Optimizing Linear Friction Welding Parameters to Attain Maximum Tensile Strength in Dissimilar Aluminum Alloy Joints

J. Ahamed Bahavudeena*, P. Sivarajb ,V. Balasubramanianc

aP.G Student, bAssistant Professor,3ProfessorCenter for Materials Joining and Research (CEMAJOR), Department of manufacturing Engineering,Annamalai University, Annamalai Nagar - 608002.

A B S T R A C T

Joining of Dissimilar aluminum alloys using conventional arc welding processes will lead to problems like porosity and hot cracking etc., To overcome

these issues, solid state welding processes like friction welding, friction stir welding and diffusion bonding are used. Recently, Linear Friction Welding

(LFW) process is being used to join the ferrous and non-ferrous materials due to its own advantages such as low heat input, high production efficiency and

environmental friendly. In this paper, Response Surface Methodology (RSM) was applied to optimize the linear friction welding process parameters to

attain maximum tensile strength of the joint. The maximum tensile strength of 240 MPa was obtained in the joints fabricated under the welding conditions

of friction pressure of 32.5 MPa, forging pressure of 1.1 MPa, friction time of 40 sec and oscillating frequency of 35 Hz.

KEYWORDS: Aluminum Alloys, Linear Friction Welding, Tensile Properties, Response Surface Methodology.

1.0 INTRODUCTIONDissimilar Welding of aluminium alloys AA6XXX and

AA5XXX is increasingly used in the fabrication of aircraft structures, aerospace components, ship building and vehicle bodies for their unique properties such as high strength to weight ratio and good corrosion resistance[1].Joining of aluminium alloys using conventional welding processes possess some problems like hot cracking, porosity and lack of fusion in the joints [2]. To overcome these issues, solid state welding techniques are preferred.

Linear Friction Welding (LFW) is solid state welding technique, used to join dissimilar alloys in which a stationary part is forced against a part that is reciprocating in a linear manner to generate friction heat [3]. The heat along with the force applied perpendicular to the weld interface, causes material at the interface to deform and plasticize as flash. Surface oxide and other impurities are removed as flash and this allows metal to metal contact between parts and joins. However, LFW may be particularly suitable for the welding of these materials as it has been demonstrated that the time at high temperature during welding can be controlled to some extent and hence producing welds with improved mechanical properties [4].

Wanjara et al. focused their research on the LFW of dissimilar AA6063 aluminum alloy and copper. Both process feasibility and the interface properties were investigated. A quite large process window was identified indicating that LFW can be considered as an effective alternative to Explosive Welding (EW) to join these metals, provided that sufficiently thick parts are

considered. As a matter of fact, LFW cannot be used to join this sheets because of difficulties in the parts clamping [5, 6]. Finally, dissimilar aluminum to aluminum joints were studied by Rotundo et al. [7]. In their paper, the authors showed the feasibility of LFW between AA2024 and a 2124/25 vol% SiCp composite. High joint efficiency was reached, with UTS and YS equal to the 90 % of the base material. Additionally, uniform particle distribution was found in the 2124/25 vol% SiCp composite side. In particular, aluminum alloys as 2XXX, 6XXX and 7XXX series are considered in the above areas because of their good mechanical properties and corrosion resistance [8].

From the literature review, it is understood that most of the published information on linear friction welding of dissimilar material focused on microstructural characteristics, micro hardness variations, and tensile properties evaluation. No systematic study has been reported so far to optimize the linear friction welding parameters to obtain maximum tensile strength in dissimilar aluminium alloys joints. Hence in this investigation an attempt was made to optimize linear friction welding process parameters to obtain the maximum tensile strength in dissimilar joints of AA5083 and AA6061 aluminium alloys using Response Surface Methodology (RSM).

