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Infrared Physics & Technology

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Investigating the effect of process parameters on the temperature field andmechanical properties in pulsed laser welding of Ti6Al4V alloy sheet usingresponse surface methodology

Hamidreza Heydari, Mohammad Akbari⁎

Department of Mechanical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

A R T I C L E I N F O

Keywords:Pulsed laserWeldingresponse surface methodology (RSM)Regression modellingTensile strengthMelt pool

A B S T R A C T

Laser welding of Ti6Al4V alloy with 3 mm sheet thickness was studied. The effect of process parameters in-cluding laser peak power, pulse duration, and welding speed was systematically investigated on the temperaturefield of the fusion zone, tensile strength and elongation. The laser welding experiments were performed based oncentral composite design and response surface method to develop multiple regression models. The accuracy ofthe regression models was adequate through analysis of variance to make correlations between input parametersand responses. It was found that laser peak power and pulse duration had remarkable effects on weld tensilestrength melt pool dimensions and elongation rate. Increasing the laser peak power from 1800 to 2200 W, clearlyincreased the tensile strength about 300 Mpa. Both the elongation rate and melt pool dimensions significantlyincreased with augmentation of laser peak power. Increasing welding speed from 3 to 7 mm/s decreased thetemperature of the region near the fusion zone from 370 to 130 °C. Increasing welding speed significantlyreduced the mechanical strength for 3 mm thickness about 20 percent. On the contrary, this reduction effect isnegligible for the elongation rate about 10 percent due to creating high rates of martensitic structure and brittleproperties of the weld.

1. Introduction

Laser welding of titanium and its alloys is known as one of thepromising methods of joining for aerospace and biomedical industries.The systematic investigation and study of laser beam welding on tita-nium alloys seems to be beneficial for applying this method to variousindustrial purposes. Fabrication of different structure or instrumentswith different thickness and shapes could have been a challenge forimplementing the laser welding process because of selecting appro-priate joining process conditions [1–7]. Generally, many welding de-fects such as burned surface of the weld bead or incomplete melt poolpenetration leads to weak joint because of improper selection of processparameters or welding condition. There are a great number of researchstudies on laser welding of titanium and its alloy through experimentaland numerical analysis. Kumar et al. [8] welded Ti6Al4V alloy with1.4 mm thickness by using a pulsed Nd: YAG laser system. The effect ofheat input on the shape of the welded bead, width of the melt pool, HAZadjacent of the fusion zone and microstructure and mechanical prop-erties of laser welded samples was investigated. In other study, Kumaret al. [9] evaluated metallurgical properties of 5 mm thickness Ti6Al4V

welded plate with a fiber laser. The quality of the welded specimens isexamined in terms of penetration depth, weld bead appearance, geo-metry, hardness and microstructures developed in the fusion and heataffected zone. The results showed that the beam power in the laserwelding process plays an important role for the full penetration ofmelting in the base plate. Gao et al. [10] investigated the effect ofoverlap coefficient on the microstructures and mechanical properties ofNd: YAG laser welded Ti6Al4V alloy sheets. Microstructural studiesshowed that in case the overlap coefficient increases, the grains of thefusion zone became coarse and the width of the HAZ region increased.Gao et al. [11] used pulsed laser welding and developed a relationshipbetween welding parameters and the quality of Ti6Al4V welded joints.When the overlap coefficient is more than 75%, the number of poros-ities decreases as the overlap coefficient increased.

Casalino et al. [12] investigated the full penetration welding of2 mm thick Ti6Al4V plates in the butt state using high-brightness fiberlaser. The influences of different welding conditions on the morphologyof the weld bead, metallurgical and mechanical properties were in-vestigated. The mechanical behaviour was investigated in terms ofVickers microhardness and tensile strength. The efficiency of the

https://doi.org/10.1016/j.infrared.2020.103267Received 5 December 2019; Received in revised form 29 February 2020; Accepted 29 February 2020

⁎ Corresponding author.E-mail address: m.akbari.g80@gmail.com (M. Akbari).

Infrared Physics and Technology 106 (2020) 103267

Available online 02 March 20201350-4495/ © 2020 Elsevier B.V. All rights reserved.

