SammanfattningDet här projektet behandlar området Additiv Tillverkning (AM) för metalliska material och undersöker om det är lämpligt att använda vid produktion inom flygindustrin. AM är en relativt ny tillverkningsmetod där föremål byggs upp lager för lager direkt ifrån en datormodell. Teknikområdet tillåter i många fall större konstruktionsfriheter som möjliggör tillverkning av mer viktoptimerade och funktionella artiklar. Andra fördelar är materialbesparing och kortare ledtider vilket har ett stort ekonomiskt värde.En omfattande litteraturstudie har gjorts för att utvärdera alla tekniker som finns på marknaden och karakterisera vad som skiljer de olika processerna. Även maskiners prestanda och kvalité på tillverkat material utvärderas, och för varje teknik listas möjligheter och begränsningar. Teknikerna delas grovt upp i pulverbäddsprocesser och material deposition-processer. Pulverbäddsteknikerna tillåter större friheter i konstruktion, medan material deposition-processerna tillåter tillverkning av större artiklar. Den vanligaste energikällan är laser som ger ett starkare men mer sprött material än de alternativa energikällorna elektronstråle och ljusbåge.Två specifika tekniker har valts ut för att undersöka närmare i detta projekt. Electron Beam Melting (EBM) från Arcam och Wire fed plasma arc direct metal deposition från Norsk Titanium (NTiC). EBM är en pulverbäddsprocess som kan tillverka färdiga artiklar i begränsad storlek då låga krav ställs på toleranser och ytfinhet. NTiC använder en material deposition-process med en ljusbåge för att smälta ner trådmaterial till en nära färdig artikel. Den senare metoden är mycket snabb och kan tillverka stora artiklar, men måste maskinbearbetas till slutgiltig form. En materialundersökning har genomförts där Ti6Al4V-material från båda teknikerna har undersökts i mikroskop och testats för hårdhet. För EBM-material har även ytfinhet och svetsbarhet undersökts då begränsad byggvolym i många fall kräver fogning. Materialen har egenskaper bättre än gjutet material med avseende på styrka och duktilitet, men inte lika bra som valsat material. Provning visar att skillnaden på mekaniska egenskaper i olika riktningar är liten även fast materialet har en inhomogen makrostruktur med kolumnära korn i byggriktningen. EBM ger en finare mikrostruktur och ett starkare material och, tillsammans med de ökade konstruktionsfriheterna, så är det den tekniken som är bäst lämpad för flygplansartiklar då svetsbarheten är god och det finns möjlighet att bearbeta ytan till slutgiltigt krav.Nyckelord: Additiv Tillverkning, Flygteknik, Titan / AbstractThis project treats Additive Manufacturing (AM) for metallic material and the question if it is suitable to be used in the aeronautics industry. AM is a relatively new production method where objects are built up layer by layer from a computer model. The art of AM allows in many cases more design freedoms that enables production of more weight optimized and functional articles. Other advantages are material savings and shorter lead times which have a large economic value.An extensive literature study has been made to evaluate all techniques on the market and characterize what separates the different processes. Also machine performance and material quality is evaluated, and advantages and disadvantages are listed for each technique. The techniques are widely separated in powder bed processes and material deposition processes. The powder bed techniques allow more design freedom while the material deposition techniques allow production of large articles. The most common energy source is laser that gives a harder and more brittle material than the alternative energy sources electron beam and electric arc.Two specific techniques have been selected to investigate further in this project. Electron Beam Melting (EBM) from Arcam and Wire fed plasma arc direct metal deposition from Norsk Titanium (NTiC). EBM is a powder bed process that can manufacture finished articles in limited size when no requirements are set on tolerances and surface roughness. NTiC uses a material deposition process with electric arc to melt wire material to a near-net shape. The latter method is very fast and can produce large articles, but have to be machined to finished shape. A material investigation have been made where Ti6Al4V-material from both techniques have been investigated in microscope and tested for hardness. For the EBM-material have also surface roughness and weldability been investigated since the limited building volume often requires welding. The materials have mechanical properties better than cast material with respect to strength and ductility, but not as good as wrought material. Test results show that the difference in mechanical properties in different directions is small, even though the material has an inhomogeneous macrostructure with columnar grains in the building direction. The EBM-material has a finer microstructure and a stronger material and, in combination with improved design freedom, this technique is most suitable for aerospace articles when the weldability is good and it is possible to surface work where requirements of the surface roughness are set.Keywords: Additive Manufacturing, Aeronautics, Titanium

<p>Extrusion Deposition Additive Manufacturing is a process by which short fiber-reinforced polymers are extruded in a screw and deposited onto a build platform using a set of instructions specified in the form of a machine code. The highly non-isothermal process can lead to undesired effects in the form of residual deformation and part delamination. Process simulations that can predict residual deformation and part delamination have been a thrust area of research to prevent the repeated trial and error process before a useful part has been produced. However, populating the material properties required for the process simulations require extensive characterization efforts. Tackling this experimental bottleneck is the focus of the first half of this research.</p><p>The first contribution is a method to infer the fiber orientation state from only tensile tests. While measuring fiber orientation state using computed tomography and optical microscopy is possible, they are often time-consuming, and limited to measuring fibers with circular cross-sections. The knowledge of the fiber orientation is extremely useful in populating material properties using micromechanics models. To that end, two methods to infer the fiber orientation state are proposed. The first is Bayesian methodology which accounts for aleatoric and epistemic uncertainty. The second method is a deterministic method that returns an average value of the fiber orientation state and polymer properties. The inferred orientation state is validated by performing process simulations using material properties populated using the inferred orientation state. A different challenge arises when dealing with multiple extrusion systems. Considering even the same material printed on different extrusion systems requires an engineer to redo the material characterization efforts (due to changes in microstructure). This, in turn, makes characterization efforts expensive and time-consuming. Therefore, the objective of the second contribution is to address this experimental bottleneck and use prior information about the material manufactured in one extrusion system to predict its properties when manufactured in another system. A framework that can transfer thermal conductivity data while accounting for uncertainties arising from different sources is presented. The predicted properties are compared to experimental measurements and are found to be in good agreement.</p><p>While the process simulations using finite element methods provide a reliable framework for the prediction of residual deformation and part delamination, they are often computationally expensive. Tackling the fundamental challenges regarding this computational bottleneck is the focus of the second half of this dissertation. To that end, as the third contribution, a neural network based solver is developed that can solve parametric partial differential equations. This is attained by deriving the weak form of the governing partial differential equation. Using this variational form, a novel loss function is proposed that does not require the evaluation of the integrals arising out of the weak form using Gauss quadrature methods. Rather, the integrals are identified to be expectation values for which an unbiased estimator is developed. The method is tested for parabolic and elliptical partial differential equations and the results compare well with conventional solvers. Finally, the fourth contribution of this dissertation involves using the new solver to solve heat transfer problems in additive manufacturing, without the need for discretizing the time domain. A neural network is used to solve the governing equations in the evolving geometry. The weak form based loss is altered to account for the evolving geometry by using a novel sequential collocation sampling method. This work forms the foundational work to solve parametric problems in additive manufacturing.</p>