Continuous-wave fiber laser cutting ofaluminum thin sheets: effect ofprocess parameters and optimization

Leonardo Daniele Scintilla

Continuous-wave fiber laser cutting ofaluminum thin sheets: effect ofprocess parameters and optimization

Leonardo Daniele Scintilla

Continuous-wave fiber laser cutting of aluminum thinsheets: effect of process parameters and optimization

Leonardo Daniele Scintilla*Politecnico di Bari, Dipartimento di Meccanica, Matematica e Management, Viale Japigia, 182, 70126 Bari, Italy

Abstract. One-millimeter-thick Al 1050 sheets were cut using a 2-kW fiber laser operating in continuous-wave(CW) mode. An experimental approach that consisted of fitting the regression models by means of responsesurface methodology was adopted. The effects of cutting speed, assist gas pressure, and focal position onroughness arithmetic mean value were investigated. The desirability function was applied for the simultane-ous optimization of cut quality and operating costs. The full potential of the CW mode high processing speedsand of the better absorptivity of 1-μm laser radiation for highly reflective materials are employed at the sametime. Cutting aluminum with fiber laser increases the cutting speed and gives a cut quality comparable withresults obtained with CO2 and Nd:YAG lasers that represent the most established laser sources for thisapplication. © 2014 Society of Photo-Optical Instrumentation Engineers (SPIE) [DOI: 10.1117/1.OE.53.6.066113]

Keywords: laser cutting; aluminum sheet; optimization; fiber laser.

Paper 140671P received Apr. 24, 2014; accepted for publication May 19, 2014; published online Jun. 27, 2014.

1 IntroductionLaser beam cutting (LBC) is the most favorable method tocut sheets in complex shapes and intricate profiles. It is aconsolidated sheet metal trimming technology in almostall automotive industries.1 The capability of the laser cuttingtechnology mainly depends on the optical and thermal prop-erties rather than mechanical properties of the material to becut. Aluminum (Al) and its alloys are considered as difficult-to-cut materials with laser cutting process:2 it is affected by(1) the high reflectivity that causes high requirements in laserpower and back-reflected beams; (2) the high thermal con-ductivity that produces a large heat affected zone (HAZ);(3) the formation of an aluminum oxide layer on the moltenmaterial that prevents the use of reactive laser fusion tech-nique; and (4) the high viscosity of molten material thatmakes its removal difficult.3 The proper selection of processparameters plays a crucial role to gain the required cutquality in such materials. For that reason, the investigationon the process parameter effects and the detection of theoptimal cutting condition based on design of experiment(DOE) techniques represent the best approach. Benyounisand Olabi4 provided a reference guide on the optimizingtechniques. They outlined the selection criteria of the appro-priate technique among factorial design, linear regression,response surface methodology (RSM), artificial neural net-works, Taguchi method, and various combinations of these.In order to model, analyze, and optimize single or multiplequality characteristics in the LBC of different materials, mostof the cited methodologies are applied by researchers. Inrecent years, DOE techniques were implemented to achievebetter cut qualities in LBC of polyethylene,5 medium densityfiberboard,6 and stainless steel.7 The RSM was employed toobtain optimum LBC responses as minimum tapering andmaximum material removal rate of Al∕Al2O3-MMC8 orHAZ extension, surface roughness, and dimensional accu-racy in polymers.9 In case of Al and its alloys, many papers

dealt with the optimization of cut quality using differentmethods. Dubey and Yadava applied Taguchi method foroptimization of kerf deviation and kerf width10 and materialremoval rate using quality loss function,11 cutting 0.9-mm-thick 8011 aluminum alloy sheets with a pulsed Nd:YAGlaser. Sharma and Yadava utilized two different hybridapproaches for multiobjective optimization during pulsedNd:YAG laser cutting of thin Al-alloy sheet for straight12

and curved13 profiles. Pandey and Dubey combined robustparameter design methodology and fuzzy logic theory tocompute the fuzzy multiresponse performance index.14

They also used a hybrid approach optimization of grayrelational analysis and fuzzy logic theory to improve thecut quality of 1-mm Duralumin sheet by simultaneouslyoptimizing multiple performances.2

As a result of literature review, it can be gathered thatthe most extensively used lasers for Al and its alloys sheetcutting are continuous wave (CW) CO2

