Effect of Cutting Condition of Abrasive Water Jet on the Kerf Geometry of Nickel Based Super Alloy

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International Journal of Emerging Technology and Advanced Engineering

Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 7, Issue 10, October 2017)

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Effect of Cutting Condition of Abrasive Water Jet on the Kerf

Geometry of Nickel Based Super Alloy

Arvind Kumar

1

, Hari Singh

2

, Vinod Kumar

3

1_{Department of Mechanical Engineering, C.E.C, Landran, Mohali, Punjab, India}

2_{Department of Mechanical Engineering, N.I.T.Kurukshetra, Kurukshetra, Haryana, India}

3

Department of Mechanical Engineering, Thapar University, Patiala, Punjab, India

Abstract- In this experimental study, an attempt has been

conducted to investigate the effects of abrasive water jet machine parameters on the Kerf geometry of Nickel based super alloy, Inconel 718. Experiment were carried out by varying four parameters such as water pressure , traverse speed, standoff distance and abrasive flow rate using response surface methodology (RSM) with Box Behnken Design (BBD). In order to determine the importance of each machine parameter on Kerf quality; ANOVA, was employed. Moreover by using Design Expert Software the mathematical model for Kerf width and taper were defined. It was observed that that pressure and traverse speed was the main factors which affect Kerf quality considerably.

Keywords- ANOVA, Box Behnken Design, Inconel 718,

Kerf taper, Response surface methodology.

I. INTRODUCTION

As the world is moving fast with new technology, the various industries such as nuclear, aerospace and power generation require an advanced material which should have some superior properties. One such material which can fill this void is Nickel based super alloy. Such materials are particularly well suited for the kind of services where high temperature environments, thermal shock, creep and corrosion resistance is required. It can maintain the requisite yield strength and toughness at very low and high

temperature (-250 to 7000C). These properties make them

ideal for jet engine, gas turbine and cryogenic storage tank. In this regard, Inconel 718 is used in the current investigation.

Apart from many advantages, it also possesses some limitation. Super alloy contains the constituents like Nickel or Titanium which make them difficult to machine due to

its rapid work hardening during machining by traditional

method like milling or turning. Limitation of conventional method drawn concern to use nontraditional technique for machining this kind of material. Among others, abrasive water jet machining is one of the leading nontraditional methods which now a days is used to machine very hard material.

Abrasive water jet machining is most suitable method for various reasons such as no heat affected zone on work piece, multi directional cutting and its ability to cut any complex shapes [1]. The basic machine setups of AWJM are shown in Fig.1. In AWJM process, the target material is removed by the action of a high velocity jet of water mixed with abrasive particles based on the principle of erosion process which involve two distinct mechanisms depending upon whether the eroded material is brittle or ductile in nature [2-3].

Fig. (1)

Abrasive water jet machining is an unconventional machining process that has been used successfully in various industrial operations for surface preparation and peening. Considerable efforts have been made by various researchers from last 3 decades to study this cutting technology from various points of view such as depth of penetration, material removal, surface roughness, kerf geometry in order to have improved performance and thorough understanding of the process.

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Ay et al. [4] Hascalik et al.[5] and Ma and Deam [6] found the kerf quality of Inconel, titanium and acrylic plastic respectively by varying only traverse speed of jet. Uthayakumar et al. [7] observe the cutting performance of Inconel with three machine parameters such as pressure, traverse speed and standoff distance. Jegaraj and Babu [8] prepared a design for quality cutting of Aluminum alloy by changing the size of nozzle assembly. Palleda [9] performed number of machining trial on glass to check the effect of standoff distance on kerf taper. Shanmugam and Masood [10] used energy conservation approach to find best optimal parameters so that minimum kerf taper may produce.

On the basis of previous study it has been conclude that researchers have concentrated on a single quality characteristic as objective during optimization of AWJM. Optimum value of process parameters for one quality characteristic may deteriorate other quality characteristics and hence the overall quality. No literature is available on multi-objective optimization of AWJM on Inconel material so this paper has attempted to examine the Kerf characteristics so that an optimal combination of machine variables can be found for required engineering tolerance.

