Numerical and Statistical Analysis for Betterment of ... · AZ31B Mg alloy includes 2.87% of...

Numerical and Statistical Analysis for Betterment of

Mechanical Properties During FSW of AZ31B Mg

Alloys 1I.S. Stephan Thangaiah, 2P. Sevvel, 3C. Satheesh, 4S. Manova Raja Singh

and 5V. Jaiganesh

1VIT Business School,

VIT University, Vellore, India.

[email protected]

2Department of Mechanical Engineering,

S.A. Engineering College,

Thiruverkadu, Chennai, India.

[email protected]


Madha Institute of Engineering, & Technology,

Tharapakkam, Chennai.

[email protected]




[email protected]




[email protected]

Abstract In this experimental paper, the role of the friction stir welding (FSW)

process parameters namely tool pin geometry, tool rotational speed, and

feed rate on the mechanical properties of AZ31B Mg alloy were

International Journal of Pure and Applied MathematicsVolume 117 No. 7 2017, 359-369ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

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investigated in a detailed manner. The basic objective of this work is to

understand by which process parameter, hardness of stir zone and tensile

strength are influenced and by which factor interactions they are inter

related. Experimental designs based on full factorial concept were carried

out to calculate the measurement of responses. Additionally, regression

analysis was also employed to create interrelationship between responses

and factors. The relevant degree of the linear regression equation was

calculated, which was thought to be useful judgement of the predictive

equation. Subsequently, the optimal factor levels were determined. The

experimental results revealed us that the most dominant factor on the

hardness and ultimate tensile strength in the nugget zone was the tool pin

geometry, the tool rotational speed occupies the position as the second

factor and the feed rate as the last factor.

International Journal of Pure and Applied Mathematics Special Issue

360

1. Introduction

In the recent years, aerospace and automotive industries extensively prefer

fabricated components and parts composed of magnesium alloys, because of

their combined interest towards larger strength and reduction in weight [1-5]. At

the same time, reasons including expulsion, voids in region of weld, cracking

etc makes it difficult to employ conventional welding techniques to join parts &

components composed of Mg [6-10]. At the same time, the innovative friction

stir welding (FSW) technique seems to be more appropriate for joining alloys of

Mg, as the joining takes place without melting the base metal. Moreover, it does

not require the use of electrodes, filler metals and the process is completely free

from toxic & non toxic fumes. Apart from this, obtaining high quality

weldments at lower cost with negligible level of residual stresses & distortion

are other attractive features of this technique [11-14]. The mechanical properties

of the FSW weldments are found to be determined by the proper selection of

process parameters like rotation speed of the tool, feed rate, axial force, tool pin

profile shape etc.

For the sake of improving the efficiency of the weldments, it is essential to

reduce the defects through maximization of the mechanical properties of the

joints [15-20]. Hence, in this paper, a detailed investigation was carried out to

understand the improvement in mechanical properties and the role of

corresponding important factors to intensify process reliability and level of

joining productivity.

2. Experimental Methodology & Design

AZ31B Mg alloy was taken as the base metal of investigation in the required

dimension of 100X50X5 mm in the form of flat plates. The composition of the

AZ31B Mg alloy includes 2.87% of aluminium, 0.72% of Zinc, 0.3% of

manganese, 0.05% of copper and balance being Mg. The joints were

successfully fabricated using a uniquely fabricated FSW machine housed with a

5 kW electric motor.

In this experimental investigation, the FSW process parameters namely

rotational speed of the tool (S), tool pin profile geometry (G) and feed rate (T)

were taken into consideration. T and F were mixed in three different levels

together with the employment of tools with square & taper pin profile shapes.

Figure 1 (a) illustrates in detail the photographic view of the two different tool

pin profiles used in this investigation. Fabrication of the AZ31B Mg alloy joints

using the combination of the above mentioned process parameters can be seen

in the Figure 1 (b) and Figure 1 (c) shows a part of the FSW joints fabricated

successfully during this investigation.


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Figure 1: Photographic View of the (a) Tool Pin Profile Employed in this

Investigation (b) Fabrication of the FSW Joints of AZ31B Mg Alloy Flat

Plates (c) part of the AZ31B Mg Alloy Joints Successfully Fabricated using

FSW Process

Table 1 describes in detail the selected factors and their levels adopted in

this investigation. The entire set of the experimental designs were carried out by

means of the full factorial experimental designs.

Table 1: Description of the Various FSW Process Parameters & their Factorial Levels

S.No FSW process

parameter Unit Symbol Level 1 Level 2 Level 3

1 Rotational speed of

Tool RPM S 750 1000 1250

2 Feed Rate mm/min T 50 75 100

3 Tool pin profile – G Taper

Cylindrical

Straight

Cylindrical –

3. Results, Interpretations & Analysis

Impact of Factor Levels

The plots of the major response for ultimate tensile strength (UTS) and stir zone

hardness (SZH) are illustrated in the Figure 2 and 3. It must be understood that

these plots show factor level versus means of the data. From these figures, we

can understand that the feed rate (T) factor has a major impact on both SZH and

UTS and this factor’s effect is directly proportional to responses. It can be seen

that, UTS and SZH increases with the increase in T. The tool pin profile (G)

seems to have the same impact on UTS like feed rate. But, it can be seen that,

there is a decrease in UTS with increase in tool rotational speed. Likewise,

identical results were obtained for both T & F w.r.t SZH as seen in Figure 3.