2.0 EXPERIMENTAL WORK

The base materials, AA 5083-H111 and AA 6061-T6 aluminium alloys were used in this investigation with rectangular

* Corresponding author. Tel.: +91 9944200446E-mail address: bahavudeen.ahamed0@gmail.com

2 SOJOM 2018

flat specimen of dimension 60mm x 30mm x 6mm thickness. Linear Friction Welding Machine (capacity of 20 kN) was used to weld the joints. From the literature, the predominant factors which had greater influence on tensile strength of linear friction welded joints were identified. They are friction pressure, friction time, forging pressure and frequency. The definitions of these four factors were given below and it is explained. Friction Force (F) the load applied by stationary member towards oscillating member. It is also referred to as heating pressure and is calculated by dividing the applied load by cross sectional area of oscillating member. Friction Time [T] is the time of application of friction Force. It is also referred to as heating time. The machine has provision to set the time. Forging Force (P) is the load applied after applying sufficient time of friction load. It is also called as upsetting load. Frequency (O) is the number of oscillatory cycles per second.

Trial experiments were conducted to determine the working range of above factors. Feasible limits of the parameters were chosen in such a way that the friction welded joint should be free from any visible external defects. The important factors that influence the tensile properties of friction welded joint and their working range for AA 5083-H111 and AA 6061-T6 aluminium alloys are presented in table 1.

Table 1 Important Parameter and their levels

No

Factor UnitNotation

Levels-2 -1 0 +1 +2

1Friction Pressure

MPa F 27.5 30 32.5 35 37.5

2Friction Time

sec T 30 35 40 45 50

3Forging Pressure

MPa P 0.5 0.8 1.1 1.4 1.7

4Oscillation Frequency

Hz O 25 30 35 40 45

As the range of individual factor was wide, four factors and five level factorial design matrix were selected. The experimental design matrix (Table 2) consisting of 30 sets coded conditions and comprising a full replication of four-factor factorial design of 16 points, 8 star points, and 6 center points was used. The upper and lower limits of the parameters were coded as +2 and - 2, respectively. The coded values of intermediate levels of parameters can be calculated using the relationship as follows

Xi =2[2X- (Xmax+Xmin)]/ (Xmax - Xmin) (1)

where, Xi is the required coded value of a variable X; and X is any value of the variable from Xmin to Xmax. The friction welds were made as per the conditions dictated by the design matrix at random order so as to avoid the noise creeping output response. As prescribed by the design matrix, 30 joints were fabricated. Three tensile specimens from each welding conditions were fabricated as per the standards ASTM E8M-04 to evaluate the tensile strength of

the joints. The specimen was loaded at the rate of 1. 5 kN/min as per the ASTM specifications.

Table 2 Design matrix and Experimental results

Exp.No

Coded values Original Values Tensile strength of joints (MPa)

F T P OF

(MPa)T

(sec)P

(MPa)O

(Hz)

1 -1 -1 -1 -1 30 35 0.8 30 2062 1 -1 -1 -1 35 35 0.8 30 2133 -1 1 -1 -1 30 45 0.8 30 2004 1 1 -1 -1 35 45 0.8 30 2265 -1 -1 1 -1 30 35 1.4 30 2046 1 -1 1 -1 35 35 1.4 30 2037 -1 1 1 -1 30 45 1.4 30 2078 1 1 1 -1 35 45 1.4 30 2109 -1 -1 -1 1 30 35 0.8 40 19910 1 -1 -1 1 35 35 0.8 40 20211 -1 1 -1 1 30 45 0.8 40 20512 1 1 -1 1 35 45 0.8 40 21413 -1 -1 1 1 30 35 1.4 40 21814 1 -1 1 1 35 35 1.4 40 20715 -1 1 1 1 30 45 1.4 40 22016 1 1 1 1 35 45 1.4 40 21817 -2 0 0 0 27.5 40 1.1 35 19818 2 0 0 0 37.5 40 1.1 35 21019 0 -2 0 0 32.5 30 1.1 35 18420 0 2 0 0 32.5 50 1.1 35 19821 0 0 -2 0 32.5 40 0.5 35 21022 0 0 2 0 32.5 40 1.7 35 18423 0 0 0 -2 32.5 40 1.1 25 19824 0 0 0 2 32.5 40 1.1 45 22625 0 0 0 0 32.5 40 1.1 35 23826 0 0 0 0 32.5 40 1.1 35 23827 0 0 0 0 32.5 40 1.1 35 24028 0 0 0 0 32.5 40 1.1 35 23829 0 0 0 0 32.5 40 1.1 35 24030 0 0 0 0 32.5 40 1.1 35 237