II. MATERIALS AND METHODS

Inconel 718 is Nickel based super alloy known for its tensile, high impact, and rupture strength. The chemical composition and mechanical properties are reported in Tables I and II respectively

III. EXPERIMENTAL SETUP AND PROCEDURE

Inconel 718 nickel based alloy plate of size 200*200*16 mm has been used for the present investigation. All the experiments were performed on a Flow Mach (4020B) water jet machine equipped with 5 axes cutting head and ultra-high pressure pump Fig.(1). During cutting,

parameters such as jet impact angle (900), size of garnet

abrasive (80 mesh), and focusing tube diameter(0.75mm) are kept constant while four parameters such as P, AFR, SOD & TS have been varied. Total twenty nine slots were cut in length of 10 mm on one side of the plate. The Kerf width (Wt & Wb) was measured at top as well as the bottom

face, (as shown in Fig.2) of the work piece with Mitutoyo

Profile Projector PJ-A3000. The

TABLE 1

CHEMICAL COMPOSITION OF INCONEL 78

C% Si% P% Mn% S% Cr% Ni% Mo% Al% Co% Ti% Nb% Cu%

0.08 0.35 0.015 0.035 0.015 21.0 55.00 3.3 0.80 1.0 1.15 5.5 0.30

TABLE II

MECHANICAL PROPERTIES OF INCONEL 718

Melting point

(oC)

Density g/cm3

Hardness (HV150)

Tensile strength (Mpa)

Yield strength (

Mpa)

Thermal conductivity

(W/mK)

Elastic Modulus

(Gpa)

Modulus of rigidity

(Gpa)

1336 8.19 370 800-1000 1110 11.2 204.9 77.2

Kerf angle for each slot is calculated using the following equation [4]

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Fig.(2)[4]

IV. DESIGN OF EXPERIMENTS

The machining was planned according to response surface methodology, RSM(Box-Behnken Design) with the

four parameters at three levels as shown in Table III.

Levels and parameters were selected according to the machine capability and past research work. RSM, a collection of mathematical and statistical techniques, is used for analysis of the relation between different descriptive variables and one or more response variables [11]-[13]. In this present work, design expert 6.08 version software has been used for developing the predictive model of machine parameters to obtain a good quality surface. The design of experiments (DOE) matrix with all twenty-nine experiments with the output response for the process parameters is presented in Table IV. In this study, an effort has been made to model the empirical relation among

machining parameters by using RSM. ANOVA was

applied to check the validity of regression model and determine the quadratic effect of machine parameters on

the output response function.

TABLE III

LEVELS OF MACHINE PARAMETERS

S.NO. Symbols Input Variables Levels

1 2 3

1 A Water pressure(P), psi 25000 37500 50000

2 B Abrasive flow rate(AFR), lb/min 0.7 1.1 1.5

3 C Stand-off distance(SOD), mm 0.6 3.3 6

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TABLE IV

DOE MATRIX WITH RESPONSE RESULTS

Machine Input Parameters Output Response

Run No. Pressure Abrasive flow rate

Stand-off distance

Traverse speed

Top Kerf Width

Bottom Kerf Width

Kerf Angle

psi lb/min mm mm/min mm mm Deg.