T

welding process was calculated by the relation of the transmitted powerand the expansion of the melting zone. Fiber laser beam welding wasperformed on 2 mm thick Ti6Al4V alloy at different welding statussheet by using special protection gas (solstice system). Two distinctcross-sections of weld bead shapes (T-shaped and X-shaped) were ob-served according to the different line energies beads. It was shown thatT-typed welding situations are desirable while considering full pene-tration in keyhole mode, narrower weld width and lesser heat affectedzone [13].

Zhao et al. [14] studied the effects of laser power, scan speed andlaser beam error in terms of microstructure, chemical composition andmechanical properties. It was found that the fusion welding was in theupper part of the weld and brazing weld was formed at the lower part ofthe weld. The driving force of the different regions in the melt poolcould be varied. The strength of the joint was equal to or a bit greaterthan the base metal. Ahn et al..[15] optimized the high power fiberlaser welding parameters for Ti6Al4V alloy. The microstructural ana-lysis was performed to depict the effect of parameters.

Response Surface Method (RSM) was known as a beneficial nu-merical prediction in manufacturing processes such as laser welding ofdifferent materials such as Ti6Al4V, steels, etc [16,17].

Kumar et al. [18] studied empirical modelling of fiber laser beam

welding of 5 mm thick Ti6Al4V alloy based on actuarial design of ex-aminations. The relation between the process parameters like weldingpower, welding speed, and defocused location of the laser beam withthe responses like width of the molten pool, length of the heat affectedzone, and the area of fusion zone are established in terms of regressionmodels through response surface method (RSM). Also, the most sig-nificant process parameters and their optimum ranges are identifiedand their percentage contributions on output responses are calculated.

Optimization of TIG welding process for different materials such astool steel and stainless steel has been done using response surfacemethodology (RSM) based on central composite design (CCD) [19].

Table 1Chemical and mechanical properties for Ti6Al4V alloy.

Element Ti Si Zr Sn Nb Mo Mn Fe Cr V Al

composition Balance 0.03 0.02 0.05 0.02 0.03 0.02 0.04 0.01 4 6.5Ultimate tensile strength 950 MPa Tensile yield strength 880 MPaElongation at break 14% Density 4.43 g/cc

Fig. 1. Schematic of the experimental setup.

Fig. 2. Experimental setup for (a) laser welding head, (b) Thermocouple and DAQ card, (c) Thermocouple placement.

Fig. 3. Tensile test sample, a) dimensions, b) welded sample New paragraph:use this.

Table 2Factors and their levels.

variables sign unit levels

−2 −1 0 1 2Peak power pp W 1800 1900 2000 2100 2200Pulse duration pd ms 7 8 9 10 11Welding speed sp mm/s 3 4 5 6 7

H. Heydari and M. Akbari Infrared Physics and Technology 106 (2020) 103267

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Ragavendran et al. [20] studied optimization of the hybrid laser–TIGwelding parameters for austenitic stainless steel 316LN by integrating aTIG welding heat source and pulsed laser. The design matrix was gen-erated by using central composite design. The weld bead geometry wasconsidered as a response and multiple regression models were devel-oped to correlate the process parameters with the responses. Surfacequality of the weld produced by the laser–arc hybrid welding of 4 mmthick steel was studied by Moradi et al. [21]. The trends of stability interms of top weld width variation were estimated by using design ofexperiments particularly RSM method. The process parameters ofpulsed Nd:YAG laser beam welding of AISI316L sheet optimized totrough response surface methodology to achieve the maximum ultimatetensile strength. Using a full quadratic regression model, a relationbetween input parameters and the response was established [22].

The aim of the present study is to systematically assess the effect oflaser process parameters on the temperature field and mechanicalstrength of the Ti6Al4V welded joint. The three inputs variation ofwelding speed, laser power and pulse duration are considered. Thetemperature field adjacent the fusion zone, the tensile strength andelongation are considered as means of the responses for the statisticalanalysis. Simultaneous clarifying the relation between tensile strengthand elongation rate according to the temperature variation and

microstructural analysis has not been investigated before.