3,15–18 and Nd:YAGoperating in pulsed mode (PM).10–14 High-power CW fiberlasers, emitting at 1.07 μm, represent valid and reliable alter-natives to CO2 and Nd:YAG lasers cutting Al and its alloysfor their typical applications in the automotive field. In fact,better absorptivity of 1-μm laser radiation and much higherprocessing speeds of CW mode with respect to the PM canbe achieved at the same time. The comparison between fiberand CO2 lasers from a technical and commercial point ofview revealed that the fiber lasers are better than CO2 lasersat cutting highly reflective materials like copper and alumi-num alloys and thin section metals, below about 4 mm.19

A small number of research studies about cutting Al andits alloys with fiber laser sources have been reported. Theydealt with cutting 3-mm-thick Al 2024-T3 using argon20 and4-mm-thick Al 5754 sheets using nitrogen.21 The develop-ment of the new generation of direct diode laser sources,suitable for cutting applications, makes possible the compari-son of preliminary results with the performance achievablewith CO2 and fiber laser sources.22

*Address all correspondence to: Leonardo Daniele Scintilla, E-mail:leonardodaniele.scintilla@poliba.it 0091-3286/2014/$25.00 © 2014 SPIE

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Optical Engineering 53(6), 066113 (June 2014)

In this work, the process condition that allows optimizingat the same time the cut edge quality and the operating cost of1-mm-thick Al1050 sheets fiber laser cutting was identified.To the author’s knowledge, the systematic analysis based onRSM cutting this material with CW high power fiber laserhas not been investigated. The aim is to find the suitablecombination of process parameters in a material consideredas difficult-to-cut and to show the potential of fiber lasers interms of cut quality and processing speed with respect tothe most established laser sources. The effect of each lasercutting parameter responses, namely cutting speed, assist gaspressure, and focal position, on roughness arithmetic meanvalue was studied. As the models have been developed andchecked for their adequacy, the optimal cutting condition canbe found by using desirability approach. A classification ofcut quality was also performed according to the standardISO 9013.

2 Experimental Details

2.1 Test Material and Laser Sources

Cutting experiments were performed on Al 1050 of 1-mm-thick sheets. Cutting tests were conducted in CW mode andusing nitrogen as assist gas. The multimode fiber laser(BPP ¼ 2.7 mmmrad) used for cutting experiments hadthe following specifications: 2-kW maximum output power,1.07-μmwavelength, and 100-μm output fiber core diameter.The laser beam was focused using a 5-in. focal length lens,resulting in random polarized beam. The minimummeasuredspot diameter after the beam passed the transmission fiberand the optical elements was 162 μm. Nitrogen was suppliedcoaxially using a cylindrical copper nozzle with 2-mm exitdiameter. A standoff distance of 0.8 mm from the workpiecewas set.

2.2 Cutting Tests Input Parameters

The definition of the input parameters and their levels wasbased on a previous work by Scintilla and Tricarico,23 whereAl 1050 cutting tests were performed by varying only twofactors, namely cutting speed (vC) and assist gas pressure(p). In this work, the focal position (f) is considered asan additional factor. All cutting tests were performed inCW operation mode and using a laser power (PL) equalto 2000 W. Linear cuts were performed on 150-mm-lengthspecimens. The choice of the input parameter values for thegeneration of the experimental plan is detailed in Sec. 3.1.

2.3 Cut Quality Assessment

Roughness arithmetic (Ra) mean value was considered asan indicator of cut quality. Furthermore, a classification ofcut quality was also performed according to ISO 9013.According to this standard, the quality of cut surfaces of ther-mally cut materials is described by perpendicularity or angu-larity tolerance (u) and the mean height of the profile (Rz5).Roughness was measured by means of a surface roughnesstester (Mitutoyo Surftest, Kawasaki, Japan SJ-401) in theupper (UP) and lower (LOW) part of the cut edge at a dis-tance of 0.33 mm from the surface and the bottom part of thesheet, respectively. In this study, the higher values of rough-ness among those measured in the different parts of thecutting edges (UP, LOW) for each sample are considered

as representative. For evaluation of u, cut edges were photo-graphed by a multipurpose zoom microscope (Nikon, Tokyo,Japan AZ100M) and measured by image analysis software.

