Metal additive manufacturing (MAM) is a manufacturing technology experiencing a rapid expansion rate. Metal laser powder bed fusion (ML-PBF) is among the most popular techniques in this field. The environmental implications of it are often discussed in literature and compared to conventional manufacturing. However, the system in its entirety, from a cradle-to-gate perspective, has not seen intense scrutiny so far. A Life Cycle Assessment (LCA) often serves as the evaluation method when investigating environmental impacts; however, this method has been proven to be complex and time-consuming. Efforts are made to reduce this burden by, among others, developing streamlined LCA tools for MAM. This thesis presents three different life cycle assessments, each with different system boundaries, methodologies, and data qualities. In all of them, Global Warming Potential (GWP) and CO2 emissions are focused on. The aim of this thesis is to investigate how large the environmental impact of ML-PBF is when considering the whole system, and to compare this to a streamlined assessment, per kilogram of printed AlSi10Mg based on an average production scenario. The database ecoinvent v.3 and the characterization method ReCiPe 2016 midpoint (H) are used for the analysis with wider system boundaries in combination with specific data. Whereas a third-party streamlined LCA tool is used for the LCA with narrower system boundaries, using the specific energy content of the material. Previous research in the field of ML-PBF often neglects the impact of inert gas and attributes a large portion of the impact to processing electricity. Moreover, post-processing and machine impacts are usually not included in the system boundaries but have been advocated by many to be worth investigating. The results in this thesis show that in contrast to previous research, argon gas accounted for the biggest GWP and where process electricity accounted for less than half of argon. A system boundary expansion was also found to lead to an increase of nearly 230 % of CO2 eq emissions, making it significant to the analysis. Many minuscule factors such as machining, various losses, idle time, machine impact and compressed air contributed to this contrast. Combining this with an improvement and generalizability analysis showed that the global warming potential associated with ML-PBF can be lowered by more than 75 % through either altering the electricity mix or optimizing process parameters, both at the company and upstream. Additionally, it was discovered that the LCA calculation method, and deviations in data quality, contributed to a higher difference in the environmental impact than expanding the system boundaries.

Additive manufacturing (AM) processes may introduce large residual stresses in the as-built part, in particular the laser powder bed fusion process (L-PBF). The residual stress state is an inherent consequence of the heterogeneous heating and subsequent cooling during the process. L-PBF has become renowned for its “free complexity” and rapid prototyping capabilities. However, it is vital to ensure shape stability after the component is removed from the build plate, which can be problematic due to the residual stress inducing nature of this manufacturing process. Residual stresses can be analyzed via many different characterization routes (e.g. X-ray and neutron diffraction, hole drilling, etc.), both quantitatively and qualitatively. From an industrial perspective, most of these techniques are either prohibitively expensive, complex or too slow to be implementable during the early prototyping stages of AM manufacturing. In this work a deformation based method employing a specific geometry, a so called “keyhole”-geometry, has been investigated to qualitatively evaluate the effect of different stress relief annealing routes with respect to macroscopic part deformation, mechanical properties and microstructure. Previous published work has focused on structures with open geometry, commonly referred to as bridge-like structures where the deformation required for analysis occurs during removal from the build plate. The proposed keyhole-geometry can be removed from the build plate without releasing the residual stresses required for subsequent measurement, which enables bulk manufacturing on single build plates, prior to removal and stress relief annealing.  Two L-PBF manufactured austenitic stainless steel alloys were studied, 316L and 21-6-9. Tensile specimen blanks were manufactured and the subsequent heat treatments were carried out in pairs of keyhole and tensile blank. Both a contact (micrometer measurement), and a non-contact (optical profilometry) method were employed to measure the residual stress induced deformation in the keyholes. The annealing heat treatment matrix was iteratively expanded with input from the deformation analysis to find the lowest temperature at which approximately zero deformation remained after opening the structure via wire electrical discharge machining. The lowest allowable annealing temperature was sought after to minimize strength loss.  After stress relief annealing at 900 ℃ for 1 hour, the 316L keyhole-geometry was considered shape stable. The lateral micrometer measurement yielded a length change of 1 µm, and a radius of 140 m (over the 22 mm top surface) was assigned from curve fitting the top surface height profiles. The complementary microstructural characterization revealed that this temperature corresponded to where the last remains of the cellular sub-grain structures disappears. Tensile testing showed that the specimen subjected to the 900 ℃ heat treatment had a marked reduction in yield stress (YS) compared to that of the as-built: 540 MPa → 402 MPa, whereas ultimate tensile strength (UTS) only reduced slightly: 595 MPa → 570 MPa. The ductility (4D elongation) was found to be ~13 % higher for the specimen heat treated at 900 ℃ than that of the as-built specimen, 76% and 67% respectively.  For alloy 21-6-9 the residual stress induced deformation minimum (zero measurable deformation) was found after stress relief heat treatment at 850 ℃ for 1 hour. Slight changes in the microstructure were observable through light optical microscopy when comparing the different heat treatment temperatures. The characteristic sub-grain features associated with alloy 316L were not verified for alloy 21-6-9. Similar to the results for 316L, UTS was slightly lower for the tensile specimen subjected to the heat treatment temperature required for shape stability (850 ℃) compared to the as-built specimen: 810 MPa → 775 MPa. The measured ductility (4D elongation) was found to be approximately equal for the as-built (47%), and heat treated (48%) specimen. As-built material exhibited a YS of 640 MPa while the heat treated specimen had a YS of 540 MPa. For alloy 21-6-9, the lateral micrometer deformation measurements were compared with stress relaxation testing performed at 600 ℃, 700℃ and 800 ℃. Stress relaxation results were in good agreement with the results from the lateral deformation measurements.  The study showed that for both steel alloys, the keyhole method could be successfully employed to rapidly find a suitable stress relief heat treatment route when shape stability is vital.