3.0 DEVELOPMENT OF EMPIRICAL RELATIONSHIP

Tensile strength (TS) of Linear friction welded of dissimilar aluminium alloy joint is a function of the friction welding parameters such as Friction pressure, Friction Time, Forging pressure and oscillating frequency, and it can be expressed as

TS= f {F, T, P, O} (2)

The second-order polynomial (regression) equation used to represent the response surface Y (TS ) is given by

Y=bo+~biXi+~biiXi2; +~bijXiXj (3)

3 SOJOM 2018

and for four factors, the selected polynomial could be expressed as

R; =bo+bl(F) +b2(T) +b3(P) +b4(O) + bl2(FT) +b13(FP) +b14(FO) +b23(TP) + b24(TO) +b11 (F2) +b22(T2)+ b33(P2)+b44(O2) (4)

where, bois the average of the responses; and b1, b2, b3,…, b44are regression coefficients-f that depend on respective linear, interaction, and squared terms of factors. The value of the coefficient was calculated using Design Expert Software. The significance of each coefficient was determined by Student's t test, and p values, which are listed in Table 3. Values of "Prob>

LFW Machine full view LFW machine close up view during welding

Photograph of all the joints together

Photograph of one joint close up view

Photograph of all the Tensile Specimen(before testing)

Photograph of all the Tensile Specimen

(before testing)Fig 1 Joint fabrication and specimen Preparation

F" less than 0.0500 indicate that model terms are significant. In this case F, T, P, O, FT, FP,FO PO, F2, T2, P2 AND O2 are significant model terms. Values greater than 0.10 indicate that model terms are not significant. The final empirical relationship was constructed using only these coefficients, and the developed final empirical relationship is given below

Rm = [238.83+2.87(F)+3.04(T)-1.29(P)+3.71(O)+2.86(FT)-3.31(FP) -2.94(FO) -0.81(TP) +1.06(TO) +6.19(PO) -8.34(F2) -11.59(T2) -7.97(P2) -4.84(O2) MPa

Analysis of variance (ANOVA) technique was used to check the adequacy of the developed empirical relationship. In this investigation, the desired level of confidence was considered to be 95 %. The relationship may be considered to be adequate, provided

that 1) the calculated value of the F ratio of the model developed should not exceed the standard tabulated value of F ratio and 2) the calculated value of the R ratio of the developed relationship should exceed the standard tabulated value of R ratio for a desired level of confidence. It is found that the model is adequate. The F ratio of 120.18 for the model implies that the model is significant. There is only a 0.01% chance that this large F ratio of a model could occur due to noise. The lack of fit for F ratio of 1.55 implies that the lack of fit is insignificant. There is only a 32.92% chance that a lack of fit of this large F ratio could occur due to noise.

Table 3 Analysis of variance (ANOVA) test results

Note: 1) Significant; 2) Not significant. SD=2.14. Mean=212.63. CV% =1.01. PRESS= 24.24. R2= 0.9912; CV-Coefficient of variation; p-Probability.

