Polytechnic Department of Engineering and
Architecture
Doctorate School in
Industrial and Information Engineering
XXXI Cycle
-Doctoral Thesis
Research on Process Parameter
Optimization in Selective Laser Melting
Supervisor:
Candidate:
Prof. Marco Sortino
Dott. Emanuele Vaglio
Ringraziamenti
Questa tesi rappresenta solo una parte del bagaglio che viene da questi tre anni di studio, sperimentazione ed esperienza, per i quali vorrei dimostrare la mia gratitudine.
Ringrazio il Prof. Marco Sortino ed il Prof. Giovanni Totis per avermi dato l’opportunità di partecipare all’importante progetto che ha portato alla nascita del Laboratorio di Meccatronica Avanzata dell’Università di Udine, e per aver promosso e supportato con impegno e disponibilità la mia crescita scientifica, professionale e personale.
Ringrazio gli amici e colleghi Federico, Thomas e Christian, che hanno condiviso con me questo percorso, per gli stimolanti confronti e per i momenti di svago trascorsi insieme.
Grazie a mia mamma, a mio papà ed alle mie sorelle per il supporto e la fiducia incondizionata che mi hanno sempre dimostrato.
Infine, un ringraziamento speciale ad Alice, che mi ha spinto ad intraprendere il cammino percorso e che con amore è sempre stata al mio fianco.
Contents
Ringraziamenti i Abstract xvii Sommario xix 1 Additive Manufacturing 1 1.1 Introduction . . . 11.2 First developments of Additive Manufacturing . . . 2
1.2.1 Additive Manufacturing of metals . . . 4
1.3 The Selective Laser Melting technology . . . 7
1.3.1 The laser system . . . 8
1.3.2 The optical system . . . 14
1.4 The production plant . . . 24
1.4.1 Software equipment . . . 25
1.4.2 Hardware equipment . . . 29
2 The Selective Laser Melting process 53 2.1 Process parameters . . . 53
2.2 Interaction between laser beam and materials . . . 59
2.3 Physics of the molten pool . . . 61
2.4 Defectology of the SLM process . . . 67
2.4.1 Spattering . . . 68
2.4.2 Balling . . . 69
2.4.3 Porosity . . . 71
2.4.4 Residual stresses, deformations and cracks . . . 74
2.4.5 Other defects . . . 80
3 The Single track analysis 87 3.1 Introduction . . . 87
3.2 State of the art . . . 88
3.3 Single tracks formation through thin laser spot . . . 101
3.3.1 Tracks morphology . . . 104
3.3.2 Tracks width . . . 110
3.3.3 Tracks depth . . . 113
3.3.4 Tracks height . . . 116
3.3.5 Tracks connection angle . . . 118
4 From single tracks to solid parts 123
4.1 Introduction . . . 123
4.2 Solid part analysis . . . 129
4.2.1 Solid samples morphology . . . 133
4.2.2 Solid samples surface quality . . . 147
4.2.3 Dimensional precision and accuracy of the solid samples . 171 4.2.4 Process parameter optimization . . . 173
List of Figures
1.1 First development of Additive Manufacturing techniques with the systems of (a) Housholder (b) Kodama e (c) Hull. . . 4 1.2 Additive manufacturing technologies for metals: (a) Direct
En-ergy Deposition and (b) Powder Bed Fusion. . . 5 1.3 Schematization of the Selective Laser Melting process. . . 7 1.4 Interaction mechanisms between photons and electrons: (a)
ab-sorption (b) spontaneous emission and (c) stimulated emission. . 9 1.5 Scheme of the pumping process in a laser system: mechanism
with (a) three and (b) four levels. . . 10 1.6 Amplification and selection of the electromagnetic radiation in
the laser resonator. ©Encyclopaedia Britannica, Inc. . . 11 1.7 Geometry of a Gaussian laser beam [24]. . . 13 1.8 Focusing of the laser beam: (a) pre-focusing lens, (b) f-theta
objective, (c) dynamic pre-focusing and (d) combining dynamic pre-focusing with an f-theta objective. . . 15 1.9 Optical system for positioning the laser beam on the scanning
plane. ©SCANLAB GmbH. . . 16 1.10 Complete optical system, including beam shaping components,
beam positioning components and the controller. . . 16 1.11 Laser control signals. . . 17 1.12 The mark and jump vectors describe the laser trajectories during
the process. . . 18 1.13 Subdivision in microstep of a vector command. . . 18 1.14 (a) Burn-in and (b) shortening of the marked vector caused by
on delay too short and too long respectively. . . 19 1.15 (a) Deviation of the mark vector and (b) oscillations caused by
too small values of the mark delay and jump delay respectively. . 20 1.16 (a) Shortening of the marked segment and (b) burn-in caused by
too short and too long off delay respectively. . . 21 1.17 (a) Corner rounding and (b) burn-in caused by too short and too
long corner delay respectively. . . 21 1.18 Scan head and laser control during the scanning of (a) a jump
vector, (b) a mark vector and (c) two consecutive mark vectors.) 22 1.19 Conventional scanning head control: the acceleration is adjusted
on the base of the target speed in order to have a constant track-ing error.) . . . 23 1.20 Resolution parameters in the translation of a CAD model into
1.21 Concept Laser M2 Cusing machine. . . 30 1.22 Filtering module for the purification and recycling of the process
gas. . . 32 1.23 Particle size distribution of the AlSi10Mg powder used in the
experiment. . . 35 1.24 SEM image of (a), (b) the new and (c), (d) the recycled AlSi10Mg
powder. . . 36 1.25 Chemical composition of the recycled powder compared to that
of the new powder and the reference range according to DIN EN 1706. . . 37 1.26 Chamber furnace installed at the LAMA FVG Laboratory. . . . 40 1.27 (a) Operating principle of shot-peening and (b) typical trend of
residual stresses along the depth of the treated part. . . 41 1.28 Shot-peening machine installed at the LAMA FVG Laboratory. . 43 1.29 Otec ECO-Maxi tumbling machine installed at the LAMA FVG
Laboratory. . . 45 1.30 Haas VF-2TR machining center installed at the LAMA FVG
Lab-oratory. . . 46 1.31 (a) Bianco Mod. 370 M 60◦ sawing machine and (b) Comec RP
330 grinding machine installed at the LAMA FVG Laboratory. . 47 1.32 Argon storage and distribution system at the LAMA FVG. . . . 49 1.33 Box with controlled atmosphere for the installation of the SLM
machine and the complementary equipments. . . 51 2.1 Schematization of the exposure parameters. . . 54 2.2 Effect of the intensity of the laser beam on the SLM process. . . 54 2.3 Scanning strategy: (a) monodirectional, (b) bidirectional and (c)
with meander. . . 56 2.4 (a) Constant and (b) alternating Layer exposure. . . 56 2.5 Exposure strategy with rotated, alternated and traslated islands. 57 2.6 (a) Concordant and (b) discordant inert gas flow with respect to
the scanning speed [67]. . . 58 2.7 Absorption of the electromagnetic radiation as a function of the
wavelength for various metallic materials [68]. . . 59 2.8 Superficial defect caused by the perturbation of the liquid
mate-rial due to the pressure generated by the evaporation phenomenon [70]. . . 61 2.9 Molten pool evolution during the SLM process and solid track
formation. The liquid material is confined within the colored regions [72]. . . 63 2.10 Reconstruction of the thermofluidynamic behavior of the liquid
metal inside the molten pool [72]. . . 64 2.11 Formation, evolution and collapse of the depression region [72]. . 65 2.12 Types of convective flow generated by the Marangoni effect as
the relationship between surface tension and temperature varies: (a) negative gradient, (b) positive gradient and (c) gradient with a change of sign. . . 66 2.13 Contact angle and interaction forces between the solid, the liquid
2.14 Spatter formation due to the flows generated by the recoil pres-sure and the Marangoni effect [72]. . . 68 2.15 Onset of the balling effect as the scanning speed increases [77]. . 70 2.16 Porosity caused by too large values of (a) hatch distance and (b)
layer thickness. . . 71 2.17 Lack of fusion defects caused by the combination of too large
hatch distance and layer thickness with respect to the size of the molten pool [84]. . . 72 2.18 Pore formed in keyhole regime due to excessive energy supplied