2. Materials and methods

The sheet of Ti6Al4V with 3 mm thickness was used for the laserwelding experiments. The samples dimensions were cut at length andwidth of 50 mm and 20 mm respectively. The chemical and physicalcharacterizations of materials are shown in Table 1.

The temperature measurement during laser welding experimentswas performed using thermocouples. For precision placement of thethermocouple tips, some grooves were engraved on the samples asshown in Fig. 1. A pulsed Nd:YAG flash lamp laser with maximumaverage power of 700 W was utilized for welding experiments. The laserbeam wavelength was 1.06 mm, maximum pulse energy of 40 J, pulsefrequency (1–250 Hz) and pulse duration (0.2–25 ms). A 3axis com-puter numerical control (CNC) table with special fixture for clampingand positioning of the samples was utilized to execute the weldingoperation and temperature measurement simultaneously. Argon gaswas applied through a coaxial nozzle at pressure of 2 bars for protectingthe fusion zone from against oxidation. K-type thermocouples with1 mm diameter at the tip were used. The thermocouples were mountedat distance of 2 mm away from the center of the fusion zone or center ofthe laser beam. The temperature measurement accuracy is± 1% for thetemperature range (0–400 °C). The temperature data were grabbed byusing Advantech USB 4718 module thermocouple and labview softwarefor recording. A Schematic view of the experimental setup and briefdescription of the elements are depicted in Fig. 1. An actual view of theexperimental setup is observed in Fig. 2.

The microstructure and shape of the fusion zone were investigatedusing optical microscope with ASTM E883-17 standard. The tensiletests samples were prepared under ASTM E8M standard and GOTECHuniversal testing machine was used for doing tests. A sample of pre-pared tensile test is shown in Fig. 3.

3. Experimental design

Applying design of experiments can systematically improve in-vestigating the effect of each process parameter on the responsethrough a limited number of experiments. It can also make a relationbetween input parameters and output responses so as to optimize theprocess parameters through a mathematical model at minimum error[23].

RSM (Response surface methodology) is known as a statistical

Table 3Experimental design matrix and the measured responses.

Experiment NO. Welding speed (mm/s) Peak power (W) Pulse duration (ms) Tensile Strength (Mpa) Elongation (%) Temperature (°C) Depth (mm) Width (mm)

1 −1 −1 −1 310 3.64 163 1.1 2.712 0 0 2 625 5.4 237 2.21 3.543 0 0 0 415 4 170 2.12 3.114 1 −1 −1 245 3.2 146 1.68 2.545 0 0 0 412 3.2 185 2.17 3.226 0 0 −2 295 4.8 190 2.05 2.837 1 1 1 620 5.3 253 2.25 3.148 −1 1 1 580 6.6 310 2.98 3.879 0 0 0 461 3.8 164 2.35 3.3210 −2 0 0 451 4.2 261 2.67 3.8811 0 0 0 480 3.7 191 2.3 3.2212 2 0 0 280 4.1 145 0.94 2.1413 1 −1 1 370 4.1 153 2.14 29414 0 0 0 431 3.3 155 2.1 3.1515 1 1 −1 258 4.85 255 2.19 3.4716 −1 −1 1 380 3.9 190 2.78 3.9417 −1 1 −1 356 5.9 270 2.86 3.8818 0 0 0 386 4.2 185 2.2 3.319 0 −2 0 370 3.7 133 0.8 3.120 0 2 0 610 8.2 374 2.5 3.7

Table 4Analysis of variance test results for temperature model.