1 25000.00 1.10 3.30 20.00 1.019 0.749 0.484

2 50000.00 1.10 3.30 20.00 1.039 0.995 0.079

3 37500.00 1.10 0.60 60.00 0.916 0.535 0.682

4 25000.00 1.10 6.00 40.00 1.102 0.675 0.765

5 25000.00 1.10 3.30 60.00 0.936 0.524 0.738

6 37500.00 1.10 3.30 40.00 0.976 0.655 0.575

7 37500.00 1.10 3.30 40.00 0.984 0.662 0.577

8 37500.00 1.10 3.30 40.00 0.983 0.669 0.562

9 37500.00 0.70 3.30 60.00 0.994 0.512 0.863

10 50000.00 1.50 3.30 40.00 1.113 0.76 0.632

11 37500.00 1.10 6.00 20.00 0.893 0.896 0.005

12 50000.00 0.70 3.30 40.00 1.222 0.805 0.749

13 37500.00 1.10 6.00 60.00 0.98 0.594 0.691

14 37500.00 1.10 3.30 40.00 0.953 0.672 0.503

15 37500.00 0.70 3.30 20.00 0.927 0.803 0.222

16 37500.00 1.50 0.60 40.00 0.988 0.544 0.795

17 37500.00 1.50 3.30 20.00 0.837 0.76 0.138

18 37500.00 0.70 6.00 40.00 1.036 0.655 0.682

19 37500.00 0.70 0.60 40.00 0.956 0.542 0.741

20 37500.00 1.10 3.30 40.00 0.929 0.641 0.516

21 25000.00 1.50 3.30 40.00 1.182 0.532 1.164

22 37500.00 1.10 0.60 20.00 0.858 0.82 0.068

23 37500.00 1.50 6.00 40.00 0.972 0.581 0.700

24 50000.00 1.10 0.60 40.00 1.119 0.802 0.568

25 37500.00 1.50 3.30 60.00 0.975 0.491 0.866

26 50000.00 1.10 6.00 40.00 1.349 0.897 0.809

27 25000.00 0.70 3.30 40.00 0.913 0.581 0.595

28 25000.00 1.10 0.60 40.00 1.121 0.605 0.924

29 50000.00 1.10 3.30 60.00 1.319 0.625 1.242

V.RESULT AND DISCUSSION

Tables V, VI and VII show the ANOVA result for top kerf width, bottom kerf width and kerf taper respectively. The p value < 0.05 (at confidence level) signify that the model is statistically significant. The model F- value 25.32, 87.57 and 52.26 from respective tables shows that model is

significant. The calculated R2 value(92.30, 97.22 and

96.67) from Table V, VI & VII showing that experimental and predicted values are in good correlation. The normal probability graph for both kerf width and taper (Fig. 3) showing that residual are coming along a straight line.

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Top Kerf Width = +1.84166 – (7.13526E-005*Pressure) + (0.71271*AFR-0.057623*SOD) - (8.16288E-005*Traverse

speed) + (1.03275E-009*Pressure2) -

(1.40646E-004*Traverse speed2) - (1.89000E-005*Pressure*AFR) +

(1.84444E-006*Pressure*SOD) +

(3.63000E-007*Pressure* Traversespeed) Eq. 1

Bottom Kerf Width = + 0.59156 –

(1.41697E-005*Pressure) + (0.83868*AFR) + (0.013889 *SOD) –

(7.37489E-003*Traverse speed) + (3.74530E-010*

Pressure2) – (0.40300*AFR2) +(6.94257E-005*Traverse

speed2) – (1.45000E-007*Pressure*Traverse speed) Eq.2

Kerf taper = + 1.54871 – (7.95024E-005*Pressure) – (0.18083*AFR) – (0.11531*SOD) + (0.026756*Traverse

speed) + (1.08739E-009*Pressure2) + (0.78457*AFR2) –

(4.44299E-004*Traverse speed2) –

(3.93000E-005*Pressure*AFR) + (2.96296E-006*Pressure*SOD) +

(6.62000E-007*Pressure*Traversespeed) Eq.3

DESIGN-EXPERT Plot Top Kerf Width

Studentized Residuals N or m al % P ro ba bi lit y

Normal Plot of Residuals

-2.82 -1.53 -0.24 1.05 2.33 1 5 10 20 30 50 70 80 90 95 99 DESIGN-EXPERT Plot Bottom Kerf Width

Studentized Residuals N or m al % P ro ba bi lit y

-2.81 -1.73 -0.64 0.44 1.52 1 5 10 20 30 50 70 80 90 95 99 DESIGN-EXPERT Plot kerf taper Studentized Residuals N or m al % P ro ba bi lit y

-2.77 -1.62 -0.47 0.68 1.83 1 5 10 20 30 50 70 80 90 95 99

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Fig.3 Normal Plot Vs. Residiual (a) at top kerf width, (b) bottom kerf width(c) kerf taper

DESIGN-EXPERT Plot Top Kerf Width

Actual P re di ct ed

Predicted vs. Actual

0.84 0.96 1.09 1.22 1.35

DESIGN-EXPERT Plot Bottom Kerf Width

Actual P re di ct ed

0.47 0.61 0.75 0.89 1.04

DESIGN-EXPERT Plot kerf taper Actual P re di ct ed

-0.01 0.29 0.58 0.87 1.16

(a) (b) (c)