to the material [85]. . . 73 2.19 Porosity caused by the presence of a spatter particle that interfere
with the coating process and the action of the laser beam. . . 73 2.20 (a) Temperature trend at the laser position and (b) material state
of stress during the exposure (stage 1), immediately after (stage 2) and when the thermal equilibrium is achieved (stage 3) [87]. . 75 2.21 Residual stresses trend (a) in the building platform and in the
produced part before their separation and (b) in the part after the separation from the building platform [88]. . . 76 2.22 Support structures tested for the manufacture of large parts: (a)
strip structures, (b) cylindrical structures and (c) reduced cylin-drical structures. . . 77 2.23 Particle size distribution of the Ti6Al4V ELI powder used in the
experiment. . . 78 2.24 Ti6Al4V ELI dog bone specimens produced with three different
support structures: (a) strip structures, (b) cylindrical structures and (c) reduced cylindrical structures. . . 79 2.25 Powder bed (a) before and (b) after the disturbance caused by
the displacement of the produced part during the process, and (c) failed binding of the layer to the solid substrate due to the formation of a thick powder layer. . . 80 2.26 Oxidation of 316L stainless steel parts caused by a periodic trend
of the oxygen content in the process chamber. . . 81 2.27 Semisolid material around the welding melt pool where hot
crack-ing occurs [90]. . . 82 2.28 Macro and microscopic view of (a), (c) solidification cracking and
(b), (d) liquation cracking in welding [90]. . . 83 2.29 (a) Staircase effect, (b) dross formation and (c) deformation
mech-anism of undercut surfaces due to thermal stress [93]. . . 84 3.1 (a) M2 process map and (b) H13 steel track cross-section obtained
through single track analysis [98]. . . 90 3.2 Top view of a single track and the surrounding region [79]. . . 91 3.3 Instability of single track from SS grade 316L at low scanning
speed (left) and high scanning speed (right) [79]. . . 91 3.4 Process map for the SS grade 316L [79]. . . 92 3.5 Process window for the AlSi10Mg alloy (a) with respect to tracks
3.7 classification of the Al-Cu-Mg tracks in (a) unstable, (b) stable with cracks and (c) stable without cracks [113]. . . 95 3.8 Effect of layer thickness on the quality of single tracks [77]. . . . 95 3.9 Classification of the 316L stainless steel tracks: (a) irregular and
preballing, (b) regular but occasionally broken, (c) regular and thin and (d) regular and thick [102]. . . 96 3.10 Process map for the Ti47Al2Cr2Nb alloy [111]. . . 98 3.11 Process map for the Ti6Al4V alloy [103]. . . 99 3.12 Ti6Al4V single tracks for different scanning speed: (a) v = 40mm/s,
(b) v = 60mm/s, (c) v = 80mm/s, (d) v = 100mm/s, (e) v = 120mm/s, (f) v = 140mm/s, (g) v = 160mm/s, (h) v = 180mm/s, (i) v = 200mm/s [107]. . . 100 3.13 Process map for the Ti6Al4V alloy [116]. . . 101 3.14 Characteristics of the powder used: (a) SEM view and (b)
gran-ulometric distribution. . . 102 3.15 (a) Design of Experiment and (b) manufactured specimens. . . . 104 3.16 Section line of the specimens used for the microstructural
char-acterization. . . 104 3.17 SEM view of the Ti6Al4V ELI alloy single tracks produced
vary-ing the laser power and the scannvary-ing speed. . . 105 3.18 SEM view of the cross-section of the Ti6Al4V ELI alloy single
tracks produced varying the laser power and the scanning speed. 106 3.19 (a) Classification of the Ti6Al4V ELI single tracks and (b)
pro-cess map for small laser spot diameter (d = 50µm) and thin layer thickness (t = 25µm). This figure obtained from the PhD research activity was included in [118]. . . 107 3.20 Characteristic defects of the single trace in correspondence for
mean LED values. This figure obtained from the PhD research activity was included in [118]. . . 108 3.21 Comparison between process parameters maps obtained with a
laser spot diameter of 50µm and 80µm (transparent green) [116]. This figure obtained from the PhD research activity was included in [118]. . . 110 3.22 Experimental width of the single tracks depending on (a) the laser
power and (b) the scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 111 3.23 Response surface describing the tracks width according to the
laser power and scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 112 3.24 (a) Residuals dispersion of the tracks width model and (b)
veri-fication of the residuals distributional normality. . . 112 3.25 Experimental depth of the single tracks depending on (a) the laser
power and (b) the scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 113 3.26 Response surface describing the tracks depth according to the
laser power and scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 114 3.27 (a) Residuals dispersion of the tracks depth model and (b)
3.28 Residuals of the tracks depth regressive model distribution com-pared to the normal distribution having mean and standard devi-ation equal to that of the analyzed sample: (a) probability density function and (b) cumulative distribution. . . 115 3.29 Distribution of the residuals of the model reconstructed excluding
the samples corresponding at the lower and higher LED levels. . 115 3.30 Experimental height of the single tracks depending on (a) the
laser power and (b) the scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 117 3.31 Response surface describing the tracks height according to the
laser power and scanning speed. This figure obtained from the PhD research activity was included in [118]. . . 118 3.32 (a) Residuals dispersion of the tracks height model and (b)
veri-fication of the residuals distributional normality. . . 118 3.33 Experimental connection angle of the single tracks depending on
(a) the laser power and (b) the scanning speed. This figure ob-tained from the PhD research activity was included in [118]. . . . 119 3.34 Response surface describing the tracks connection angle
accord-ing to the laser power and scannaccord-ing speed. This figure obtained from the PhD research activity was included in [118]. . . 120 3.35 (a) Residuals dispersion of the tracks connection angle model and
(b) verification of the residuals distributional normality. . . 120 3.36 Influence of the mutual position between the current track and
the underlying ones on the contact angle. . . 121 3.37 Microhardness profile along the tracks width for some process
condition. This figure obtained from the PhD research activity was included in [118]. . . 122 4.1 (a) Relative density and (b) average top surface roughness of
AlSi10Mg solid parts produced at different scan speed and laser power [101]. . . 124 4.2 Processing map for Al-Cu-Mg alloys multi-tracks [113]. . . 125 4.3 Multiple tracks produced with process parameters that generated
(a), (b) regular and thick single tracks and (c), (d) regular and thin single tracks. The applied overlapping rate is (a), (c) 30% and (b), (d) 10% [102]. . . 126 4.4 Density of the Ti47Al2Cr2Nb alloy samples produced with
pro-cess parameters within the propro-cess window identified through the single tracks experiment [111]. . . 127 4.5 Analysis of the porosity of the Ti6Al4V samples produced with
the process parameters within the process window identified through the single tracks experiment [107]. . . 128 4.6 Laser power-scanning speed combinations selected to compare the
characteristics of single tracks with those of solid parts produced with the same parameters. . . 130 4.7 Microscopic view of the powder used for the production of solid
specimens. . . 131 4.8 (a) Manufacture of the solid samples used for the analysis and
4.9 Measurement direction of the average roughness (a) on the up-per surface and (b) on the side surfaces. The reference system coincides with the SLM machine one. . . 132 4.10 Measurement direction of the sample size. The reference system