Source DF Adj SS Adj MS F-Value P-Value

Model 8 77277.6 9659.7 43.11 0.000Linear 3 64220.7 21406.9 95.54 0.000Speed 1 8010.3 8010.3 35.75 0.000Power 1 52670.2 52670.2 235.08 0.000Pulse width 1 3540.2 3540.2 15.80 0.002Square 3 12535.8 4178.6 18.65 0.000Speed*Speed 1 1288.6 1288.6 5.75 0.035Power*Power 1 9841.2 9841.2 43.92 0.000Pulse width*Pulse width 1 5130.0 5130.0 22.90 0.0012-Way Interaction 2 521.0 260.5 1.16 0.348Speed*Power 1 40.5 40.5 0.18 0.679Speed*Pulse width 1 480.5 480.5 2.14 0.171Error 11 2464.6 224.1Lack-of-Fit 6 1462.6 243.8 1.22 0.424Pure Error 5 1002.0 200.4Total 19 79742.2R-sq = 97.25%R-sq(adj) = 95.25%R-sq(pred) = 97.25%

H. Heydari and M. Akbari Infrared Physics and Technology 106 (2020) 103267

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technique based on mathematics in order to model different applica-tions. Typically, RSM facilitate design of experiments using parametricanalysis of the experimental results as means of responses of the processparameters or input variables.

Basically, the experimental data including process variables and theresponses are fitted to quadratic models composed of second-orderPolynomial to consider different interactions and nonlinear effects ofthe variables [24]. Central Composite Design (CCD) is known as thepopular and useful design method in RSM. Generally, the arrangementof CCDs is around the central points with several replicas as means ofadditional center points to give better evaluation of the process para-meters for the empirical model [25]. This design composed of the fullquadratic effects including square, linear and interactions between thedifferent responses. The responses can be shown as 3D response surfaceor contour plots [26].

In general, a relation between independent variables as an input andthe responses obtained from the experiments with minimum error isdescribed as following [26]:

= ⋯ + εY f(x1, x2, , xk) (1)

In Eq. (1), ε indicates the error for the variables. Prediction of

response (y) is obtained through making a relationship between theindependent variables (xi) and the response surface [26].

The second order polynomial equation could be utilized so as toprovide a prediction model for the response (y) presented by the fol-lowing Eq. (2):

∑ ∑ ∑ ∑= + + + += =

y b C x D x E x x εi

k

i ii

k

i ii j

ij i j01 1

2

(2)

The terms b0 is the intercept or constant value which describe theaverages of the results. Terms of Ci (linear), Di (squared) and Eij (in-teraction) are the coefficients and ε is the random error of the regres-sion model. Analysis of variance is commonly utilized to estimate linearor second order polynomials significance gained from the experimentaldata. Thus, by using the sequential F-test and T-test at confidence levelof 95% the validity or accuracy of the calculated regression equation isevaluated.

A series of the experiments was designed based on a CentralComposite Design (CCD) matrix at five-level for each parameter inorder to systematically study the effect of the pulsed laser processparameters on the responses. As it is observed in Table 2, the inputparameters for the laser power (300–500 W), welding speed (3–7 mm/s) and pulse duration (7–10 ms) were selected as means of three inputvariables. The temperature, tensile strength and elongation of weldedjoints were considered as response. Table 3 illustrates the designedmatrix in form of the coded values (from −2 to + 2) for the inputparameters and the responses measured values. The experimental ma-trix design composed of six center points, eight experiments as factorialpoints and six experiments as axial points which totally has 20 ex-periments. This design includes the quadratic effects such as linear andsquare and two-way interactions of the responses.

4. Results and discussion

The 20 sets of laser welding experiments were performed accordingto the plan of the experimental design in Table 4. According to theexperimental design matrix, three input parameters including weldingspeed, peak power and pulse duration were selected in order to estab-lish a polynomial full quadratic model. This model makes the correla-tions between the responses (tensile strength, elongation and

Fig. 4. The effect of the process parameters on the temperature field:(a) speed and peak power, (b) speed and pulse duration (c) peak power and pulse duration.

Table 5Analysis of variance test results for tensile strength model.

Source DF Adj SS Adj MS F-Value P-Value

Model 5 238,486 47,697 24.26 0.000Linear 3 205,014 68,338 34.76 0.000speed 1 14,102 14,102 7.17 0.018power 1 61,133 61,133 31.09 0.000pulse width 1 129,780 129,780 66.01 0.000Square 1 14,361 14,361 7.30 0.017speed*speed 1 14,361 14,361 7.30 0.0172-Way Interaction 1 19,110 19,110 9.72 0.008power*pulse width 1 19,110 19,110 9.72 0.008Error 14 27,526 1966Lack-of-Fit 9 21,583 2398 2.02 0.227Pure Error 5 5943 1189Total 19 266,012R-sq = 89.65%R-sq(adj) = 85.96%R-sq(pred) = 71.95%

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temperature field) and input variables. The response values analysis forthis experimental design was done using Minitab software.