This study aims to improve the Additive Manufacturing (AM) design space for the popular multi-component Ni alloy Inconel 625 (IN625) thorough investigating the microstructural evolution, namely the solidification microstructure and the solid-state phase transformations during the Laser Powder Bed Fusion (LPBF) process. Highly non-equilibrium solidification and the complex reheating conditions during the LPBF process result in the formation of various types of solidification microstructures and grain morphologies which consequently lead to a wide range of mechanical properties. Understanding the melt’s thermal conditions, alloy chemistry, and thermodynamics during the rapid solidification and solid-state phase transformation in AM process will help to control material properties and even produce a material with specific microstructural features suited to a given application. This research helps to better understand the process-microstructure-property relationships of LPBF IN625. First, a set of simple but effective analytical solidification models were employed to evaluate their ability to predict the solidification microstructure in AM applications. As a case study, Solidification Microstructure Selection (SMS) maps were created to predict the solidification growth mode and grain morphology of a ternary Al-10Si-0.5Mg alloy manufactured by the LPBF process. The resulting SMS maps were validated against the experimentally obtained LPBF microstructure available in the literature for this alloy. The challenges, limitations, and potential of the SMS map method to predict the microstructural features in AM were comprehensively discussed. Second, The SMS map method was implemented to predict the solidification microstructure and grain morphology in an LPBF-built multi-component IN625 alloy. A single-track LPBF experiment was performed utilizing the EOSINT M280 machine to evaluate the SMS map predictions. The resulting microstructure was characterized both qualitatively and quantitatively in terms of the solidification microstructure, grain morphology, and Primary Dendrite Arm Spacing (PDAS). Comparing the experimentally obtained solidification microstructure to the SMS map prediction, it was found that the solidification mode and grain morphology were correctly predicted by the SMS maps. Although the formation of precipitates was predicted using the CALculation of PHAse Diagrams (CALPHAD) approach, it was not anticipated from the analytical solution results. Third, to further investigate the microsegregation and precipitation in IN625, Scanning Transmission Electron Microscopy (STEM) using Energy-Dispersive X-ray Spectroscopy (EDS), High-Angle Annular Dark-Field Scanning Transmission Electron Microscopy (HAADF-STEM), Scheil-Gulliver (with solute trapping) model, and DIffusion-Controlled TRAnsformations (DICTRA) method were employed. It was found that the microstructural morphology mainly consists of the Nickel-Chromium (gamma-FCC) dendrites and a small volume fraction of precipitates embedded into the interdendritic regions. The precipitates predicted with the computational method were compared with the precipitates identified via HAADF-STEM analysis inside the interdendritic region. The level of elemental microsegregation was overestimated in DICTRA simulations compared to the STEM-EDS results; however, a good agreement was observed between the Scheil and STEM-EDS microsegregation estimations. Finally, the spatial variations in mechanical properties and the underlying microstructural heterogeneity of a multi-layer as-built LPBF part were investigated to complete the process-structure-properties relationships loop of LPBF IN625. Towards this end, numerical thermal simulation, electron microscopy, nano hardness test, and a CALPHAD approach were utilized to investigate the mechanical and microstructural heterogeneity in terms of grain size and morphology, PDAS, microsegregation pattern, precipitation, and hardness along the build direction. It was found that the as-built microstructure contained mostly columnar (Nickel–Chromium) dendrites were growing epitaxially from the substrate along the build direction. The hardness was found to be minimum in the middle and maximum in the bottom layers of the build’s height. Smaller melt pools, grains, and PDAS and higher thermal gradients and cooling rates were observed in the bottom layers compared to the top layers. Microsegregation patterns in multiple layers were also simulated using DICTRA, and the results were compared with the STEM-EDS results. The mechanism of the formation of precipitates in different regions along the build direction and the precipitates’ corresponding effects on the mechanical properties were also discussed. / Thesis / Doctor of Philosophy (PhD)