coincides with the SLM machine one. . . 133 4.11 View of the upper surface of the solid samples produced with the
continuous exposure strategy and a 20% overlapping rate. . . 134 4.12 View of the upper surface of the solid samples produced with the
continuous exposure strategy and a 30% overlapping rate. . . 134 4.13 View of the upper surface of the solid samples produced with the
islands exposure strategy and a 20% overlapping rate. . . 135 4.14 View of the upper surface of the solid samples produced with the
islands exposure strategy and a 30% overlapping rate. . . 135 4.15 Mesoscopic view of the upper surface of the solid samples
pro-duced with the continuous exposure strategy and a 20% overlap-ping rate. . . 136 4.16 Mesoscopic view of the upper surface of the solid samples
pro-duced with the continuous exposure strategy and a 30% overlap-ping rate. . . 136 4.17 Mesoscopic view of the upper surface of the solid samples
pro-duced with the islands exposure strategy and a 20% overlapping rate. . . 137 4.18 Mesoscopic view of the upper surface of the solid samples
pro-duced with the islands exposure strategy and a 30% overlapping rate. . . 137 4.19 Microscopic view of the upper surface of the solid samples
pro-duced with the continuous exposure strategy and a 20% overlap-ping rate. . . 138 4.20 Microscopic view of the upper surface of the solid samples
pro-duced with the continuous exposure strategy and a 30% overlap-ping rate. . . 138 4.21 Microscopic view of the upper surface of the solid samples
pro-duced with the islands exposure strategy and a 20% overlapping rate. . . 139 4.22 Microscopic view of the upper surface of the solid samples
pro-duced with the islands exposure strategy and a 30% overlapping rate. . . 139 4.23 Comparison between specimens produced with a laser power of
50W at different scaning speed levels. . . 140 4.24 Comparison between the surface quality of (a) the specimen
4.25 Classification of the morphology of the specimens produced with (a) the continuous exposure strategy and an overlapping rate of 20%, (b) the islands exposure strategy and an overlapping rate of 20%, (c) the continuous exposure strategy and an overlapping rate of 30%, and (d) the islands exposure strategy and an over-lapping rate of 30%. The dotted line highlights the defect-free class. . . 144 4.26 Single tracks morphology classification. . . 145 4.27 Evaluation of the presence of unmelted particles on the surfaces of
the specimens produced with (a) the continuous exposure strat-egy and an overlapping rate of 20%, (b) the islands exposure strategy and an overlapping rate of 20%, (c) the continuous expo-sure strategy and an overlapping rate of 30%, and (d) the islands exposure strategy and an overlapping rate of 30%. . . 146 4.28 Roughness average of the solid specimens upper surface
depend-ing on (a) the laser power, (b) the scanndepend-ing speed, (c) the hatch distance and (d) the exposure strategy. . . 148 4.29 Response surface describing upper surfce roughness according to
Equation 4.3. . . 149 4.30 (a) Dispersion of the residuals of the upper surfce roughness
model (Equation 4.3) and (b) verification of the residuals dis-tributional normality. . . 149 4.31 Comparison between the empirical probability density function
of the residuals and the corresponding theoretical curve calcu-lated on the basis of the mean and the standard deviation of the experimental data. . . 150 4.32 Response surface describing upper surfce roughness according to
Equation 4.4. . . 151 4.33 (a) Dispersion of the residuals of the upper surfce roughness
model developed starting from the exponential approach and in-cluding the scanning speed factor (Equation 4.4), and (b) verifi-cation of the residuals distributional normality. . . 151 4.34 Response surface describing upper surfce roughness according to
Equation 4.5. . . 152 4.35 (a) Dispersion of the residuals of the upper surfce roughness
model (Equation 4.5) and (b) verification of the residuals dis-tributional normality. . . 152 4.36 Response surface describing the upper surfce roughness of the
specimens produced with the islands exposure strategy according to Equation 4.6. . . 153 4.37 (a) Dispersion of the residuals of the upper surfce roughness
model (Equation 4.6) and (b) verification of the residuals dis-tributional normality. . . 153 4.38 Response surface describing the upper surfce roughness of the
specimens produced with the islands exposure strategy according to Equation 4.7. . . 154 4.39 (a) Dispersion of the residuals of the upper surfce roughness
4.40 Response surface describing the upper surfce roughness of the specimens produced with the islands exposure strategy according to Equation 4.8. . . 155 4.41 (a) Dispersion of the residuals of the upper surfce roughness
model (Equation 4.8) and (b) verification of the residuals dis-tributional normality. . . 155 4.42 Evaluation of the upper surface roughness of the specimens
pro-duced with (a) the continuous exposure strategy and an overlap-ping rate of 20%, (b) the islands exposure strategy and an over-lapping rate of 20%, (c) the continuous exposure strategy and an overlapping rate of 30%, and (d) the islands exposure strategy and an overlapping rate of 30%. . . 156 4.43 Roughness average of the upper surface of the specimens
pro-duced with (a) the continuous exposure strategy and (b) the is-lands exposure strategy according to the single tracks class. . . . 158 4.44 Roughness average of the solid specimens lateral surfaces
depend-ing on (a) the laser power, (b) the scanndepend-ing speed, (c) the hatch distance (d) the surface orientation with respect to the machine x axis and (d) the exposure strategy. . . 159 4.45 Response surface describing the roughness of the 45◦ oriented
lateral surface of the specimens produced with the continuous exposure strategy according to Equation 4.10. . . 160 4.46 (a) Dispersion of the residuals of the roughness model for the 45◦
oriented lateral surface (Equation 4.10) and (b) verification of the residuals distributional normality. . . 161 4.47 Comparison between the empirical probability density function
of the residuals and the corresponding theoretical curve calcu-lated on the basis of the mean and the standard deviation of the experimental data (Equation 4.10). . . 161 4.48 Response surface describing the roughness of the 135◦ oriented
lateral surface of the specimens produced with the continuous exposure strategy according to Equation 4.11. . . 162 4.49 (a) Dispersion of the residuals of the roughness model for the
135◦ oriented lateral surface (Equation 4.11) and (b) verification
of the residuals distributional normality. . . 162 4.50 Comparison between the empirical probability density function
of the residuals and the corresponding theoretical curve calcu-lated on the basis of the mean and the standard deviation of the experimental data (Equation 4.11). . . 163 4.51 Response surface describing the roughness of the 135◦ oriented
lateral surface of the specimens produced with the continuous exposure strategy according to Equation 4.12. . . 164 4.52 (a) Dispersion of the residuals of the roughness model for the
135◦ oriented lateral surface (Equation 4.12) and (b) verification
of the residuals distributional normality. . . 164 4.53 Response surface describing the roughness of the 45◦oriented
4.54 (a) Dispersion of the residuals of the roughness model for the 45◦
oriented lateral surface (Equation 4.13) and (b) verification of the residuals distributional normality. . . 165 4.55 Comparison between the empirical probability density function