3 Modeling and Optimization

3.1 Experimental Design

The experimental design chosen for the regression modelfitting was the face-centered central composite design.The distance α of the axial runs from the design center isequal to 1. This design locates the star or axial points onthe centers of the face of the cube and in this way, it requiresonly three levels of each factor.24 Cutting speed was set in therange between 17 and 23 m∕min, focal position was estab-lished between 0 and −1.5 mm, and the assist gas pressurewas varied in the range between 0.4 and 1 MPa. Table 1 illus-trates the laser input variables and the assigned experimentaldesign levels.

The best models were selected using the sequential f-testand other adequacy measures. A step-wise regressionmethod was used in order to fit the second-order polynomialEq. (1) to the experimental data and to identify the relevantmodel term

y ¼ β0 þXk

i¼1

βixi þXk

i¼1

βix2ii þX

i<j

βijxixj þ ε: (1)

The mathematical relationships between the responsey and input process variables xi expressed by Eq. (1) consistof linear terms, square terms, and linear interactions. Theparameter β0 defines the intercept of the plane; βi, βii, βijare the second-order regression coefficients; and ε representsthe noise or error observed in the response y.

3.2 Optimization

In this work, the optimization of cut quality was realizedapplying the desirability function. Papers reported in the lit-erature show that the desirability approach was successfullyimplemented for the process parameters optimization in lasermaterial processing field and in particular the laser weld-ing25–27 and laser cutting.5–7 The general approach consistsof converting each response yi into an individual desirabilityfunction di that varies over the range 0 ≤ di ≤ 1. If theresponse yi is at its goal or target, then di ¼ 1, and if theresponse is outside an acceptable region, di ¼ 0.24 Thenthe design variables are chosen to maximize the overalldesirability as expressed by

Table 1 Levels of independent factors used in the designed laserbeam cutting experiments.

Symbol Factor Unit

Level

−1 þ1

vC Cutting speed m∕min 17 23

p Assist gas pressure MPa 0.4 1

f Focal position mm −1.5 0

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D ¼ ðd1 · d2: : : dmÞ1∕m; (2)

where m is the number of responses.This optimization technique has flexibility in assigning

weights and importance on each factor and responses. Ashighlighted by Eltawahni et al.,7 although the most desirableresult is to obtain the best cut quality in terms of surfaceroughness, kerfs dimensions, etc., the final cut qualityinfluences the cost of the realized part. Since laser cuttingis a multi-input and multi-output process, in order to runan in-depth optimization, it is of fundamental importanceto clearly identify the goals of optimization and related cri-terion. In this work, the optimization criterion is to find outthe process parameters combination which would minimizeat the same time the cut quality and operating cost by min-imizing the laser power and maximizing the cutting speed.

4 Results and Discussion

4.1 Analysis of Variance

Among the roughness values of the different parts of the cut-ting edges, those measured in the lower part (RaLOW) areconsidered as representative due to their higher valueswith respect to the corresponding values measured in theupper part. In Ref. 28, the application of the model adequacymeasures performed on other cut quality measures, namelykerf width at the sheet surface and dross height, highlightedthat these models are not adequate. The process parametersof the experimental design matrix, the average measuredresponses, and the corresponding cut edge images are pre-sented in Fig. 1. According to Montgomery,24 in case arun is missing for a variety of reasons, it is possible to fitthe model using the remaining observations. The experimen-tal point f ¼ −1.5 mm, p ¼ 0.4 MPa, and vC ¼ 23 m∕minthat resulted in a “no-cut” condition, as shown in Fig. 1, isconsidered as missing data in the development of regres-sion model.

Table 2 summarizes the resulting analysis of variance(ANOVA) for the reduced quadratic models of RaLOW andshows the significant model terms. With regard to the hier-archy of the model terms, the step-wise regression methodwas used. The nonsignificant model terms were removed.Concerning the adequacy measures, the adequate precisionis 6.247. This parameter compares the range of the predictedvalue at the design points to the average prediction error.Since it is greater than 4, which represents the desiredratio, it indicates an adequate model. The ANOVA for theRaLOW indicates that cutting speed is the most significantmodel term. In addition, the main effects of focal position

Std RunFactor Image

vC, m/min p, MPa f, mm

15 1 20 0.7 -0.75

3 2 17 0.4 0

12 3 20 0.7 0

2 4 23 0.4 -1.5

7 5 17 1 0

11 6 20 0.7 -1.5

8 7 23 1 0

1 8 17 0.4 -1.5

14 9 20 1 -0.75

9 10 17 0.7 -0.75

6 11 23 1 -1.5 NO CUT

4 12 23 0.4 0

5 13 17 1 -1.5

10 14 23 0.7 -0.75

13 15 20 0.4 -0.75

Fig. 1 Experimental runs list and the corresponding cut edge image.