No description available.

Laser powder bed fusion is an additive manufacturing technique that is capable of building metallic parts by spreading many layers of metal powder over a build surface and using a laser to melt specific sections of the surface. The part is built by melting consecutive layers on top of each other until the design is completed. However, during this process defects can occur. These defects have impacts on the part’s physical properties, and it is important to detect them for quality assurance. A single part takes several hundred or thousands of layers to build. While each layer is built, cameras and sensors are used to create images of each layer. These images are used for identification and classification of defects that could have a negative impact on a printed part’s physical properties, such as tensile strength. Classification of defects would reduce manual inspection of the printed part. Thus, the classification of defects in each layer must be automated, as it would be infeasible to manually classify each layer. Recently, machine learning have proven to be an effective method for automating defect classification in laser powder bed fusion. However, machine learning and especially deep-learning approaches generally require a large amount of labeled training data, which is typically not available for laser powder bed fusion printed parts. Labeling of images requires manual labor and domain knowledge. One of the greatest obstacles in defect classification, is how machine learning can be applied despite this absence of labeled data. A machine learning approach that show potential for being trained with less data, is the siamese neural network approach. In this thesis, a novel approach for automating defect classification is developed, using layer images from a laser powder bed fusion printing process. In order to cope with the limited access to labeled data, the classifiers are based on the siamese neural network structure. Two siamese neural network structures are developed, a one-shot classifier, which directly classifies the instance, and a hierarchical classifier with a hierarchical classification process according to the hierarchy of the defect classes. The classifiers are evaluated by inferring a test set of images collected from the laser powder bed fusion process. The one-shot classifier is able to classify the images with an accuracy of 70%and the hierarchical classifier with an accuracy of 86%. For the hierarchical classifier area of the ROC curves were calculated to be, 0.96 and 0.95 for the normal vs defect and overheating vs spattering stages respectively. Unlabeled images were added to the training set of a new instance of the hierarchical classifier, which could infer the test set without any major changes to test set accuracy.

