AN INVESTIGATION OF MACHINABILITY & SURFACE INTEGRITY ON ALUMINIUM …€¦ · MMCs. To improve the fracture toughness of the conventional composites, the new class of materials known

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http://www.iaeme.com/IJMET/index.asp 369 [email protected]

International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 10, October 2017, pp. 369–378, Article ID: IJMET_08_10_041

Available online at http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10

ISSN Print: 0976-6340 and ISSN Online: 0976-6359

© IAEME Publication Scopus Indexed

AN INVESTIGATION OF MACHINABILITY &

SURFACE INTEGRITY ON ALUMINIUM AND

TITANIUM CARBIDE COMPOSITE MATERIAL

USING ABRASIVE WATER JET MACHINING

S. A. Puviyarasu

Department of Mechanical Engineering, Dr. N.G.P Institute of technology,

Affiliated to Anna University, Coimbatore, Tamilnadu, India

ABSTRACT

The experimental investigation was conducted to determine the influence of

machinability and surface integrity on aluminium and titanium carbide composite

material using abrasive water jet machining (AWJM). The matrix is aluminium and

the reinforcement is titanium carbide, varies from 0-8 %. The effects of AWJ

machining parameters were Speed, standoff distance and Reinforcement was

considered as model variables. For this purpose, design of experiments was carried

out in order to collect the material removal rate and surface roughness. Then the

Analyses of variance (ANOVA) were carried out to check the validity of regression

model and to determine the significant parameter influencing the surface roughness

and Material removal rate. The experimental result shows that these hybrid process

parameters can fit the requirements of modern manufacturing applications.

Keywords: Abrasive water jet machining (AWJM), ANOVA, Material Removal Rate

(MRR), Surface Roughness(RA).

Cite this Article: S. A. Puviyarasu, An Investigation of Machinability & Surface

Integrity on Aluminium and Titanium Carbide Composite material using Abrasive

water jet Machining, International Journal of Mechanical Engineering and Technology

8(10), 2017, pp. 369–378.

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=10

1. INTRODUCTION

In many developed countries and in several developing countries there exists continued

interest in Metal Matrix Composites (MMCs). Researchers tried numerous combinations of

matrices and reinforcements since 1950s. This led to developments for aerospace, but

resultant commercial applications were limited. To enhance further the properties of MMCs

more than two materials were added in the matrix to give birth to hybrid metal matrix

composites. However, conventional monolithic materials have limitations in achieving good

combination of strength, stiffness, toughness and density [1]. To overcome these

An Investigation of Machinability & Surface Integrity on Aluminium and Titanium Carbide

Composite material using Abrasive water jet Machining


shortcomings and to meet the ever increasing demand of modern day technology, composites

are the most promising materials of recent interest. Metal matrix composites (MMCs) possess

significantly improved properties including high specific strength; specific modulus, damping

capacity and good wear resistance compared to the unreinforced alloys [2]. But the poor

ductility and reduced fracture toughness limits the applications of conventional composite

MMCs. To improve the fracture toughness of the conventional composites, the new class of

materials known as Metal Matrix Composites (MMCs) are developed by reinforcing particles

in the micro metal scale. SiC and Al2O3 are the common reinforcing materials used in

aluminium matrix composites. Limited research been conducted on Titanium carbide

reinforced and aluminium matrix composites which have a combination of two or more

reinforcements. Here we are using aluminium and titanium carbide as a composite material; it

varies from 0-8%.

Abrasive water jet machining (AWJM) is suitable to be used for hard and brittle materials

with excellent machining performances; it is most frequently used in the surface finishing,

cleaning, deburring for the materials such as steels, glass and ceramics [3]. The capability of

the AWJM process used for specific materials with high efficiency, accuracy and low cost

was conducted to meet the requirement of modern industrial applications. [4]. The three input

process parameters namely standoff distance, speed and reinforcement percentage were

chosen as variable to study their effects on response parameter. The ranges of input parameter

were selected on the basis of literature survey, machine capability and preliminary

experiments conducted by using one variable at a time approach. M. Hashish et al. [5]

experimentally investigated the wear behaviour of abrasive-water jet nozzle materials. Two

general patterns of wear namely the divergent and convergent were observed. Divergent

pattern occurs when soft mixing tube materials or relatively hard abrasives were used, while

convergent pattern occurs otherwise. . For this purpose, design of experiments was carried out

in order to collect the material removal rate and surface roughness. Shah and Patel [6]

reported that the MRR increases with increase of air pressure, grain size and with increase in

nozzle diameter. Initially MRR increases and then it is almost constant for small range. After

that MRR decreased as SOD increases. Khan, Haque [7] experimented the relationship

between work feed rate and taper of cut during AWJM using different abrasive materials. For

all types of abrasives the taper of cut shows an increasing trend with increase in work feed

rate. With increase in work feed rate the machining zone is exposed to the jet for a shorter

time.