of the residuals and the corresponding theoretical curve calcu-lated on the basis of the mean and the standard deviation of the experimental data (Equation 4.13). . . 166 4.56 Response surface describing the roughness of the 45◦oriented
lat-eral surface of the specimens produced with the islands exposure strategy according to Equation 4.14. . . 166 4.57 (a) Dispersion of the residuals of the roughness model for the 45◦
oriented lateral surface (Equation 4.14) and (b) verification of the residuals distributional normality. . . 167 4.58 Response surface describing the roughness of the 135◦ oriented
lateral surface of the specimens produced with the islands expo-sure strategy according to Equation 4.15. . . 167 4.59 (a) Dispersion of the residuals of the roughness model for the
135◦oriented lateral surface (Equation 4.15) and (b) verification
of the residuals distributional normality. . . 168 4.60 Evaluation of the 45◦ oriented surface roughness for the
speci-mens produced with (a) the continuous strategy and an overlap-ping rate O = 20%, (b) the islands strategy and O = 20%, (c) the continuous strategy and O = 30%, (d) the islands strategy and O = 30%. . . 169 4.61 Evaluation of the 135◦ oriented surface roughness for the
speci-mens produced with (a) the continuous strategy and an overlap-ping rate O = 20%, (b) the islands strategy and O = 20%, (c) the continuous strategy and O = 30%, (d) the islands strategy and O = 30%. . . 169 4.62 Roughness average of the 45◦ oriented surface of the specimens
produced with (a) the continuous and (c) the island sstrategy, and of the 135◦ oriented surface of the specimens produced with
(b) the continuous and (d) the islands strategy. . . 170 4.63 Lateral dimensional deviation of the solid specimens depending
on (a) the laser power, (b) the scanning speed, (c) the exposure strategy, (d) the hatch distance and (e) the surface orientation with respect to the machine x axis. . . 173 4.64 Process maps for the laser power and the scanning speed
opti-mization in the case of continuous exposure strategy and overlap-ping rate equal to 20% regarding (a) the geometrical morphology, (b) the formation of unmelted particles, (c) the upper surface roughness, (d) the roughness of the lateral surface oriented at 45◦ with respect to the machine x axis, and (e) the roughness of
the lateral surface oriented at 135◦ with respect to the machine
x axis. . . 178 4.65 Quality ratings of the parts produced by Selective Laser Melting
using small laser spot according to Equation 4.18. . . 182 4.66 Quality ratings of the parts produced by Selective Laser Melting
4.67 Flowchart of the process parameter optimization method. 1.5cm threshold is three times the standard dimension of the elementary cell in the islands strategy. . . 183 4.68 General flowchart for the process parameters optimization in
List of Tables
1.1 Initial chemical composition of the AlSi10Mg powder used in the
experiment. . . 35
2.1 Chemical composition of the Ti6Al4V ELI powder used in the experiment. . . 78
2.2 Process parameter used to process Ti6Al4V ELI specimens. . . . 78
3.1 State of the art of experimental process parameters optimization. 89 3.2 Chemical composition of the Ti6Al4V ELI powder used in the single tracks analysis. . . 102
3.3 Process parameter used for the manufacture of the substrate on which the Ti6Al4V ELI single tracks were produced. . . 103
3.4 Analysis of variance of the tracks width data. . . 110
3.5 Analysis of variance of the tracks depth data. . . 114
3.6 Analysis of variance of the tracks height data. . . 116
3.7 Analysis of variance of the tracks connection angle data. . . 119
4.1 Chemical composition of the Ti6Al4V ELI powder used for the solid samples production. . . 130
4.2 Analysis of variance of the horizontal surface mean roughness Ra data. . . 147
4.3 Analysis of variance of the lateral surfaces mean roughness Ra data. . . 160
4.4 Analysis of variance of the lateral dimensional deviation data. . . 172
4.5 Statistical models for the dimensional compensation of solid parts.173 5.1 Statistical models describing the geometrical characteristics of the single tracks. . . 188
5.2 Statistical models describing the surfasce roughness of the 3D samples. . . 190
5.3 Statistical models for the dimensional compensation of solid parts.190 5.4 Optimal parameters to process Ti6Al4V ELI titanium alloy with small laser spot. . . 191
Abstract
“You cannot teach a man anything; you can only help him discover it in himself.”
Galileo Galilei
In this work the process optimization of the Selective Laser Melting tech-nology has been investigated in order to develop a systematic multiobjective method for the process parameters selection. Without limiting the generality, the study has been conducted on the Ti6Al4V ELI titanium alloy, and given the particular suitability of the SLM technique for the production of small parts characterized by detailed features, the condition selected to develop and test the general methodology for process parameters optimization is characterized by a small laser spot of 50µm of diameter and a thin layer thickness of 25µm.
In order to pursue the objective set, an experimental analysis of the sin-gle scan tracks has been firstly performed according to the full factorial ap-proach, varying the laser power on 8 equidistant levels in the range between 50W and 400W , and the scan speed on 10 equidistant levels in the range be-tween 250mm/s to 2500mm/s. Unlike other similar studies, in which the tracks have been scanned on a premachined base, in this work it was decided to resort to the use of a substrate consisting of bases produced during the same process in which the tracks were scanned in order to reproduce as closely as possible the conditions that occur during production. The specimens obtained have been then classified from the morphological point of view identifying five classes rep-resentative of the track shape and of the melting quality in the case of the single scan, and have been analyzed by means of a scanning electron microscope for studying and modeling the geometrical characteristics of the tracks such as the width, the height, the depth and the contact angle with respect to the solid substrate as the laser power and the scanning speed vary.
On the basis of the results obtained in the first phase, the most promising region of the explored factorial plan has been then selected, and a further exper-imental campaign focused on the analysis of solid samples has been conducted. This time also the overlapping rate between the tracks and the scanning strat-egy have been included as factors. More precisely, the former was varied on two levels, corresponding to 20% and 30% of the measured single track width, while the latter was considered distinguishing between continuous exposure strategy and islands exposure strategy. In this way it was possible to define the appli-cable criteria for the evaluation of the products quality and to determine the influencing factors related to them, to elaborate a systematic method for the analysis and the classification of the samples used for the optimization, and to
Sommario
“Non puoi insegnare qualcosa ad un uomo. Lo puoi solo aiutare a scoprirla dentro di sé.”
Galileo Galilei
In questa tesi è stato trattato il tema dell’ottimizzazione di processo della tecnologia Selective Laser Melting con il fine di elaborare un metodo sistematico multiobiettivo per la selezione dei parametri di processo. Pur senza voler perdere in generalità, lo studio è stato condotto sulla lega di titanio Ti6Al4V ELI, e data la particolare idoneità della tecnologia SLM per la produzione di parti piccole caratterizzate da feature dettagliate, la metodologia in oggetto è stata sviluppata e testata in condizioni caratterizzate da uno spot del laser di piccole dimensioni, ovvero di diametro pari a 50µm, e ridotto spessore dei layer, pari a 25µm.