Table 2 Analysis of variance table for significant factors in RaLOWreduced model.

SourceSum ofsquares df

Meansquare f -value Prob > f

Model 3.65 3 1.22 4.17 0.0372

Cutting speed 2.46 1 2.46 8.40 0.0159

Assist gas pressure 0.92 1 0.92 3.15 0.1065

Focal position 1.18 1 1.18 4.03 0.0725

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and assist gas pressure are the important factors influencingthe model as well. The step-wise ANOVA procedure showsthat all the second-order effects (v2C, p

2, f2) and the two-levelinteractions of cutting speed, focal position, and assist gaspressure (vC × p, p × f, vC × f) are not important factorsaffecting the model.

The coefficients of the reduced mathematical modelobtained starting from Eq. (1) are reported in Table 3 interms of both coded and actual factors.

The residual versus run plot of RaLOW in Fig. 2 showsa random scatter, as expected. Normal plots of residuals(Fig. 3) indicate that except some moderate scatter, pointsfollow a straight line, which indicates that the residualsfollow a normal distribution.

4.2 Effect of Process Factor on RaLOW

The effects of the three factors on RaLOW were evaluated interms of contour plots. From Fig. 4, it can be noted that thedeveloped model predicts an increase of RaLOW at f ¼ −1.5with an increasing cutting speed and a decreasing assist gaspressure. For vC ¼ 23 m∕min and p ¼ 0.4 MPa that corre-sponds to the “no-cut” condition, the calculated RaLOWaccording to the model is 4.387 μm. This represents themaximum value calculated by the model in the range ofprocess parameters explored. Although the experimentalevidence shows a “no-cut” condition in that point, the pre-dicted RaLOW trend is consistent with the experimentalevidence that exhibits a marked decrease of cut quality fora certain combination of process parameters.

Figures 4–6 illustrate the mutual effect of assist gaspressure and cutting speed on RaLOW for different values offocal positions. They show that trends of RaLOW when focal

position is set at its middle (f ¼ −0.75) and higher values(f ¼ 0 mm) are very similar to the one obtained at midvaluef ¼ −1.5 (Fig. 4). The combination of lower values of vCand higher values of p, as well as the focal position seton sheet surface (f ¼ 0 mm), is most desirable conditionin order to achieve lower values of RaLOW.

Trends of RaLOW varying f and p for different values ofvC are very similar and therefore only the contour plot atmiddle value of cutting speed (vC ¼ 20 m∕min) is illus-trated in Fig. 7. It shows that a slight decrease of RaLOWoccurs with the simultaneous rising of focal position from−1.5 mm to 0 and assist gas pressure from 0.4 to 1 MPa.Best results are obtained for vC ¼ 17 m∕min. The combinedeffects of vC and f on RaLOW for p ¼ 0.7 MPa are repre-sented in Fig. 8. Very similar trends for p ¼ 1 MPa and p ¼0.4 MPa were detected and consequently they are notreported here. The combination of higher values of f andlower values of vC gives the lower value of RaLOW.

Contour plots in Figs. 4–8 show that for different valuesof f and vC, RaLOW is reduced by increasing assist gas pres-sure and by decreasing cutting speed. For a fixed laser powerand optical setup, when the cutting speed is increased, amaximum cutting speed is reached: beyond this limit, theenergy provided to material is insufficient to produce com-plete cut. The decrease of cut quality can be explainedconsidering that the optimal cutting speed giving the bestcut quality is lower than the maximum achievable cuttingspeed for the particular value of the set laser power. Whencutting speed is increased beyond optimal, phenomena suchas dross formation and deterioration of cut edge roughnessoccurs. In order to have a better cut quality, assist gas pres-sure and laser power have to be increased. In fact, the incre-ment in cutting speed as a result of the increase of assist gaspressure is a consequence of the higher momentum trans-ferred to the molten material, as reported by Riveiro et al.3

Furthermore, the increase of laser power leads to highervalues of the average temperature of the molten materialthat reduces the viscosity and makes it more easily removedby the assist gas jet. The effect of focal position can beexplained by the modification on workpiece surface ofthe irradiance. For a fixed laser power and optical setup,

Table 3 Coefficients of developed mathematical model for RaLOW.

