chemical due to good corrosion resistance, high strength-to-weight ratio, ease of weldability. In this present work, magnetic field assisted powder mixed electrical discharge machining setup was fabricated and experiments were performed using one factor at a time approach for aluminum 6061 alloy. The individual effect of machining parameters namely, peak current, pulse on time, pulse off time, powder concentration and magnetic field on material removal rate and tool wear rate was investigated. The effect of peak current was found to be dominant on material removal rate and tool wear rate followed by pulse on time, powder concentration and magnetic field. Increase in material removal rate and tool wear rate was observed with increase in peak current, pulse on time and a decrease in pulse off time, whereas, for material removal rate increases and tool wear rate decreases up to the certain value and follow the reverse trend with an increase in powder concentration. Material removal rate was increased and tool wear rate was decreased with increase in magnetic field.

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