Effect of SiCp Reinforcement on Machinability of A356 Alloy Metal Matrix Composites

2016 ◽  
Vol 852 ◽  
pp. 142-148
Author(s):  
K. Jayakumar
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composites ◽  
Metal Matrix ◽  
End Milling ◽  
Cutting Speed ◽  
A356 Alloy ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Matrix Composites

Machining of Aluminum Metal Matrix Composites (AMMCs) is a challenge for manufacturing industries due to their heterogeneous constituents which vary from soft matrix to hard reinforcements and their interfaces. To overcome the difficulties in machining of MMCs, researchers are continuously working to find the optimum process or machining parameters. In this work, End milling studies were carried out in A356 alloy powder-SiC particles (1 μm) in 0, 5, 10, 15 volume % reinforced AMMCs synthesised by vacuum hot pressing (VHP) route.The influence of machining parameters such as cutting speed, feed and depth of cut on the prepared composites in terms of surface roughness (Ra) and material removal rate (MRR) are measured from experimental study. Experiments were conducted as per Taguchi L16 orthogonal array with 4 factors and 4 levels.From the experimental result, it was identified that surface roughness varied from 0.214 μm to 4.115 μm and MRR varied from minimum of 1.11 cm3/min to maximum of 9.65 cm3/min. It is also observed that, MRR increased with increase in machining parameters and reinforcement quantity. Similarly, surface roughness decreased for increase of cutting speed, SiC particle (SiCp) reinforcement and increased for increase in feed and depth of cut. The optimum condition were observed in higher speed, lower feed and higher depth of cut on MMC with higher SiC content (15%) for getting higher machinability.

Study on Surface Roughness in Minimum Quantity Lubrication Turning of Al-6082/SiC Metal Matrix Composites

2019 ◽  
Vol 895 ◽  
pp. 127-133 ◽  
Author(s):  
C.J. Vishwas ◽  
M. Naik Gajanan ◽  
B. Sachin ◽  
Roy Abhinaba ◽  
N.P. Puneet ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composites ◽  
Feed Rate ◽  
Metal Matrix ◽  
Minimum Quantity Lubrication ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Minimum Quantity

Aluminum-based metal matrix composites (MMCs) have been suggested due to intense interest from automobile, marine, aerospace and other structural applications owing to their balanced mechanical, physical and chemical properties. MMCs are manufactured in order to meet present demand such as low material density, high mechanical strength and higher wear resistance of the component. Generally,MMCs tend to form rougher surface during machining because of the abrasive nature of hard ceramic particles present in them. Stir casting technique was used for fabrication of this composite which ensures better homogeneity.Furthermore, an attempt has been made in this paper to examine the results on the surface roughness of Al-6082/SiC metal matrix composites (containing 0%, 5% and 10% SiC particles).Focus was spent on parametric optimization of these composites in order to achieve cost-effective machining limits. The machining parameter studies have been carried out through the design of experiments (DoE) under minimum quantity lubrication (MQL) condition and effect of machining parameters such as spindle speed, feed rate and depth of cut on surface roughness was investigated to analyze the influence of reinforcement on surface roughness. In addition, analysis of variance was studied to obtain percentage contribution of machining parameters involved. Also, the surface morphology of the machined surface was studied through a scanning electron microscope (SEM). Distribution of SiC in aluminum alloy is fairly uniform with few clusters. Results of the experiments revealed that most significant turning parameter for surface roughness was spindle speed followed by feed rate and depth of cut. Furthermore, an optimal setting parameter for getting lower surface roughness was presented in confirmation table.

Studies on Mechanical and Machinability Properties of B4Cp Reinforced 6061Aluminum MMC Produced via Melt Stirring

2014 ◽  
Vol 592-594 ◽  
pp. 744-748 ◽  
Author(s):  
Vijaykumar Hiremath ◽  
S.T. Dundur ◽  
Raj L. Bharath ◽  
G.L. Rajesh ◽  
V. Auradi
Keyword(s):  
Boron Carbide ◽  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Mechanical And Physical Properties ◽  
Aluminum Metal Matrix Composites ◽  
Poly Crystalline Diamond