Then the Analyses of Variance (ANOVA) were carried out to determine the significant

parameter influencing the surface roughness and material removal rate. The proposed

experimental procedure and results leads to improvements in response parameters. It is fit to

the requirement of modern manufacturing applications.

2. EXPERIMENTAL SETUP:

2.1 Materials:

The work piece adopted in this study was Aluminium and titanium carbide composite

material, with dimensions of 100mm* 100mm*10mm. Aluminium is the third most

abundant element after oxygen and silicon and the most abundant metal in the crust, though it

is less common in the mantle below and the Titanium carbide is the only chemical compound

of titanium and carbon it has attracted for the sake of its excellent properties such as hard and

wear- resistance, high melting point and chemically inert [8]. The specimens were milled and

grained firstly to ensure their parallelism before each experiment. The essential properties of

the material is given below

S. A. Puviyarasu


Table 1 Essential Properties of Aluminium alloy

Property Value

Melting Point 660.2

Boiling Point 2480

Thermal Conductivity (0-100 C) 0.57

Density (g/cm³) 2.6898

Poissons Ratio 0.34

2.2 Equipment and procedure

Initially, the aluminium alloy and the reinforcement material are fabricated by using stir

casting process. This involves Matrix material aluminium alloy as taken in rod form was

melted at 800oC in the electric resistance furnace. Preheating of reinforcement particles

(titanium carbide ) was done for one hour for 790 oC to remove moisture content and gasses

from the surface of the particulates. The speed of the stirrer was gradually raised upto 500rpm

and the preheated reinforcement particles were added into the melt. The speed regulator

maintained at a constant speed of the stirrer, after the addition of hard ceramic (reinforcement)

particles stirring was continued for 5-7minutes for proper mixing of reinforcement in the

matrix.

After fabrication of the material, the experiments were conducted on the Abrasive Water

Jet Machining (AWJM). Considerable research and development effort has been made in

recent years to develop new techniques to enhance the cutting performance of this technology

such as the depth of cut and surface finish. Some newly developed techniques include cutting

with forward angling the jet in the cutting plane, multiple pass cutting and controlled nozzle

oscillation. Among these new techniques, controlled nozzle or cutting head oscillation has

been found to be one of the most effective ways in improving the cutting performance without

additional costs to the process.

The three input process parameters namely standoff distance, speed and reinforcement

percentage were chosen as variable to study their effects on response parameter in Fig. 1.

Figure 1 Abrasive Water jet machine

The ranges of input parameter were selected on the basis of literature survey, machine

capability and preliminary experiments conducted by using one variable at a time approach.

As work piece material, the titanium carbide with aluminium composites with 100mm ×

100mm × 10mm size was used. Moreover the material would be splashed and impinged by

high speed of abrasive grains. The specimens were cut into 10mm to diameter from the




thickness of 10mm. Therefore, the surplus material was removed and surface finishing would

be enhanced.

2.3 Conditions

The essential machining parameters such as abrasive grain size, pressure, nozzle diameter,

working medium as shown below

Figure 2 Schematic diagram of operation of AWJM Process

Table 2 Experimental Conditions

Work condition Description

Nozzle diameter 1.1mm

Pressure 3600psi

Abrasive size 80 mesh

Abrasive material Silicon sand

Working time/piece 10-25 sec

3. RESULTS AND DISCUSSION

The experiments were designed and conducted by employing response surface methodology

(RSM). The selection of appropriate model and development of response surface models have

been carried out by using statistical software, “Mini tab (16)”. The selected models were

obtained for the response characteristics, viz., surface roughness, material removal rate. The

surface roughness and material removal rate is the most important parameters for assessing a

production process. In this investigation, we have found that rougher surface of the material

after machining due to the fact that as the particle moves down they loses its kinetic energy

and their ability. By analysing the experimental data of the selected material, it found that

optimum selection of the input parameters i.e. Speed, Standoff distance and Reinforcement

(%) are crucial in controlling the material removal rate and surface roughness. The effect of

each parameter was studied while keeping other parameters as constant.

Then How the Input parameters influence the output is carried out by using analysis of

variance (ANOVA) was performed. It analyse the statistical results. For analysis of data,

checking the lack of fit of model is required. For this purpose Analysis of Variance (ANOVA)

is performed.

S. A. Puviyarasu


3.1 PROCESS PARAMETERS AND THEIR LEVELS

The process parameters and their levels is shown in Table 3

Table 3 Process parameter and their levels

PROCESS

PARAMETERS -2 -1 0 1 2

STAND OFF

DISTANCE 2 4 6 8 10

SPEED 102 127 153 178 204

%

REINFORCEMENT0 2 4 6 8

3.2 EXPERIMENTAL RESULTS

According to central composite design with three control factors at half fraction, a total of 25

experiments need to be performed as shown in table 4. Each time experiment was performed,

a particular set of control factors were chosen and work piece was cut.