4.1. Effect of the process parameters on the temperature

For temperature, the results of the analysis of variance for thepolynomial quadratic model are shown in Table 4. According to theresults, all parameters are significant for the temperature field near thefusion zone. Evidently the P-values lower than 0.05 determined thesignificant influence of these parameters on the temperature. For thequadratic terms, all of them have significant effect particularly peakpower while interaction terms are insignificant.

From the analysis of variance (ANOVA) shown in Table 4, the re-gression model of the temperature indicates adequate fitness by con-sidering the measures such as adjusted R-squared which is more than95%. The temperature regression formula which is function of the threeprocess parameters is presented as following (see Eq. (3)):

= − − − + + +

− ×

p p sp p

p sp p

Temp

7791 28.3sp 7.5 134.4 7.57 0.002 10.2

7.75

p d p

d d

2 2

2 (3)

As it is observed in Fig. 4 and Table 4, the effect of peak power onthe temperature field variation is more significant than other para-meters. Both linear and quadratic terms for peak power had the highestinfluence on the temperature. The welding speed and pulse durationhad lower effect on the temperature in comparison to peak power. In-creasing welding speed clearly reduced the temperature while in-creasing pulse duration has the least effect among all variables.

4.2. Effect of the process parameters on tensile strength

Tensile strength is known as a major criterion for analysing the weldquality. Hence the effect of parameters on the tensile strength ofTi6Al4V weld joint was evaluated using ANOVA analysis and poly-nomial full quadratic model. The regression equation for the tensilestrength is presented as following (see Eq. (4)):

= + − − − + ×T P P sp p p6760 200SP 3.78 887 22.98 0.49St P d p d2

(4)

As it is observed in Table 5, the effect of all parameters (linearterms) on tensile strength is significant. In case of tensile strength, pulseduration and peak power are the influential orderly. The quadratic termof welding speed and the interaction between pulse duration and peakpower were statistically effective for tensile strength regarding the p-value below 0.05 (see Table 5). The adjusted R-squared is about 86%with the lack of fit value of 0.22 which implies this is insignificant andthe model is adequately fitted the data.

Furthermore, Fig. 5 clearly shows that the pulse duration has hadthe highest effect on the tensile strength. It could be concluded thatincreasing pulse duration not only increased the fusion zone tempera-ture but also vividly reduced the amount of martensite formation at thefusion zone. The reduction of martensite microstructure directly in-creases the tensile strength and reduces the possibility of cracking.Evidently, simultaneous increase of both peak power and pulse dura-tion significantly increases tensile strength. This could be attributedwith increasing the fusion zone temperature, depth of melt pool pene-tration and heating cycle as well. Therefore, interaction of laser peak

Fig. 5. The effect of the process parameters on the Tensile strength:(a) speed and peak power, (b) speed and pulse duration (c) peak power and pulse duration.

Table 6Analysis of variance test results for elongation model.

Source DF Adj SS Adj MS F-Value P-Value

Model 8 28.7736 3.5967 28.50 0.000Linear 3 18.9175 6.3058 49.97 0.000speed 1 0.4865 0.4865 3.86 0.075power 1 17.6610 17.6610 139.96 0.000pulse width 1 0.7700 0.7700 6.10 0.031Square 3 9.2806 3.0935 24.51 0.000speed*speed 1 0.2986 0.2986 2.37 0.152power*power 1 7.8560 7.8560 62.26 0.000pulse width*pulse width 1 3.0183 3.0183 23.92 0.0002-Way Interaction 2 0.5755 0.2878 2.28 0.148speed*power 1 0.5565 0.5565 4.41 0.060speed*pulse width 1 0.0190 0.0190 0.15 0.705Error 11 1.3881 0.1262Lack-of-Fit 6 0.6281 0.1047 0.69 0.671Pure Error 5 0.7600 0.1520Total 19 30.1617R-sq = 95.33%

R-sq(adj) = 92.61%R-sq(pred) 84.60%

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power and pulse duration at the same time will improve the mechanicalstrength due to higher temperature gradient induced the fusion zone atlonger heating time and lower rate of fusion zone cooling.