Laser-material interaction of Nickel based superalloy Haynes 282 melt pools were studied for laser parameters similar to laser powder bed fusion (PBF-LB) without powder. The effect of power, speed, hatch distance and laser focus offset were analysed by characterizing different types of melt pool behaviour, including conduction, transition to keyhole, and keyhole mode. Focus offset parameter was found to modify the melting mode from keyhole to conduction type in experiments with and without powder. This change in melting mode is attributed to the variation in laser beam spot size for the same line energy. Such manipulation of type of melting with control of focus offset can be utilized as a method to optimize process parameters for novel materials in the PBF-LB process at high layer thickness. Based on the above study, cubes were built with refined process parameters utilizing powder layer thicknesses of 60- and 90-microns for improved productivity, using partial factorial design of experiment. The conduction mode of melting helped reducing defects, minimizing lack of fusion and keyhole porosity in specimens built with powder at 60- and 90-microns layer thickness. Effect of process parameters and indirect measure like area energy, on the melt pool overlap, defect level and dominant shape of the defects are presented. Optimizing the process parameters to identify the boundaries for building cubes with reduced porosity is also discussed. / Den Ni-baserade superlegeringen, Haynes 282, skannades med laserparametrar liknande de som används i laserpulverbäddfusion (PBF-LB), men utan pulver.Studien undersökte inverkan av effekt, hastighet, avstånd mellan två intilliggandeskanningspass och laserfokusförskjutning, vilket karakteriserades genom olikatyper av beteenden hos smältbadet, inklusive värmeledning, övergång frånvärmeledning till nyckelhål, och nyckelhål. Fokusförskjutningen visade sig ändrasmältbadets läge från nyckelhål till värmeledning. Denna förändring observeradesbåde i experiment utan pulver och i de med pulver. Förändringen beror påbreddningen av laserstrålens punktstorlek samtidigt som samma linjeenergibibehålls. Denna förändring i smältningstyp genom fokusförskjutning kananvändas som en metod för att optimera utforskningen av nya material i PBFLB-processen. Baserat på detta byggdes kuber med pulver med lagertjocklekar på 60 och 90mikrometer, användande olika processparametrar enligt en experimentell designbaserad på en central sammansatt design. Smältning genom värmeledning bidrogtill att minska defekter, minimera bindningsfel och nyckelhålsporositet i proversom byggts med pulver med lagertjocklekar på 60 och 90 mikrometer. Inverkanav processparametrarna och indirekta mått såsom areaenergi på smältbadetsöverlappning, defektnivå och den dominerande formen på defekter presenteras.Optimering av processparametrarna samt identifiering av parameterrymden föratt bygga kuber med minskad porositet undersöks också. / <p>Paper A is to be submitted, and paper C is acceptet and are not included in this licentiate thesis. We do  not have permission to publish paper B in the digital version.</p>

Au cours du procédé de fusion laser sur lit de poudre, la température atteinte dans une zone locale est susceptible de générer des gradients thermiques importants. Ces gradients conduisent à leur tour à l'apparition de contraintes résiduelles qui ont un effet sur les caractéristiques mécaniques de la pièce, provoquent des déformations, ainsi que des micro et macro fissures. Dans ce contexte, les trajectoires de lasage jouent un rôle fondamental sur le niveau et la distribution de la température au cours de la fabrication. Il est ainsi nécessaire de valider la génération des trajectoires au regard du comportement thermique induit par ce procédé.Cette thèse propose d'exploiter une méthode analytique pour développer un modèle qui permette d'analyser d'une manière rapide et efficace le comportement thermique dans la pièce lors de la fabrication. En effet, à partir d'une trajectoire de lasage donnée, d'un ensemble de paramètres liés au matériau de la pièce à fabriquer et de paramètres liés au procédé, l'outil développé effectue une simulation de la température en chaque point de la pièce, au cours de temps et de manière rapide, comparée aux autres logiciels de simulation thermique. En effet, afin de réduire le temps de calcul et l'espace mémoire utilisé pour une telle simulation, un ensemble de techniques d'optimisation a été mis en place.Le modèle proposé a été validé dans le cas de l'alliage Ti6Al4V par comparaison avec une simulation thermique par éléments finis obtenue par un logiciel industriel. Ensuite, les résultats de ce modèle sont confrontés aux résultats expérimentaux. Une fois le modèle validé, il a été mis en œuvre pour analyser des trajectoires couramment utilisées dans la littérature et dans l'industrie.Afin de réduire les gradients thermiques et améliorer la qualité des pièces, la solution proposée consiste à contrôler la température et la taille du bain de fusion. Pour se faire, le modèle thermique développé a été exploité pour moduler les paramètres du procédé au cours de la fabrication d'une part et pour développer une stratégie de lasage à pas adaptatif d'autre part. / During manufacturing by Laser Powder Bed Fusion (LPBF), the achieved temperatures in local areas could generate significant thermal gradients. These gradients lead to the apparition of residual stresses which affect the mechanical characteristics of the part and may cause deformation, as well as micro and macro cracks. In this context, scanning paths play a fundamental role on temperature level and distribution during manufacturing. For that reason, it is necessary to validate the generation of trajectories considering the thermal behaviour induced by this process.The purpose of this PhD thesis is to use an analytical method in order to develop a model that allows a fast and efficient analysis of thermal behaviour, during part manufacturing. Indeed, with a given scanning path, material properties and process parameters, the developed tool performs a temperature simulation at each point of the part, over time and in a fast way, compared to other thermal simulation software. In order to reduce computation time and memory storage used for such a simulation, a set of optimization techniques has been proposed.The developed model has been validated in the case of the Ti6Al4V alloy through a comparison with a finite element thermal simulation obtained by industrial software. Then, the results of this model were compared to experimental results. Once validated, it has been implemented to analyze trajectories commonly used in the literature and industry.In order to reduce thermal gradients and improve part quality, the proposed solution consists in controlling the temperature and size of melt pool. For this purpose, the developed thermal model has been used to modulate the process parameters during manufacturing on the one hand and to develop an adaptive scanning strategy on the other hand.