Al fine di perseguire l’obiettivo prefissato è stato dapprima eseguito uno stu-dio della singola traccia fusa secondo l’approccio sperimentale fattoriale, facendo variare la potenza del laser su 8 livelli equidistanziati nell’intervallo compreso tra 50W e 400W , e la velocità di scansione su 10 livelli equidistanziati nell’inter-vallo compreso tra 250mm/s e 2500mm/s. A differenza di altri studi analoghi, nei quali le tracce sono state prodotte su una base prelavorata, in questo la-voro è stato scelto di ricorrere all’impiego di un sottostrato costituito da basi prodotte nel corso dello stesso processo in cui sono state scansionate le trac-ce in modo da riprodurre quanto più fedelmente possibile le condizioni che si verificano durante la lavorazione. I provini così ottenuti sono stati classificati dal punto di vista morfologico individuando cinque classi rappresentative della conformazione e della qualità della fusione riferita alla singola scansione, e sono stati analizzati mediante microscopio elettronico a scansione per studiare le ca-ratteristiche geometriche delle tracce, quali la larghezza, l’altezza, la profondità e l’angolo di contatto con il sottostrato solido, ed elaborare i modelli statistici che le descrivono al variare della potenza del laser e della velocità di scansione. Sulla base dei risultati ottenuti nella prima fase è stata dunque seleziona-ta la regione del piano fattoriale esplorato qualiseleziona-tativamente più promettente, ed è stata condotta un’ulteriore campagna sperimentale incentrata sull’analisi di campioni solidi, nella quale sono stati inclusi come fattori anche il tasso di sovrapposizione tra le tracce e la strategia di scansione. Più precisamente, il primo è stato fatto variare su due livelli, corrispondenti al 20% ed al 30% della larghezza misurata della traccia fusa, mentre il secondo è stato incluso distin-guendo tra strategia di scansione continua e strategia di scansione ad isole. In questo modo è stato possibile definire dei criteri applicabili per la valutazione
Additive Manufacturing
“Others dream of things that were, and ask ’Why?’ I dream of things that never were, and ask ’Why not?” ’
Cardinal Saint-Saens
1.1
Introduction
The global competition and the progress of the innovation process in various industrial sectors are imposing to engineering companies to focus on products with high added value and capable of performing advanced functions often re-sisting to aggressive working environments. To meet these requirements it is necessary to combine excellent physical and mechanical properties with complex geometry and very tight dimensional tolerances, hampered by the low machin-ability of the latest generation materials using conventional methods as well as by several factors that intervene in the manufacturing processes such as inac-curacy of the machine, thermal expansion, mechanical deformations, vibrations and others. In order to strengthen the business competitiveness, the scenario described above must also be placed in the context of streamlining the pro-duction processes which is leading more and more companies to move towards the philosophy of lean production, accompanied by an ever deeper computeriza-tion of the produccomputeriza-tion systems especially geared towards optimizing produccomputeriza-tion cycles and processes automation. At the same time the sustainability of man-ufacturing production and the reduction of its environmental impact represent today a primary objective.
As a result, more than a century after Henry Ford pronounced the famous sentence “a customer can have a car painted any color he wants as long as it’s black” we are witnessing a drastic revolution in the manufacturing logic that is marking the advent of a new industrial era. This breakthrough is based on the digitalization of the production systems and it is aimed at the extreme product customization. The additive manufacturing technologies are a cornerstone of this renewal thanks to the possibility to produce high quality products with exceptional design freedom. Among the techniques currently available, the Se-lective Laser Melting (SLM) technology stands out for its ability to process metallic materials. SLM printed parts are characterized by density extremely
close to the theoretical one, excellent mechanical characteristics, and good sur-face finishing. Thanks to these peculiarities, this technology allows to satisfy the most daring needs of industry and have revolutionary potential application in strategic fields, from aviation and aerospace to medicine.
However there are still many obstacles to the widespread diffusion of this technology, first of all the costs and the long processing time, but also the lim-ited knowledge of the phenomenology of the process and of how it is influenced by the controllable process parameters such as the laser power, the scanning speed, the laser spot size, the overlapping rate between successive tracks, and the layer thickness, but also other factors involved in the process such as the characteristics of the powders or the operating conditions in the building cham-ber.
Optimization approaches met in literature can be divided into analytical, numerical and empirical methods. The first are based on simplified mathemat-ical models of process physics. Nevertheless, the reliability of analytmathemat-ical models predictions is generally low due to the high complexity of process physics, that cannot be adequately described by simple models. The numerical approach requires instead less simplifications and assumptions, leading to more realistic predictions. Nevertheless, numerical methods need further developments since also them have not been proven capable of reproducing the physics of the pro-cess in a sufficiently reliable way. Finally, empirical methods are based on direct evaluation of SLM results by varying process parameters according to a given Design of Experiments. In literature numerous experimental studies can be found, but most of them have been oriented towards the analysis of the single scan tracks that greatly simplifies the problem but is not very representative of the process due to the fact that it does not take into account the thermody-namic evolution that occurs in the material when multiple tracks are scanned next to each other. In any case, none of the followed paths has allowed so far the development of general and effective guidelines for an optimal choice of process parameters for obtaining high quality products. For this reason, the de-velopment of a systematic multiobjective method for the process optimization has been pursued in this work. Without loss of generality, the study will be conducted on the Ti6Al4V ELI titanium alloy. Another target was the achieve-ment of finer dimensional resolution of the 3D printed parts. This property is of particular interest for the production of small parts characterized by detailed features that often give the product the added value that justifies the use of this technology for production. Consider for example the trabecular structures in the biomedical sector, the features that compose the aerospace components, or the ducts and the thin walls applied to the heat exchangers or to the conformal cooling channels.
1.2
First developments of Additive
Manufactur-ing
for the metallic materials.
The term Additive Manufacturing includes all the technologies that build 3D objects by adding successive material layers, as opposed to the conventional subtractive manufacturing methodologies. As reported by Bourell et al. [1], The first attempts to exploit the layer by layer fabrication date back to 1890, when J. E. Blanther filed a patent for the manufacture of contour relief-maps at the United State Patent Office [2]. The process involved the preparation of a series of wax plates shaped according to the level curves of the area to be mapped. By superimposing these plates it is possible to obtain a mold and a counter-mold that represent the topography of the considered region, and they can be used to press between them the paper map giving it the three-dimensional conformation In the following years there have been several evolutions of this method, including the adoption of milling for the contouring of metal sheets proposed by DiMatteo [3], and the application of lamination [4] and laser cutting [5] tech-niques by Nakagawa, but it is in 1951 that Munz proposes the use of a photo emulsion which, if exposed to appropriate light, solidifies by incorporating an image of the scanned object [6]. The solid produced can then be carved or etched in order to obtain a three-dimensional part. In 1968 Swainson proposed a method for the photopolymerization of plastic materials by means of a laser [7], and two years later Ciraud describes for the first time a three-dimensional manufacturing method based on the use of appropriate powder materials and an addressable energy source, represented by a laser, an electron beam or a plasma beam, that at least partially melting the particles determines their union [8]. The powder material is supplied by gravity, by means of electric or magnetic fields, or through a special nozzle. This concept will be taken up later for the development of modern Direct Energy Deposition technologies. In 1979, Housholder filed a patent for the processing of powdered materials through the deposition of successive layers selectively solidified by means of a scanning sys-tem or the use of a heat source controlled with the apposition of suitable jigs. Two years later, Kodama describes the first system for additively processing polymers through UV exposure [10], preceding the patent of Charles Hull [11] of 1986 in which he presents a manufacturing method in which an ultraviolet concentrated light is focused on a surface of a tank filled with liquid photopoly-mer. The light, moved by a computer, draws each layer of the object on the liquid surface, which hardens and cures. Hull calls this technology stereolithog-raphy, and soon will found 3D Systems, the first company that commercialize Additive Manufacturing technologies (Figure 1.1).
(a) (b) (c)
Figure 1.1: First development of Additive Manufacturing techniques with the systems of (a) Housholder (b) Kodama e (c) Hull.
binders obtained by mixing the ink in special cartridges, this technology allows to realize colored parts with over 6 million colors. In those same years, great interest is addressed toward the possibility of processing metallic materials, and many efforts were put into the development of Selective Laser Melting (SLM), Electron Beam Melting (EBM) and Direct Metal Deposition (DMD) processes, presented in 1999, in 2000 and 2002 respectively, outlining the modern subdi-vision of metal AM technologies into two basic categories: Powder Bed Fusione (PBF) systems and Direct Energy Deposition (DED) systems.