The Fisher's F test with a very low probability value (Prob.>F=0.0001) demonstrates a very high significance for the regression model. The goodness of fit of the model was checked by the determination coefficient (R2). R2 was calculated to be 0.9912 for response. This implies that 99.12% of experimental data confirms the compatibility with the data predicted by the model, and the model does not explain only 0.82% of the total variations. The R2 value is always between 0 and 1, and its value indicates aptness of the model. For a good statistical model, R2value should be close to 1.0. The adjusted determination coefficient value reconstructs the expression with the significant terms. The value of the adjusted determination coefficient of 0.9829 is also high to

SourceSum of

Squares

Degree

of

freedom

Mean

Square

Fisher’s

ratio

P value

Prob>F

Model 7730.05 14 552.15 120.18 < 0.0001 significant

F 198.37 1 198.37 43.18 < 0.0001

T 222.04 1 222.04 48.33 < 0.0001

P 40.04 1 40.04 8.72 0.0099

O 330.04 1 330.04 71.83 < 0.0001

FT 105.06 1 105.06 22.87 0.0002

FP 175.56 1 175.56 38.21 < 0.0001

FO 138.06 1 138.06 30.05 < 0.0001

TP 10.56 1 10.56 2.30 0.1502

TO 18.06 1 18.06 3.93 0.0660

OP 612.56 1 612.56 133.33 < 0.0001

F2 1909.53 1 1909.53 415.62 < 0.0001

T2 3686.81 1 3686.81 802.45 < 0.0001

P2 1741.74 1 1741.74 379.10 < 0.0001

O2 643.53 1 643.53 140.07 < 0.0001

Residu

al68.92 15 4.59

Lack

of fit52.08 10 5.21 1.55 0.3292

Not

significant

Pure

error16.83 5 3.37

Correc

ted

total

7798.97 29

4 SOJOM 2018

advocate a high significance of the model. The predicted R2 is O.9584, which implies that the model could explain 95% of the variability in predicting new observations. This is in reasonable agreement with the adjusted determination coefficient 0.9829. The value of coefficient of variation is also low as 5, which indicates that the deviations between experimental and predicted values are low. Adequate precision measures the signal to noise ratio. A ratio greater than 4 is desirable. In this investigation, the ratio is 34.611, which indicates an adequate signal. This model can be used to navigate the design space.

4.0 OPTIMIZATION OF WELDING PARAMETERS

The response surface methodology (RSM) was used to optimize the parameters in this study. RSM is a collection of mathematical and statistical techniques that are useful for designing a set of experiments, developing a mathematical model, analyzing the optimum combination of input parameters, and expressing the values graphically [09]. To obtain the influencing nature and optimized condition of the process on tensile strength, the surface plots and contour plots which are the indications of possible independence of factors are developed for the proposed empirical relation by considering two parameters in the middle level and two parameters in the X and Y-axes as shown in Fig. 2. These response contours can help in the prediction of the response (tensile strength) for any zone of the experimental domain [10]. The apex of the response plot shows the maximum achievable tensile strength. A contour plot is produced to display the region of the optimal factor settings visually.

Fig. 2 Response graphs showing optimum welding conditions

For the second-order responses, such a plot can be more complex compared to the simple series of parallel lines that can occur with first-order models. Once the stationary point is found, it is usually necessary to characterize the response surface in the immediate vicinity of the point. Characterization involves identifying whether the stationary point is a minimum response or maximum response or a saddle point. To classify this, it is the most straightforward to examine it through a contour plot. Contour plots playa very important role in the study of a response surface. It is

clear in Fig. 2 that the tensile strength increases with the increase of friction Load, forging Load, friction time, and frequency to a certain value and then decreases. By analyzing the response surfaces, the maximum achievable tensile strength value is found to be 240 MPa. The corresponding parameters that yield this maximum value are friction pressure of 32.5, forging pressure of 1.09 MPa, friction time of 40 s, and Frequency of 35 Hz. Contributions made by the process parameters on ultimate tensile strength can be ranked from their respective F ratio which was seen in Table 3, provided the degrees of freedom are same for all the input parameters. The higher F ratio implies that the respective term is more significant and vice versa. From the F ratios, it can be concluded that friction time contributes more to tensile strength of the joint and it is followed by friction pressure, forging pressure, and oscillating frequency for the range considered in this investigation.