Model β0 β1 β2 β3

Coded 3.16 0.53 −0.33 −0.37

Actual −4.31579E − 3 0.17774 −1.08737 −0.49228

Fig. 2 Residual versus run number for RaLOW.

Fig. 3 Normal plot of residuals for RaLOW.

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when the focal position is set on the surface (f ¼ 0 mm),the maximum irradiance is obtained. In this condition,the energy supplied to melt the workpiece material and toincrease the molten material temperature is higher.

4.3 Optimization

The optimization goals and the respective importance intro-duced for numerical optimization are reported in Table 4. Inorder to optimize both cut quality and operating costs, fromone side, RaLOW has to be minimized. From the other side,assist gas pressure and cutting speed have to be minimizedand maximized, respectively. The criterion on focal position(maximization with the highest value of the importance) actsas a constraint and meets the requirement for avoiding a com-bination of process input parameters that could result in a

“no-cut” condition. In fact, the latter condition was observedfor minimum value of focal position (f ¼ −1.5 mm).

Table 5 shows the optimal condition of process factorscalculated by desirability method and the respective responsevalues for the set criterion. It should be reported that, ifonly the best cut quality criterion is taken into considera-tion (RaLOW minimization, vC and p in the range, f maxi-mization), the optimized condition is represented byvC ¼ 17 m∕min, p ¼ 1 MPa, and f ¼ 0. It coincides withone of the experimental conditions observed in which RaLOWis 2.065 μm.

Unlike the latter condition, Table 5 shows that the numeri-cal optimization outcome results in a cutting speed andassist gas pressure values close to their respective middlevalues in the experimental domain (vC ¼ 20 m∕min andp ¼ 0.7 MPa, respectively) along with the highest level of

Fig. 4 Effect of assist gas pressure and cutting speed on RaLOW at f ¼ −1.5 mm.

Fig. 5 Effect of assist gas pressure and cutting speed on RaLOW at f ¼ −0.75 mm.

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focal position (f ¼ 0 mm). It allows achieving a very goodcut quality simultaneously reducing operating cost. A differ-ence of about 30% is found in the comparison between thebest experimental value (RaLOW ¼ 2.065 μm) and the resultreported in Table 5 (RaLOW ¼ 2.694 μm).

4.4 Cut Quality Assessment

The cut quality assessment according to ISO 9013 in terms ofu, reveals that the measured values of perpendicularity are inthe best class defined by the standard, indicated as range 1.Concerning the cut surface roughness tolerance fields intro-duced by the ISO 9013, range 1 of the Rz5 tolerance limitcorresponds to the best quality while range 4 correspondsto the worst quality. The cut quality assessment results are

reported in Fig. 9. It can be noted that for all the cutting con-ditions, fiber laser is able to produce cuts in the range of Rz5

that are included in the range 2. A comparison can be per-formed with cutting results obtained for 4-mm thick 5754 Alalloy using nitrogen as assist gas.21 In this case, most of thecuts are in the range 2 of the Rz5 tolerance limit and somepoints are in the range 1. This performance can be ascribed tothe values of assist gas pressure (up to 20 bar) and laserpower (4 kW). These are higher than the maximum valuesof p and PL, which it was possible to set in experimentaltests of this study.

In this work, the values of RaLOW between 4.61 and2.07 μm were measured in the range of cutting speedbetween 17 and 23 m∕min. The comparison with cut qualityresults of CO2 laser cutting reported in the literature shows

Fig. 6 Effect of assist gas pressure and cutting speed on RaLOW at f ¼ 0 mm.

Fig. 7 Effect of assist gas pressure and focal position on RaLOW at vC ¼ 20 m∕min.