Table 4 Experimental results of material removal rate and surface roughness

S.NO STAND OFF

DISTANCE SPEED REINFORCEMENT TIME MRR RA

1 -2 -2 -2 24 1.58 2.264

2 -1 -1 -2 20 1.939 2.236

3 0 0 -2 17 2.402 3.655

4 1 1 -2 16 2.557 4.618

5 2 2 -2 14 2.991 4.622

6 -2 -2 -1 23 1.672 1.915

7 -1 -1 -1 21 1.91 2.418

8 0 0 -1 19 2.111 2.797

9 1 1 -1 16 2.557 1.905

10 2 2 -1 14 2.945 2.317

11 -2 -2 0 24 1.661 2.427

12 -1 -1 0 20 2.107 2.873

13 0 0 0 18 2.005 2.307

14 1 1 0 16 2.522 2.628

15 2 2 0 14 2.922 2.443

16 -2 -2 1 24 1.632 1.975

17 -1 -1 1 21 1.872 1.866

18 0 0 1 17 2.373 2.504

19 1 1 1 16 2.359 2.477

20 2 2 1 15 2.727 3.101

21 -2 -2 2 24 1.619 2.283

22 -1 -1 2 20 2.013 2.432

23 0 0 2 19 2.183 3.021

24 1 1 2 15 2.781 3.073

25 2 2 2 14 2.985 3.537




3.3 ANALYSIS OF VARIANCE (ANOVA)

3.3.1 Material Removal Rate

The ANOVA is carried out to analyse the effect of process parameters table 5 shows the input

parameters source and how they contribute or Influence the Material Removal rate. Table 6

shows the response level data. In Table 5 the standoff distance plays a more important role in

contributing the material removal rate of 4.9593 and followed by reinforcement*

reinforcement 0.03249. Thus the SOD has the maximum contribution of 98.75% and followed

by R*R of 0.64% contribution. The total sum of square and mean of square significantly

contribute same as shown in table 5

Table 5 Analysis of variance for MRR

Source DOF SS MS SS

Contribution% MS Contribution%

SOD 1 4.95936 0.000881 98.7530 1.091291

Speed 1 0.00037 0.003472 0.007376 4.300755

Reinforcement 1 0.00000 0.010714 0 13.27139

SOD*SOD 1 0.01145 0.005501 0.227997 6.814071

Speed*Speed 1 0.00575 0.005746 0.114496 7.117552

R*R 1 0.03249 0.032487 0.646955 40.24154

SOD*Reinforcement 1 0.00157 0.010936 0.031262 13.54638

Speed*Reinforcement 1 0.01099 0.010993 0.218837 13.61699

Total 8 5.02198 0.08073 99.99 % 99.99%

DF- Degrees of freedom, SS- Sum of squares, MS-Mean square (Variance)

Table 6 Response Table for MRR

Source SOD R*R SOD*SOD

1. 98.75% 0.64% 0.22%

Rank 1 2 3

Figure 3 3D Surface plot MRR for SOD versus speed

S. A. Puviyarasu


Figure 4 3D Surface plot MRR for SOD versus Reinforcement %

Figure 5 3D Surface plot MRR for Speed versus Reinforcement %

From the Figure 3 it is observed that the speed is directly proportional to the MRR

whereas the MRR decreases initially and then increases gradually with the increase in SOD

by considering the speed. From Figure 4. It is observed that the MRR is directly proportional

to Reinforcement % whereas the MRR increases initially and decreases gradually with

increase in SOD by considering the Reinforcement %. Figure 5 shows that the MRR increases

initially and decreases gradually with decrease in Reinforcement % and by considering

increase in speed.

3.3.2 SURFACE ROUGHNESS

The table.7 shows the input parameters source and how they contribute or Influence the

Surface roughness. Table.8 shows the Response level data. In table.7 standoff distance plays a

more important role in contributing the surface roughness of 3.4785 and followed by

reinforcement* reinforcement 3.1507. Thus the SOD has the maximum contribution of

45.20% and followed by R*R of 40.94% contribution. The total sum of square and mean of

square significantly contribute same as shown in table.8

Table 7 Analysis of variance for Ra

Source DOF SS MS SS Contribution% MS Contribution%

SOD 1 3.4785 0.01696 45.208 0.52111

Speed 1 0.0507 0.01370 0.658 0.42095

Reinforcement 1 0.6110 0.02231 7.94 0.68550

SOD*SOD 1 0.0945 0.00634 1.228 0.19480

Speed*Speed 1 0.0071 0.00710 0.09227 0.21815




R*R 1 3.1507 3.15075 40.9479 96.81121

SOD*Reinforcement 1 0.2837 0.01918 3.68709 0.58933

Speed*Reinforcement 1 0.0182 0.01819 0.23653 0.55891

Total 8 7.6944 3.25453 99.99% 99.99%

DF- Degrees of freedom, SS- Sum of squares, MS-Mean square (Variance)