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TABLE V

ANALYSIS OF VARIANCE (ANOVA) FOR TOP KERF WIDTH

SOURCE SS DOF MS F-VALUE P>F REMARKS

Model 0.409463 9 0.0454 25.31 < 0.0001 Significant

A 0.065712 1 0.0657 36.56 < 0.0001

B 3.01E-05 1 3.00833E-05 0.016 0.8984

C 0.011656 1 0.0116 6.486 0.0197

D 0.024934 1 0.0249 13.874 0.0014

A2 0.179721 1 0.179 100.008 < 0.0001

D2 0.021845 1 0.021 12.155 0.0025

AB 0.035721 1 0.035 19.877 0.0003

AC 0.0155 1 0.015 8.625 0.0085

AD 0.032942 1 0.032 18.331 0.0004

Residual 0.034144 19 0.001

Lack of fit 0.031898 15 0.0021 3.787 0.1035 not significant Pure error 0.002246 4 0.00056

Cor total 0.443607 28

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R-Squared 92.30 Adj R-Squared 88.66 Pred R-Squared 74.24

TABLE VI

ANALYSIS OF VARIANCE (ANOVA) FOR BOTTOM KERF WIDTH

SOURCE SS DOF MS

F-VALUE

P>F REMARKS

Model 0.469415 8 0.058677 87.57 < 0.0001 Significant

A 0.12 1 0.12 184.51 < 0.0001

B

4.408E-003 1 4.408E-003 6.58

0.0185

C 0.016875 1 0.016875 25.18 < 0.0001

D 0.25288 1 0.25288 377.42 < 0.0001

A2 0.023038 1 0.023038 34.38 < 0.0001

B2 0.02797 1 0.02797 41.74 < 0.0001

D2

5.188E-003

1

5.188E-003 7.74 0.0115

AD

5.256E-003

1

5.256E-003 7.85 0.0110

Residual

0.0134 20

6.700E-004

Lack of fit

0.012785 16

7.991E-004

5.19 0.0611 Not significant Pure error

6.148E-004

4

1.537E-004

Cor total

0.482815 28

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TABLE VII

ANALYSIS OF VARIANCE (ANOVA) FOR KERF TAPER

SOURCE SS DOF MS F-VALUE P>F REMARKS

Model 2.19161 10 0.219 52.26 < 0.0001 significant

A _0.045387 ₁ _0.045 _10.82 _0.0041

B

9.804E-003

1

9.804E-003 2.34 0.1436

C _0.001541 ₁ _0.0015 _0.36 _0.5519

D _1.234567 ₁ _1.234 _294.40 _{< 0.0001}

A2 _0.194202 ₁ _0.194 _46.31 _{< 0.0001}

B2 _0.106008 ₁ _0.106 _25.27 _{< 0.0001}

D2 0.212476 1 0.212 50.66 < 0.0001

AB 0.154449 1 0.154 36.83 < 0.0001

AC 0.04 1 0.04 9.53 0.0063

AD 0.109561 1 0.109 26.12 < 0.0001

Residual 0.075481 18 0.0041

Lack of fit 0.07 14 0.01 4.20 0.0878 Not significant

Pure error 0.004805 4 0.0012 Cor total _2.267091 ₂₈

R-Squared 96.77 Adj R-Squared 94.82 Pred R-Squared 87.59

VI. CONCLUSION

In this study, effect of abrasive water jet machine parameters on top kerf width, bottom kerf width and kerf taper of Inconel 718 was investigated. Response surface methodology (RSM) with Box Behnken Design (BBD) was used to find the quadratic effect of water pressure, abrasive flow rate, standoff distance and traverse speed on three kerf qualities. On the basis of experimental result and ANOVA analysis the following conclusion were drawn as follows;

1. It was found that water pressure and traverse speed,

the two most significant parameters effectively controls the top and bottom kerf width while Abrasive flow rate was found as an insignificant parameter for top kerf.

2. Traverse speed was the major parameter which

controls the kerf angle produced in abrasive water jet machining.

3. ANOVA analysis revealed that the actual and

predicted values show an excellent fit between the regression model and the experimental value.

Acknowledgement

The authors highly appreciate Mr. Rishi, Dass Electronics, Dehradoon, India for providing the necessary machine facilities of abrasive water jet and their assistance during experiment work.

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