Aluminum boron carbide metal matrix composites (Al-MMC) have got wide applications in aeronautical and automobile industries due to their excellent mechanical and physical properties. Due to the presence of harder reinforcement particles, machining of these composites is a difficult task. The results of experimental investigation on mechanical and machinability properties of Boron carbide particle (B4Cp) reinforced aluminum metal matrix composites are presented in this paper.The influence of reinforced ratio of 7 wt% of B4Cpon mechanical properties was examined. It was observed that addition of B4Cpreinforcement resulted in improvement in hardness and tensile strengths to the extent of 71% and 38.4% respectively. Fabricated samples were turned on medium duty lathe of 3 kW spidle power with Poly crystalline diamond tool (PCD) of 10 μm particle size at various cutting conditions. The effect of machining parameters, e.g. cutting speed, feed rate and depth of cut on cutting forces and formation of BUE was studied.

Optimization of machining parameters using WASPAS and MOORA

2019 ◽  
Vol 17 (2) ◽  
pp. 237-246 ◽  
Author(s):  
Venkateshwar Reddy Pathapalli ◽  
Veerabhadra Reddy Basam ◽  
Suresh Kumar Gudimetta ◽  
Madhava Reddy Koppula
Keyword(s):  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Metal Cutting ◽  
Optimal Parameter ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Content Type ◽  
Composite Samples

Purpose Nowadays, the applications of metal matrix composites are tremendously increasing in engineering fields. Consequently, the demand for precise machining of composites has also grown enormously. The purpose of this paper is to reduce production cost and simultaneously improve desired product quality through optimal parameter setting using WASPAS and MOORA. Design/methodology/approach Metal matrix composites were fabricated using stir casting process, with aluminum 6063 as matrix and titanium carbide as reinforcement. Fabricated composite samples were machined on medium duty lathe using cemented carbide tool. All the experiments were carried out based on Box–Behnken design. Comparison of multi objective optimization based on ratio analysis and weighted aggregated sum product assessment in optimizing four parameters, namely, “cutting speed,” “feed rate,” “depth of cut” and “reinforcement weight percent of composite samples”; evaluating their influence on material removal rate, cutting force and surface roughness were carried out. Findings The output achieved by both MOORA and WASPAS are in similar MCDM) techniques in the selection of machining parameters. Practical implications The results obtained in the present paper will be helpful for decision makers in manufacturing industries, who work in metal cutting area, to select the suitable levels for the parameters by implementing the MCDM techniques. Originality/value The novelty of this paper is making an attempt to select better MCDM technique based on the comparison of results obtained for the individual technique.

Effect of machining parameters on the surface finish of a metal matrix composite under dry cutting conditions

2015 ◽  
Vol 231 (6) ◽  
pp. 913-923 ◽  
Author(s):  
Brian Boswell ◽  
Mohammad Nazrul Islam ◽  
Ian J Davies ◽  
Alokesh Pramanik
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Tool Life ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting

The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.

On the Optimisation Into Wire Electro-Discharge Machining of Al/Al2O3P Composites

2007 ◽  
Author(s):  
N. G. Patil ◽  
P. K. Brahmankar ◽  
L. G. Navale
Keyword(s):  
Metal Matrix Composites ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Kerf Width ◽  
Feed Speed ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Machining Parameter

Non-traditional process like wire electro-discharge machining (WEDM) is found to show a promise for machining metal matrix composites (MMCs). However, the machining information for the difficult-to-machine particle-reinforced material is inadequate. This paper is focused on experimental investigation to examine the effect of electrical as well as nonelectrical machining parameters on performance in wire electro-discharge machining of metal matrix composites (Al/Al2O3p). Taguchi orthogonal array was used to study the effect of combination of reinforcement, current, pulse on-time, off-time, servo reference voltage, maximum feed speed, wire speed, flushing pressure and wire tension on kerf width and cutting speed. Reinforcement percentage, current, on-time was found to have significant effect on cutting rate and kerf width. The optimum machining parameter combinations were obtained for cutting speed and kerf width separately.

scholarly journals Optimization of end milling on Al–SiC-fly ash metal matrix composite using Topsis and fuzzy logic

2019 ◽  
Vol 1 (10) ◽  
Author(s):  
N. Tamiloli ◽  
J. Venkatesan ◽  
G. Murali ◽  
Shyam Prasad Kodali ◽  
T. Sampath Kumar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fly Ash ◽  
Metal Matrix Composite ◽  
Metal Matrix Composites ◽  
Matrix Composite ◽  
Metal Matrix ◽  
End Milling ◽  
Machining Parameters ◽  
Matrix Composites ◽  
Optimal Cutting Parameters