4.3. Effect of the process parameters on elongation

In fact, the elongation could be a major measurement to determinethe plasticity behaviour of the weld joint. As shown in Table 6, theterms of peak power and pulse duration (both linear and quadratic)have p-value lower than 0.05 which are statistically significant. Thevalue of the lack of fit is about 0.7 which is insignificant. Therefore, theregression model Eq. (5) with adjusted R-squared 92% fitted the ex-perimental data adequately as following:

= + − − + +

+ − ×

Elongation

p p sp

p p sp p

(%)

209.6 4.01s 0.1999 6.02 0.1090 0.000056

0.3465 0.00264

p d

p d d

2

2 2(5)

As shown in Fig. 6, by increasing laser peak power, the elongationrate remarkably boosted due to creating bigger melt pool and deeper

Fig. 6. The effect of the process parameters on the Elongation:(a) speed and Pulse duration, (b) speed and peak power (c) peak power and pulse duration.

Fig. 7. Variation of melt pool dimensions at different laser peak powers, a) test No.19, b) test No.18, c) test No.20, d) test No.17, e) test No.8.

Table 7Melt pool dimensions (depth and width) for different laser peak powers.

Experiment No. Depth (mm) Width (mm)

18 2.2 3.319 0.8 3.120 2.5 3.717 2.7 3.98 2.9 4.1

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fusion zone. On the contrary, increasing welding speed clearly reducedmelt pool dimensions and temperature of the fusion zone. Hence, in-complete penetration notably decreased the elongation rate. Seemingly,the elongation of thin Ti6Al4V welded sheets has the same behaviourwith increasing welding speed as reported in [27] because of formationof more porosities and brittle structures of the fusion zone.

As depicted in Fig. 7, increasing laser peak power clearly increasedthe melt pool penetration and width of the fusion zone. Table 7 showsthe dimensions (depth and width) of the melt pool. Therefore, aug-mentation of the melt pool dimensions has directly impact on in-creasing both tensile strength and elongation. In case of higher thick-ness, increasing the melt pool dimensions has more significant influencethan other measures such as temperature or the amount of martensitemicrostructure. Increasing both pulse duration and peak power led tothe full penetration weld (test No.8).

5. Conclusion

Pulsed Nd:YAG laser welding of thick Ti6Al4V alloy was studiedusing statistical analysis. Mathematical modeling for investigation theeffect peak power, pulse duration and welding speed on temperaturefiled, tensile strength and elongation was performed.

(1) According to ANOVA method, the process parameters such as laserpeak power and pulse duration had significant influence on weldtensile strength and elongation.

(2) The interaction of laser peak power and pulse duration had re-markable effect on weld tensile strength because of simultaneousincrease of temperature gradient and heating cycle which in turnreduce the possibility of cracking when the penetration rate in-creased.

(3) The parameters of welding speed and peak power had significanteffect on the temperature field near the fusion zone. Meantime,increasing the pulse duration had lower influence on weldingtemperature variation. Hence the laser peak power and weldingspeed could have significant effect on variation of melt pool di-mensions. For example, increasing welding speed from 3 to 7 mm/sdecreased the temperature of the region near the fusion zone from370 to 130 °C.

(4) Increasing welding speed not only decreased the temperature of thefusion zone and melt pool dimensions but also clearly reduced theelongation rate. The elongation reduction is more significant athigh peak power levels due to clear decrease of laser line energy pertime. Increasing the welding speed created higher rate of coolingwhich in turn increase the amount of martensite formation in themelt pool and increase the possibility of brittle microstructureformation. It clearly reduces the elongation rate of the weldedsamples.

Declaration of Competing Interest

The authors declare that they have no known competing financialinterests or personal relationships that could have appeared to influ-ence the work reported in this paper.

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