The following years were characterized by the development of numerous low cost solutions, which promoted the diffusion of additive technologies, and the optimization of industrial systems from many points of view: from the increase in productivity through the use of multiple and more powerful energy sources to the possibility of using larger build volumes, from the monitoring and con-trol of the process to the development of new materials. At the same time, the diffusion of AM promoted the evolution and the renewal of numerous comple-mentary tools to production technologies, from Computer Aided Design (CAD) and topological optimization software to 3D scanning, image acquisition and reverse engineering equipment.
Nowadays additive manufacturing represents a concrete and performing al-ternative to traditional production, as well as an important opportunity to make the production more sustainable in terms of costs, energy, and CO2
emis-sions [13]. Its ability to combine excellent physical and mechanical properties with highly accurate and complex geometries allows to satisfy the most preten-tious needs of industry, and also supports previously unthinkable ambitions in the most disparate fields, from aviation and aerospace to medicine thanks to the great flexibility and the possibility to realize not only on-site and in response to actual demand but also unique and customized products.
1.2.1
Additive Manufacturing of metals
In the first development phase, additive technologies were able to process only plastic materials, achieving rather poor resolution and finishing results. Therefore, 3D printing was mainly used for rapid prototyping, i.e. the fabrica-tion of models in order to facilitate the design phase and the assessment of costs, cycle times and market response to new products. At that time, technology was rare and expensive, and only large companies had access to it.
(a) (b)
Figure 1.2: Additive manufacturing technologies for metals: (a) Direct Energy Depo-sition and (b) Powder Bed Fusion.
reduction of equipment costs and, at the same time, to a considerable improve-ment in the production quality. In the second half of the 1990s, the introduction of heat-resistant polymers and metal alloys marked the advent of the so-called Rapid Tooling (RT), context in which 3D printing is used for the production of equipment and complementary tools for traditional production: brackets, jigs, dies, molds and cores, which are traditionally produced through long and costly processes, in which any errors is difficultly managed. 3D printing has had a major impact on the design freedom of these components, and has reduced time and cost for their manufacture, encouraging the targeted production of tailored products. This generated new opportunities for previously excluded market segments and expanded those of the already involved sectors through the opti-mization of production processes, e.g. by means of the application of conformal cooling channels, which improve not only productivity, but also production cost due to the longer life of the mold, and the quality of the produced part.
However, the definitive turning point came in the 2000s, when the additive technologies reached a maturity level enabling the manufacture at competitive costs of products with geometric, dimensional, mechanical and finishing char-acteristics of the finished products [14]. This evolution is guided by the metal materials sector, which includes large industrial players from the main sectors interested in the peculiarities offered by the AM: aeronautics and aerospece, biomedical, and automotive. According to the F2792 standard defined by the American Society for Testing and Materials (ASTM) [15], it is possible to divide the most widespread AM processes for metals into two categories: Direct Energy Deposition (DED) technologies, and Powder Bed Fusion (PBF) technologies.
performed by the part, by the nozzle, or by a combination thereof. Due to their peculiarities, this class of technologies is characterized by rather large build vol-ume, but limited dimensional precision and accuracy, as well as rough surface finishing. The main fields of application are the aeronautical and aerospace, medical, oil and gas and industrial sectors for the production and repair of mechanical components, possibly even multi-material [17]. DED technologies include powder-based feedstock systems, such as Laser Engineered Net Shaping (LENS), Direct Metal Deposition (DMD) and Laser Metal Deposition (LMD) [18], and wire-based feedstock systems, such as Electron Beam Direct Manu-facturing (EBDM) and Wire Arc Additive ManuManu-facturing (WAAM), the latter available in the gas metal arc welding (GMAW), the gas tungsten arc welding (GTAW) and the plasma arc welding (PAW) versions, which are distinguished from each other by the heat source type [19].
In PBF systems instead the exposure of the material to the energy source is preceded by the deposition of a thin layer of powder on the build area. Sub-sequently a laser or an electron beam selectively scans the material, melting or sintering it. In the case of electron beam technologies, which are limited to the use of electrically conductive materials, the exposure takes place in two steps, with a first light sintering of the powder layer to prevent the particles from charging electrostatically and, consequently, to reject each other, and a second exposure to melt the area that will form the part. Being the material presintered and typically maintained at high temperature, electron beam technologies allow to achieve higher scanning speeds. During the process the molten material is protected from oxidation through the inertization of the process chamber in the case of laser systems, or through the creation of vacuum in the case of electron beam technologies. At the end of the exposure a new powder layer is deposited, and the process is repeated until completed. Powder bed processes are char-acterized by a lower production rate due to the passive time required for the material deposition, the reduced thickness of the layers and the low scanning speed. This, together with the intrinsic necessity of having a large quantity of material for the execution of a process, normally determines a smaller build vol-ume, which limits the size of the parts that can be produced. On the other hand, powder bed processes are characterized by greater precision and accuracy, that is why they are of great interest in the aeronautical, aerospace and biomedical sectors for the production of functional parts and prototypes, and, in the case of laser technologies, for the production of heat exchangers and tools [20]. In the framework of the metal materials processing, the technologies belonging to this group are Electron Beam Melting (EBM), Selective Laser Sintering (SLS) and Selective Laser Melting (SLM), which will be the object of this research and, therefore, will be deepened during the thesis.
Figure 1.3: Schematization of the Selective Laser Melting process.
obtained with this technique have an excellent surface quality, they are charac-terized by poor mechanical characteristics and may be affected by considerable dimensional inaccuracy due to non-uniform shrinkage caused by sintering or infiltration. For these reasons, binder jetting is not suitable for high-end appli-cations, but has anyway considerable applicability in other market segments.
1.3
The Selective Laser Melting technology
chamber in order to take the material from the powder compartment and de-posit it on the surface of the building compartment, forming layers of thickness comprised between 20 and 100µm. The exceeding material, which is moved in order to compensate the volumetric shrinkage that occurs due to the powder melting, is collected in a third compartment, called overflow, so that it can be sieved by external or integrated device into the SLM machine and reused. A fiber laser with power usually between 100 and 1000W generates a laser beam that is uniquely focused, in the case the optical scanning system adopts either a static or a dynamic focusing unit, or focused based on the set parameters, in the case both these components are used, and deflected along the programmed scannig path by a two-mirror galvanometric scanner.
Once the set-up of the machine has been completed through the loading of the powder material, the mounting of the building platform and of the blade recoating, and the execution of the axis reference, the process can be started, and will proceed repetitively through the steps of depositing a powder layer, selectively scanning the layer by means of the laser beam, lowering the build-ing compartment and simultaneously raisbuild-ing of the powder compartment, and depositing the next layer. At the end of the production process, which can last several days, all the powder material that has not been melted by the laser is removed by the operator, which puts it in the overflow compartment so that it can be restored and reused, and the part is extracted still attached to the building platform.