Abstract Metal matrix composites are extensively used in aerospace, automobile and other engineering applications as an alternative to a wide range of elements. High strength–weight ratio, durability and high corrosion resistance are benefits of metal matrix composites. The study that exhibits adopts optimal cutting parameters (speed, feed and depth of cut). The initial study is to explore end milling process of alumina (AA6082 with SiC 3% and fly ash 2%) molted metal matrix composite. The technique for order preference by similarity to ideal solution and fuzzy logic for optimizing the cutting parameter values has been utilized in the MMC. The response surface methodology is being used to develop the numerical model between output responses and machining parameters. The second-order regression models are studied through analysis of variance. The experimental investigation exhibits that feed rate is the important factor on response variables.

EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH DECISION TREE ALGORITHM

2021 ◽  
pp. 2150021
Author(s):  
P. RAVEENDRAN ◽  
S. V. ALAGARSAMY ◽  
M. RAVICHANDRAN ◽  
M. MEIGNANAMOORTHY
Keyword(s):  
Surface Roughness ◽  
Decision Tree ◽  
Taguchi Method ◽  
Cutting Speed ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Cnc Turning Process ◽  
Taguchi’S Design Of Experiments

The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed ([Formula: see text]), feed ([Formula: see text]), and depth of cut ([Formula: see text]) on surface roughness (Ra) of turning AA7075 filled with 10[Formula: see text]wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner within the matrix material. The machining of composite was carried out by using the CNC turning center and tungsten carbide insert as tool material. This experimental work was designed on L27 (33) orthogonal array using Taguchi’s design of experiments. From its signal-to-noise (S/N) ratio study, the minimum surface roughness (Ra) was obtained at the optimum level of parameters with the cutting speed at 1500[Formula: see text]rpm, feed at 0.15[Formula: see text]mm/rev and depth of cut at 0.3[Formula: see text]mm. Analysis of variance (ANOVA) and decision tree (DT) algorithm were used to identify the significant effect of parameters. The experimental result shows that depth of cut was the major significant parameter on surface roughness (Ra) when compared to cutting speed and feed.

Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization by Response Surface Methodology

2011 ◽  
Vol 189-193 ◽  
pp. 1376-1381
Author(s):  
Moola Mohan Reddy ◽  
Alexander Gorin ◽  
Khaled A. Abou El Hossein
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Glass Ceramic ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Speed ◽  
Lower Surface ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents the prediction of a statistically analyzed model for the surface roughness,R_a of end-milled Machinable glass ceramic (MGC). Response Surface Methodology (RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is found that cutting speed is the most significant factor contributing to the surface roughness value followed by the depth of cut and feed rate. The surface roughness value decreases for higher cutting speed along with lower feed and depth of cut. Additionally, the process optimization has also been done in terms of material removal rate (MRR) to the model’s response. Ideal combinations of machining parameters are then suggested for common goal to achieve lower surface roughness value and higher MRR.

Surface Roughness Optimization in End Milling Using the Multi Objective Genetic Algorithm Approach

2012 ◽  
Vol 576 ◽  
pp. 103-106 ◽  
Author(s):  
Muataz H.F. Al Hazza ◽  
Erry Yulian Triblas Adesta ◽  
Muhammad Riza ◽  
M.Y. Suprianto
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
End Milling ◽  
Cutting Speed ◽  
Root Mean Square Roughness ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Machining Optimization

In finishing end milling, not only good accuracy but also good roughness levels must be achieved. Therefore, determining the optimum cutting levels to achieve the minimum surface roughness is important for it is economical and mechanical issues. This paper presents the optimization of machining parameters in end milling processes by integrating the genetic algorithm (GA) with the statistical approach. Two objectives have been considered, minimum arithmetic mean roughness (Ra) and minimum Root-mean-square roughness (Rq). The mathematical models for the surface roughness parameters have been developed, in terms of cutting speed, feed rate, and axial depth of cut by using Response Methodology Method (RSM). Due to complexity of this machining optimization problem, a multi objective genetic algorithm (MOGA) has been applied to resolve the problem, and the results have been analyzed.

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