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that CW mode significantly increases the cutting speed andallows obtaining superior quality as compared to PM.Cutting 2024 T3 3-mm thick sheets,3 roughness of about6 μm operating in CW and about 15 μm in PM wereobtained. This is valid for the optimum processing conditionsdetected by the authors that correspond to maximum cuttingspeeds of about 4.5 m∕min for CW mode (PL ¼ 3000 W)and 3 m∕min for PM (PL ¼ 2000 W). The comparison withNd:YAG laser in PM shows an average value of Ra equal to1.70 μm cutting a 0.7-mm-thick strain-hardened Al alloy(grade 40800) in optimized processing conditions (PL ¼200 W, vC ¼ 0.008 m∕min). Results obtained in this workconfirmed that a good cut quality is obtained with fiber lasersat much higher cutting speeds with respect to CO2 lasersoperating in CW but also to CO2 and Nd:YAG lasers inoperating PM. If compared with work by Riveiro et al.20 con-cerning laser cutting with fiber laser in CW, the results ofthis study are similar in terms of cut quality. In fact, cutting3-mm-thick 2024-T3 Al alloy at vC ¼ 4 m∕min andPL ¼ 4000 W, Ra was 1.5 and 4 μm in the upper andlower parts of cut edges, respectively.

5 ConclusionsThe following remarks can be made concerning the investi-gation on inert gas fusion cutting of 1-mm-thick Al 1050sheets with a 2-kW fiber laser source and the optimizationof cut quality and operating cost:

• The developed response surface model for RaLOW wasfound to be adequate. The regression coefficientsanalysis showed that only the linear effects of inputprocess parameters are significant for the model.The effects of cutting speed, assist gas pressure, andfocal position were established. The cutting speed isthe factor that plays a main role in affecting the RaLOW.

• The cut quality is reduced by decreasing assist gaspressure and by increasing cutting speed. Reliablecut results were obtained when the focal position is

Table 5 Optimal cutting condition as a solution of numerical optimi-zation by desirability method.

Cutting speed(m∕min)

Assist gaspressure (MPa)

Focalposition (mm)

RaLOW(μm) Desirability

19.151 0.640 0 2.694 0.78

Table 4 Optimization criteria.

Factor/response Goal Importance

Cutting speed Maximize 1

Assist gas pressure Minimize 1

Focal position Maximize 5

RaLOW Minimize 5

Fig. 8 Effect of focal position and cutting speed on RaLOW at p ¼ 0.7 MPa.

Fig. 9 Roughness classification in terms of mean height of the profileRz5 according to ISO 9013.

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set on the surface or within the distance equivalent tothe sheet thickness. In this condition, the maximumirradiance is obtained. In the range of explored param-eters, the best value of RaLOW (2.065 μm) wasmeasured for minimum value of cutting speed (vC ¼17 m∕min), focal position on surface (f ¼ 0 mm), andmaximum value of assist gas pressure (p ¼ 1 MPa).

• The simultaneous numerical optimization of cut qual-ity and operating cost, avoiding no-cut conditions,was performed by means of the desirability method.The optimal condition was calculated as cutting speedvC ¼ 19.151 m∕s, assist gas pressure p ¼ 0.649 MPa,and focal position set on the sheet surface f ¼ 0.The predicted value of RaLOW is about 30% higherthan the best value obtained by the experiments inthe whole process parameter window investigated.

• The cut quality assessment according to ISO 9013revealed values of perpendicularity in the best classdefined by the standard (range 1) and Rz5 valuesincluded in the range 2. Processing in CW with fiberlaser increases the cutting speeds and gives a cut qual-ity comparable with results reported in the literatureobtained with CO2 and Nd:YAG laser.

Supplementary experimental investigations increasing therange of main process parameters and in particular of laserpower and assist gas pressure are necessary. Furthermore, itis highly desirable to focus future studies on different alumi-num alloys and not only on pure aluminum. In particular,aspects related with the investigation of the effects of highthermal conductivity of aluminum alloys by measuring theHAZ extension, kerf width and changes in microstructureproduced by fiber laser cutting have to be investigated.

AcknowledgmentsThe authors express their gratitude to the “Regione Puglia”for the support to the present research activity throughthe constitution of the laboratory network TRASFORMAcod. 28.

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Leonardo Daniele Scintilla holds a PhD in advanced manufacturingsystems from Politecnico di Bari, Italy, focusing his research activityon inert gas fusion cutting with disk and fiber lasers. Since 2011, he isa research fellow at the Department of Mechanics, Mathematics andManagement (DMMM) of Politecnico di Bari. His present research isfocused on laser cutting and welding of lightweight alloy, mechanicaland technological characterization with digital image correlation tech-niques and HPDC process.

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Scintilla: Continuous-wave fiber laser cutting of aluminum thin sheets. . .