Figure 2: Graphical Illustration of the Plots of the Major Response for Ultimate Tensile

Strength (UTS)


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At the same time, use of taper pin profiled tool has led to the occurrence of the

softer stir zone when compared with that of the square pin profiled tool. The

decrease in the hardness also seems to be a straight value. From these graphical

illustrations, it can be understood that the reduction in UTS and SZH is mainly

due to the large amount of generation of frictional heat resulting from high

rotational speed of the tool. Uniform plastic deformation usually occurs at lower

temperature and only when the nugget zone is stirred for a shorter time period

(which happens at larger feed rates) leading to fine sized grains [21-25], thus

resulting in increased UTS and SZH in our investigation.

Figure 3: Graphical Illustration of the Plots of the Major Response for Stir Zone Hardness

(SZH)

Analysis of Regression

Regression analysis is employed in this investigation to determine the

relationship between the factors of FSW, UTS and SZH. UTS regression model

for coefficients of factor and their effects are described in Table 2.

Table 2: Coefficients of Regression for UTS

S.No. Denomination Coefficient S.E. Coeeficient G P

1 Constant 85.1808 2.089 38.997 0.000

2 T 8.3926 1.099 6.971 0.000

3 S – 3.0451 1.092 – 2.542 0.019

4 T X T – 1.2341 2.107 – 0.379 0.589

5 S X S 0.0531 2.101 0.034 0.892

6 T X S 0.8181 1.536 0.601 0.602

Method of least squares is employed in analysis of regression to determine the

equation coefficients, which is mentioned as Equ.1.

UTS (MPa) = 59.2997 + 0.2975 X (Feed rate – 0.0301) X (Tool rotational speed

– 0.00049)

X (Feed rate X Feed rate)+(0.0001 X Feed rate) X Tool rotational speed (1)

SZH regression model for coefficients of factor and their effects are described

in Table 3.


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Table 3: Coefficients of Regression for SZH

S.No. Denomination Coefficient S.E. Coeeficient G P

1 Constant 61.9949 1.1241 59.009 0.000

2 T 6.432 0.4992 12.102 0.000

3 S – 3.1039 0.4992 – 6.065 0.020

4 T X T 0.0000 1.0191 0.0000 1.102

5 S X S – 1.7989 1.0103 – 1.795 0.076

6 T X S 0.1501 0.7016 0.198 0.598

Method of least squares is employed in analysis of regression to determine the

equation coefficients, which is mentioned as Equ.2.

SZH (HV) = 11.0079 + 0.1953 X Feed rate + 0.4997 X Tool rotational speed(2)

The residual plots for the UTS are illustrated in a clear manner in Figure 4. The

figure comprises of residuals’probability (normal) plots, fits versus residual,

data order versus residual etc. From these figures, it can be cleary understood

that, the values of UTS seems to be higher at larger feed rates and at lower

values of tool rotational speed. At the same time, we have also obtained

improved values of UTS through raising the feed rates at lower values of tool

rotational speed. Similar effects were also observed with the stir zone hardness

values.

Figure 4: Residual Plots for UTS (Ultimate Tensile Strength)

Optimum FSW Conditions

In this paper, the best suitable (optimum) condition for obtaining good quality

FSW joints is determined using the methodology of signal to noise (S/N) ratio

[26-30]. From our detailed regression analysis, we can understand that, for this

investigation, the traces of improved performance are larger values of SZH and

UTS. Hence, the larger the value is, the better it was opted for determining the

ratio of S/N. Table 3 describes in detail the results of the S/N ratio associated

with SZH and UTS.


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Table 3: Optimum Levels of S/N Ratio for UTS and SZH

S.No. Symbol Mean S/N ratio for UTS Mean S/N ratio for SZH

Level 1 Level 2 Level 3 Level 1 Level 2 Level 3

1 T 74.548 81.040 91.798 52.478 61.786 66.149

2 S 87.045 82.717 80.048 64.041 63.468 55.714

3 G 82.467 86.674 – 62.012 59.456 –

Subsequently, the most suitable FSW performance values for UTS was obtained

using a feed rate of 100 mm/min, at a tool rotational speed of 750 rpm while

employing a taper pin profiled tool for joining AZ31B mg alloy flat plates. In

other words, the most optimal factor level for obtaining higher values of UTS is

T3S1G2 (for T, level 3; level 1 for S and for G, level 2). Likewise, the best

suitable FSW performance values of SZH were achieved at T3S1G1.

4. Conclusion

In this paper, a detailed experimental investigation and numerical analysis

were carried out to determine the best suitable combination of FSW process

parameters and to correlate the relationship between these FSW process

parameters by using regression analysis in the form of full factorial design

methodology. The FSW process parameters namely tool rotational speed, tool

pin profile geometry and feed rate were optimized and most suitable factor

levels were determined for obtaining improved values of SZH and UTS, by

means of full factorial design methodology and optimizing them by means of

S/N ratio concept. Finally, the below mentioned conclusions were observed and

recorded:

With the increase in the feed rate, there seems to be direct increase in the

SZH and UTS.

On the contrary, it was observed that, the SZH and UTS decreases with

the increase in the tool rotational speed.

From the regression analysis, it was found that the most dominating

FSW process parameters on UTS and SZH, in their influence level of

order is: feed rate, tool rotational speed and finally the tool pin profile.

From the S/N ratio results, the factor level combination of T3S1G2 was

the best suitable FSW condition for obtaining higher values of UTS.

Likewise, the factor level combination of T3S1G2 was the best suitable

FSW condition for obtaining higher values of SZH.

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