The as-built products has features that will be further explored later, and which strongly depend on the processed material, the quality of the powders used, the process parameters, the type of SLM machine used, and the compo-sition and characteristics of the processed job. In general it can be said that the product resulting from the SLM process is characterized by high density, typically higher than the 99% the theoretical density of the material, by a di-mensional precision and acccuracy of the order of the tenth of a millimeter, and by a surface finishing characterized by a mean roughness typically included be-tween 5 and 20µm. From a mechanical point of view, the behavior of a product is strongly influenced by the microstructure and, therefore, the thermal history of the material that composes it. In general, the SLM processed materials are strongly anisotropic and stressed by the thermal tensions accumulated during the production process. Their static mechanical characteristics are comparable with those of the materials obtained from traditional processes, while the fatigue behavior is strongly influenced by the surface roughness and the presence of in-ternal defects in the part. It follows that often the production process must be followed by a more or less onerous phase of post-processing aimed at achieving the desired quality of the part.
1.3.1
The laser system
The laser system is the heart of the production process as it provides energy with optimal characteristics for the material melting and the part construction. Compared to electron beam technologies, the use of laser as an energy source allows great flexibility in terms of processable materials.
(a) (b) (c)
Figure 1.4: Interaction mechanisms between photons and electrons: (a) absorption (b) spontaneous emission and (c) stimulated emission.
system as well as stimulate its de-energization. Considering an atom consisting of a nucleus of protons and neutrons surrounded by electrons lying on discrete orbital shells, the electrons move between different energy levels, corresponding to the orbital shells, absorbing and emitting corresponding energy quanta in the form of photons. As described in Figure 1.4, there are three types of interactions between electrons and energy photons [22]:
• Absorption: a photon comes across an electron with a low energy level that absorbs it moving to a higher energy level;
• Spontaneous emission: an electron with a high energetic level decays spon-taneously to a lower energy level emitting a photon with energy equivalent to the difference between the energy levels involved and with random direc-tion and phase. The time required for an electron to decay spontaneously is called lifetime, and depends on the atom species and the starting energy level.
• Stimulated emission: a photon comes across an electron with a high energy level causing its decay associated with the emission of a second photon with direction, phase and wavelength indentical to those of the incident photon.
Regardless of the material, under normal conditions almost all the atoms of a medium are in the minimum energy state. The probability that a photon causes either stimulated emission or absorption are given by the percentage of atoms excited against that of atoms in the base energy state, and therefore normally the light passing through a material is absorbed by the material itself. However, if we intervene by exciting the atoms of the material with an external energy source realizing the population inversion condition, in which the atoms with a high energy level are more numerous than atoms in the base energy state, the emission process will dominate, and the light in the system will increase. The atoms excitation process is called pumping, and when it leads to the occurrence of the described condition, it is possible to exploit a photon produced by spon-taneous emission as a trigger for a series of stimulated emissions that lead to the formation of identical photons, making the light beam produced possess the following properties:
(a)
(b)
Figure 1.5: Scheme of the pumping process in a laser system: mechanism with (a) three and (b) four levels.
• Time coherence: the electromagnetic waves keep the same phase over time, giving a monochromatic beam;
Moreover, under normal conditions it is impossible to achieve population in-version in a system in which there are only two possible energy states for the atoms, since the probability that the transition from one energy state to another occurs is the same in both directions, and the maximum we could get would be a draw. Considering instead a three-level system in which the higher energy level, called pump level, is characterized by a lifetime shorter than that of the intermediate level, therefore called metastable, we would obtain that pumping electrons from the base energy level to the pump level, these would quickly decay on the intermediate level where they would accumulate, realizing the population inversion between the intermediate and the base level. However this solution is not very efficient, and requires a very high pumping effort. For this reason the most widespread solution is the four-level one, characterized by a rapid decay between the pump and the third level, a metastable behavior of the latter, and a new rapid decay between the second and the base level. In this case there will be, in fact, the rapid emptying of the second level, facilitating the occurrence of the population inversion with the metastable level (Fig. 1.5) [23].
Figure 1.6: Amplification and selection of the electromagnetic radiation in the laser resonator. ©Encyclopaedia Britannica, Inc.
medium, the pumping system, and the optical cavity or resonator. The active medium is the material that emits photons when activated. Depending on the type of laser, the active medium can be a liquid, a gas or a solid, and its properties determine the emission wavelength. The pumping system is the component that supplies energy to the active medium bringing it to an excited state. Pumping can be electric or optical using flash lamps or diodes. Finally, the optical cavity is the element that amplifies the radiation and selects it on the base of frequency, direction and coherence. It consists of two mutually opposite mirrors between which the active medium is placed. Between these two mirrors the photons are reflected in both directions at the speed of light, thus passing through the active medium several times. In this way, an optical amplifier is obtained. In order for the system to work, it is necessary that the distance L between the two opposing mirrors is exactly an integer multiple of the half-wavelength of the radiation generated by stimulated emission. Furthermore, to allow the beam to leave the cavity, a mirror is partially permeable to the corresponding wavelength. In this way, only those rays that are reflected in a perfectly parallel way leave the laser in the form of coherent light (Fig. 1.6).
high-speed scanning applications. Continuous operation requires that the population inversion is constantly implemented by a pumping source. In some media this is impossible, while in others it would require such intense pumping as to be disadvantageous. In impulsive lasers, instead, the power is concentrated in the form of pulses of a certain duration and repetition rate. A peculiar character-istic of the pulsed regime is that, with the same average power generated by the source, very high peak power is obtained. The pulsed emission is in fact characterized by bringing the population inversion in the active medium to very high levels while preventing the laser action. Subsequently, in a very short time, the amplification and propagation of the beam is allowed, obtaining high peak powers (with an order of magnitude of megawatts). On the other hand, the bandwidth of a pulse can not be shorter than the reciprocal of the duration of the pulse, therefore, for particularly short pulses we find considerably large bandwidths in contrast to the typical narrow bandwidths of CW lasers. De-pending on the application, there may be required high energy pulses, in which case the emission rate is lowered so as to allow the accumulation of a greater quantity of energy, or pulses with high peak power, obtainable by generating very short emissions. Obviously a CW laser can be turned on and off in order to obtain a series of pulses. In this case the modulation rate is much slower, on a time scale, with respect to both the average life of the radiation in the optical cavity and the period in which energy can be stored in the active medium, and they are called modulated CW lasers.
A particularly widespread modulation technique is the so-called Q-Switching, which takes its name from the Q factor, a parameter that expresses the quality of the resonant cavities. It consists in the introduction inside the optical res-onator of a controllable attenuator that prevents the light that leaves the active medium to go back and, therefore, to be amplified. Thus, the attenuator allows the occurrence of the population inversion without laser emission since the res-onator amplification is missing. The energy stored in the medium increases with time, but due to the energy losses that occur in it, e.g. spontaneous emission, the amount of stored energy will reach a maximum level, called saturation. At this point the device quickly changes the Q factor from low to high by deactivat-ing the attenuator, allowdeactivat-ing the resonator to perform the optical amplification through stimulated emission. Because of the large amount of energy already stored in the medium, the intensity of light increases very quickly, and, conse-quently, there is an equally rapid emptying of energy. A short light pulse with very high peak power is generated as the net result of the operation. The same result can be obtained with a passive attenuator, that is a saturable absorber whose capability to transmit the radiation increases when the intensity of the light exceeds a certain threshold, generating the discharge of the accumulated energy. In this case, however, it is evident that the frequency of the pulses can be controlled only indirectly through the amount of absorbent material present in the cavity and the power of the external pumping source. The Q-switching technique is characterized by a lower pulse frequency compared to the proper pulsed lasers, but the pulses have higher energy and longer duration.
The physical quantities that allow to characterize the laser beam are the following:
Figure 1.7: Geometry of a Gaussian laser beam [24].
• Fluency (F ): defined as F = E/S, is the energy density with respect to the section S of the beam. It takes into account the total energy supplied, and is usually used to characterize the pulsed lasers;
• Irradiance (H): defined as H = P/S, is the power density again with respect to the section S of the beam.