No description available.

<p>This dissertation presents research work related to laser micro sintering, laser micro machining and laser-induced plasma. Firstly, we present extensive experimental studies of double-pulse laser micro sintering (DP-LMS), which typically utilizes the high pressure generated by laser-induced plasma over the powder bed surface to promote molten flow and enhance densification. Chapter 2 shows a single-track experimental study of the DP-LMS process using cobalt powder. The related fundamental mechanisms and effects of different laser parameters on the sintering results are analyzed with the help of <em>in-situ</em> time-resolved temperature measurements. Chapter 3 shows a multi-track experimental study of the DP-LMS process using iron powder. The sintered materials are characterized via the top surface porosity, elemental composition, grain microstructure, nanohardness and metal phase. Three strategic guidelines for laser parameter selection are summarized in the end. Chapter 4 shows time-resolved imaging and OES measurements for plasma induced during DP-LMS. The plasma temperature and free electron number density are deduced by its optical emission spectra (OES). These three chapters have clearly demonstrated DP-LMS can produce much more continuous and densified materials than LMS only using the sintering or pressing laser pulses.</p> <p><br></p> <p>Then, we present laser micro grooving of silicon carbide (SiC) in Chapter 5 by ultrasound-assisted water-confined laser micromachining (UWLM), in comparison with laser machining in water without ultrasound and laser machining in air. UWLM applies <em>in-situ</em> ultrasound to the water-immersed workpiece surface to improve the machining quality and/or productivity. Time-resolved water pressure measurements are carried out to help analyze relevant mechanisms. It has been demonstrated UWLM can be a competitive approach to produce high-quality micro grooves on SiC. The crack problem appears to be effectively solved using a high pulse repetition rate.</p> <p><br></p> <p>Finally, we report a double-front phenomenon for plasma induced by high-intensity nanosecond laser ablation of aluminum in Chapter 6. An additional plasma front is observed via an intensified CCD (ICCD) camera, which propagates very fast at the beginning but stops propagating soon after the laser pulse mostly ends. Its formation could be caused by the inverse bremsstrahlung absorption of laser energy by the ionized ambient gas. Three possible mechanisms on how the ambient gas breakdown is initiated are proposed. </p>

Traditional methods for increasing the energy absorption of a structure involve using a stronger material or increasing the volume of the structure, resulting in a higher cost or additional weight. Additive manufacturing (AM) can be used to maximize the energy absorption of materials with the ability to create complex geometries such as cellular structures. Previous work has shown that the energy absorption of additively manufactured parts can be improved through functionally graded cellular structures; however, this strategy has not been applied to ultra-high strength steel materials. This work characterizes the effect of multiple functional-grading strategies (e.g. uniform, rod-graded, size-graded) on the energy absorption to weight ratio of laser powder bed fusion (L-PBF) produced M300 maraging steel lattice structures. Each structure is designed with the same average relative density to analyze the structures on an equal mass basis, to evaluate manufacturability, mechanical response, and compare experimental results with numerical simulation.