Table 8 Response Table for Ra

Source SOD R*R R

1. 45.208 40.9479 7.94

Rank 1 2 3

Figure 6 3D Surface plot Roughness for SOD versus Speed

Figure 7 3 D Surface plot roughness for SOD versus Reinforcement%

Figure 8 3 D Surface plot Roughness for Speed versus Reinforcement %

S. A. Puviyarasu


From Figure 6 shows that an increase in Surface roughness and increase in speed SOD of

the aluminium titanium carbide composite. Considering the SOD, surface roughness (Ra)

does not change much, irrespective of the speed. From Figure 7 shows that initially decrease

in surface roughness and gradually increase in Ra and considering increase in SOD and

Reinforcement %. An increase or decrease in reinforcement % does not make much impact in

Ra, when SOD is considered. Figure 8 shows that initially decrease in surface roughness and

gradually increases in Ra and considering increase in SOD and Reinforcement %.

Figure 9 Residual plots for RA

Figure 9 shows that the normal probability plot, histogram chart, versus order charts for surface

roughness values.

5. CONCLUSION

The present study explored the investigation of material removal rate and surface roughness

of the material aluminium and titanium carbide with design of experiments (Response surface

methodology) using abrasive water jet machining. From the work, following inferences can

be drawn:

1) The input process parameters of AWJM can enhance the material removal .The

abrasive grain generated mechanically not only increased the MRR but also generated

fine surface integrities

2) The MRR of each reinforcement material is gradually increases when increase in

Standoff distance and also time reduces when increase in Standoff distance. Moreover,

the Standoff distance 98.75% is the maximum contribution for MRR. When

machining the material. By using small grain size of abrasive would promote to obtain

larger MRR..

3) In the case of surface roughness, the Standoff distance and reinforcement plays major

significance of 45.20% and 40.94%.Since, the confirmation experiment were

conducted on surface roughness as obtained response surface methodology. The

optimal response valve for surface roughness 2.8µm.




4) The test results provides the greater significant on selecting the output parameters such

as MRR and RA while machining the Aluminium and titanium carbide material on

abrasive water jet machining and also fits the requirement of modern day applications.

REFERENCES:

[1] Kannan S, Kishawy H.A, Surface characteristics of machined aluminium metal matrix

composites, International Journal of Machine Tools & Manufacture Vol.46,2006,

[2] Chinmaya R. Dandekar , Yung C. Shin, Modelling of machining of composite materials,

in: Centre for Laser-Based Manufacturing, International Journal of Machine Tools &

ManufactureVol.57, 2012,pp.102–121.

[3] D. Sidda Reddy et al, Parametric optimization of Abrasive water jet machining of Inconel

800H using Taguchi Methodology, Universal journal of Mechanical Engineering, 2(5),

158-162, 2014.

[4] Amina et al, Experimental Investigation of thermally enhanced abrasive water jet

machining of hard to machine metals, CIRP journal of manufacturing science and

technology, Vol 10, May 2010.

[5] M. Hashish, Observation of wear of abrasive water jet nozzle materials, Journal in

tribology, Vol 116 no 3, July 1994.

[6] Shah R. V, Patel D. M, Abrasive water jet machining- The Review, International Journal

of Engineering Research and Applications (IJERA), Vol 2 (5), September- October 2012,

pp.803-806.

[7] Khan A.A, Haque M.M, Performance of different abrasive materials during abrasive water

jet machining of glass, in: Journal of Materials Processing Technology Vol.191, 2007,

pp.404–407.

[8] Anderson and sinn, Evaluation of the machinability of Inconel 718 under varying

conditions, International journal of machine tools and manufacture, Vol 12 no 4, Jun 2012

[9] S. Muralidharan, N. Karthikeyan, Abburi Lakshman Kumar and I. Aatthisugan. A Study

on Machinability Characteristic in End Milling of Magnesium Composite. International

Journal of Mechanical Engineering and Technology, 8(6), 2017, pp. 455–462.

S. A. Puviyarasu is an active researcher in the field of Materials and Industrial

Engineering. He has published several International research journals. He

currently pursuing his bachelors in Engineering (Mechanical Engineering),

Dr N.G.P Institute of technology, Affiliated to Anna University, Chennai,

India. Maid Id: [email protected]

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AN INVESTIGATION OF MACHINABILITY & SURFACE INTEGRITY ON ALUMINIUM …€¦ · MMCs. To improve the fracture toughness of the conventional composites, the new class of materials known