The irradiance of a laser beam is not constant through its section, but has a spatial distribution determined by the dimensions and geometry of the optical cavity. In fact, by varying the geometry of the mirrors it is possible to concen-trate the power density on the beam axis or distribute it along its section. The most important distribution is certainly the Gaussian one, in which most of the power density is in the innermost region of the beam. One way to character-ize the spatial distribution of power density is the Transverse Electromagnetic Mode (TEM). It provides the beam classification through the code T EMmn,
where m and n represent the number of power density minimums in the beam section along the radial and circumferential direction respectively. For example, T EM00 indicates a beam whose spatial profile has no minimums and a single
maximum centered in the origin of the axes, corresponding to the Gaussian dis-tribution. There are also laser sources that can generate beams with multiple overlaid T EMmn modes. In this case they are called multi-mode lasers,
distin-guishing them from single-mode lasers. The latter produce a high-quality beam, while the former can reach typically higher powers.
For what concerns the geometry of a laser beam, it can be approximately considered convergent-divergent as schematized in Figure 1.7 [24]. The point where the beam diameter assumes the minimum value w0 is called focus, while
the region around it within which the beam can propagate without significantly diverging is defined by the Rayleigh length:
z0=πw0
2
λ , (1.1)
where λ is the wavelength of the radiation. The beam radius varies along the propagation direction according to the following equation:
w(z) = w0·
r 1 +zz0
2
, (1.2)
while the transverse profile of the optical intensity of the beam with a power P can be described with the Gaussian function:
The divergence half-angle Θ depends on constructive factors, and is given by the following equation:
Θ = λ
πw0. (1.4)
It can be shown that a Gaussian beam is the one that has minimal divergence, and any real laser has divergence always greater than this limit value, i.e. the beam generated by a real laser is never exactly Gaussian. To evaluate the quality of a beam we introduce the M2 index, which represents the ratio between the
actual and the ideal divergence. When M2 tends towards one, the intensity
tends to the Gaussian distribution.
Depending on the application, the desired laser properties change consider-ably. In general, the interaction between laser beam and material is strongly influenced by the absorption coefficient that will depend, in turn, on the wave-length of the incident radiation. Among the most common lasers for tradi-tional applications we mention the CO2 lasers, the Nd:YAG lasers, and the
fiber lasers. The former are lasers with a gaseous active medium, consisting of a mixture of carbon dioxide, nitrogen, hydrogen and possibly other gases elec-trically pumped. With a wavelength of 10.6µm, they are particularly suitable for processing non-metallic materials and plastics, and do not allow the use of optical fibers and lenses for beam transport and focusing, so they are therefore replaced by metal mirrors. These are more easily cooled, and lend themselves better to high power applications. The focus spot can achieve 250µm in diam-eter. The Nd:YAG lasers instead use a solid active medium, the neodymium-doped yttrium-aluminum garnet pumped by diode. They are characterized by a wavelength of 1064µm, which makes them suitable for metal processing, but are affected by wear and overheating of the active medium, which therefore tends to deform and thus compromise the quality of the generated beam. Finally, fiber lasers exploit the core of an appropriately doped optical fiber as an active medium. The pumping is by diodes and the energy is directed into the coating between the actual core and the reflective sheath that surrounds the fiber. In this way the exciting radiation repeatedly passes through the active medium due to successive reflections, giving rise to the laser beam. The primary dopants are erbium, which determines a wavelength between 1530µm and 1620µm, which is an eye-safe wavelength range, and ytterbium, that has center wavelengths rang-ing from about 1030µm to 1080µm, which is compatible with interaction with metals. Fiber lasers allow for an extremely small focal diameter and very high pulse frequencies. They also stand out for the quality of the produced beam and their efficiency, low maintenance costs and high endurance.
1.3.2
The optical system
The light beam emitted by the laser must be directed towards the build-ing plane and moved to selectively scan the area to be melted. In this phase the beam can be subjected to the action of additional tools that modify its properties according to the process needs. The optical systems that perform these functions are essentially composed of beam shaping components, beam positioning components and a controller.
dy-Figure 1.8: Focusing of the laser beam: (a) pre-focusing lens, (b) f-theta objective, (c) dynamic pre-focusing and (d) combining dynamic pre-focusing with an f-theta objective.
namic and static focusing performed before and after the deflection, respectively. Rejecting the solution with pre-focusing lens, with which a curved image field is obtained, the first possibility is represented by the use of a flat-field scanning lens, which is able to focus a collimated beam, independently of the imposed deflection from the scanning system, maintaining a flat image field. However, with this type of lens, the beam shift is given by the product between the focal length f and the tangent of the deflection angle, which is a nonlinear quantity that complicates the scan rate control. For this reason, instead of the flat-field scanning lenses, F-Theta scanning lenses are normally used, so called because, in addition to being characterized by a flat image field, they allow describing the displacement in linear terms as the product between the focal length f and the deflection angle Θ, eliminating the need for complicated electronic correc-tion and allowing the construccorrec-tion of fast, relatively inexpensive, and compact scanning systems. The same result can also be achieved by using a dynamic focusing unit instead of the F-Theta lens, which is still able to provide a flat image field, but in addition allows to adjust the position of the focus along the optical axis z and, then, to adjust the size of the laser spot on the work surface. The dynamic focusing units can finally be used in combination with F-Theta objectives to widen the range of regulation allowed, and are currently one of the most widespread solutions adopted in AM technologies. Finally, if required, it is then possible to reduce the size of the spot or improve the collimation of the beam through the use of beam expanders, which are components usually posi-tioned upstream from the system and consisting of two or more optical elements that vary the size of the beam changing its divergence.
For what it concerns instead the positioning of the beam on the scanning plane, it occurs through the use of two mirrors rotating on mutually perpendic-ular axes, as shown in Figure 1.9. A mirror controls the placement of the beam along the x axis while the other controls the position along the y axis. They are closed-loop controlled and driven by galvanometric motors, i.e. actuators based on the interaction between a static magnetic field and a magnetic field generated by a moving coil in which a controlled current flows. A spring or a component with the same function counteracts the rotation of the coil, with the result that the deviation angle is proportional to the intensity of the current. These devices are able to combine high precision with fast movements.
Figure 1.9: Optical system for positioning the laser beam on the scanning plane. ©SCANLAB GmbH.
Figure 1.11: Laser control signals.
the application software, scan head, and laser. These boards synchronize laser control with the scanner movements and implement image correction to ensure correct exposure of the working area. The controller provides two types of commands: the control commands and the list commands. The former are commands executed immediately, and are used to set some parameters, directly control the laser and the scanner, and execute the list commands. The latter are instead made up of a series of instructions that must be loaded into a buffer, on the order of a specific control command, before being executed, then the list is closed by a special instruction, and, finally, the list command is called by a dedicated control command for execution.
The control of fiber lasers in Q-Switch mode, typically used in SLM tech-nology, occurs through different control signals that include the analogue man-agement of power, an on/off signal, the control of the Q-Switch based on the pulse period and width set, and the management of the so-called First Pulse Suppression (FPS), which allows the energy of the initial pulses of a pulse train to be adequately reduced (Cap. 2). In fact, in Q-Switch mode the first pulses after a laser switch-off phase are characterized by high energy intensity, and this can affect the quality of the process. As shown in the Figure 1.11, the FPS signal is activated at the same time as the laser is turned on, and, unless there are special control logics, the first Q-Switch pulse starts in turn at the beginning of the FPS signal.