5.0 CHARACTERISTICS OF DISSIMILAR JOINT (UNDER OPTIMUM WELDING CONDITION)

The macro and microstructural characteristics of linear friction welded dissimilar joint of AA5083 and AA6061, welded using optimized welding parameters are displayed in Fig.3. the microhardness survey carried out across the weld also depicted in Fig.4 along tested tensile specimens. From the figure, it is observed that the failure location is HAZ region of AA 5083 and it is matching with lowest hardness region.

Macrostructure

Interface

Partially Deformed Zone –AA 5083

Partially Deformed Zone –AA 6061

Heat Affected Zone – AA 5083 Heat Affected Zone – AA 6061

240 MPa(

Mpa)

( M p a )

(Sec)

5 SOJOM 2018

Base Metal – AA 5083 Base Metal – AA 6061

Fig.3 Optical Microscope of various regions

Fig 4 Microhardness survey across the welded joint

6.0 CONCLUSIONS

1) An empirical relationship was developed to predict the tensile strength of linear friction welded dissimilar joints of AA 5083-H111 and AA6061-T6 aluminium alloys, incorporating process parameters. The developed relationship can be effectively used to predict the tensile strength of linear friction welded dissimilar joints of aluminium alloys at a confidence level of 95 %.2) A maximum tensile strength of 240 MPa could be obtained under the welding conditions of friction pressure of 32.5 MPa, forging pressure of 1.09 MPa, friction time of 40 s, and frequency of 35 s. Under these welding conditions, the heat generation owing to friction might be optimum to cause sufficient plastic deformation between the materials.3) Of the four process parameters investigated, Oscillating frequency was found to have greater influence on tensile strength of the joints, followed by friction pressure, forging pressure, and oscillating frequency.

REFERENCES

[1]. PalanivelR, Koshy MathewsP, Dinaharan I, Murugan N (2011);

Mechanical and metallurgical properties of dissimilar friction stir

welded AA5083-H111 and AA6351-T6 aluminum alloys.

[2]. Dickerson TL, Przydatek J (2003); Fatigue of friction stir welds in

aluminium alloys that contain root flaws. Int J Fatigue 25:1399–409.

6 SOJOM 2018

[3]. Bhamji I, Preuss M, Threadgill PL, Addison AC (2011); Solid state

joining of metals by linear friction welding: a literature review. Mater

Sci Technology 27(1):2–12.

[4]. Bhamji I, Preuss M, Threadgill PL, Addison AC (2012); Linear

friction welding of aluminium to Magnesium Science and Technology

of Welding and Joining 2012 VOL 17 NO 5

[5]. Wanjara P, Dalgaard E, Trigo G, Mandache C, Comeau G, Jonas JJ

(2011); Linear friction welding of Al-Cu: part 1 – process evaluation.

Can Metall Q 50(4):350–359.

[6].Bhamji I, Moat RJ, Preuss M, Threadgill PL, Addison AC, Peel MJ

(2012); Linear friction welding of aluminium to copper. SciTechnol

Weld Join 17(4):314–320.

[7]. Williams JC, Starke Jr EA (2003); Progress in structural materials

for aerospace systems. ActaMater 51(19):5775–5799.

[8]. Hirsch J, Al-Samman T (2013); Superior light metals by texture

engineering: Optimized aluminum and magnesium alloys for

automotive applications. Acta Mater 61 (3):818–843.

[9]. Yilmaz M. Investigation of the Welding Zone in Friction Welding

of Different Tool Steels [D]. Istanbul, Technical University of Yildiz,

1993.

[10]. Lakshminarayanan A K, Balasubramanian V. Comparison of

RSM With ANN in Predicting Tensile Strength of Friction Stir Welded

AA7039 Aluminum Alloy Joints [J]. Transactions of Nonferrous

Metals Society of China, 2009,