There is growing interest in using additive manufacturing for various alloy systems and industrial applications. However, existing process development and part qualification techniques, both involve extensive experimentation-based procedures which are expensive and time-consuming. Recent developments in understanding the process control show promise toward the efforts to address these challenges. The current research uses the process mapping approach to achieve control of melt pool geometry and microstructure in different alloy systems, in addition to location specific control of microstructure in an additively manufactured part. Specifically, results demonstrate three levels of microstructure control, starting with the prior beta grain size control in Ti-6Al-4V, followed by cell (solidification structure) spacing control in AlSi10Mg, and ending with texture control in Inconel 718. Additionally, a prediction framework has been presented, that can be used to enable a preliminary understanding of melt pool geometry for different materials and process conditions with minimal experimentation. Overall, the work presented in this thesis has the potential to reduce the process development and part qualification time, enabling the wider adoption and use of additive manufacturing in industry.

This project is part of a bigger project where the goal is to be able to create smaller batches of individually designed pills with a high resolution. This could be done by using a powder bed 3D printer, which our job was to find out. This type of machine prints out a thin pattern of binder through a printer head and then sweeps powder over the pattern, making the powder stick to the binder. This process is repeated until the object is formed. The machine necessary was created from scratch using a guide provided by the Internet. The results were unfortunately uncertain. We managed to print with ink and the pattern created had a high level of accuracy but due to time limitations, we never got to print with actual binder in the cartridge. / Tillverkning av individanpassade läkemedel

Additive manufacturing involves the layer-wise patterned addition of material to create 3D parts, allowing for parts with complex geometries that traditional subtractive manufacturing processes cannot create, while offering good value for low run production parts by eliminating the cost of tooling. Large Area Sintering is a form of powder based additive manufacturing where entire layer cross sections are heated and fused in a single continuous exposure process. This layer by layer powder sintering process is similar to selective laser sintering, but by heating the cross section at a slower and controllable rate there is an opportunity to achieve tighter control over thermal history. This thesis discusses the design, construction, and validation of a large area sintering test platform, as well as a preliminary study on feature resolution. A key component of this system was the integration of an infrared camera, allowing point-wise temperature control of the sintering cross section. There is a hypothesis that longer and controlled heating rates in Large Area Sintering (in comparison to Selective Laser Sintering) would allow the capability to process a wider range of materials, and give more control over the resulting final part properties. The test platform created a repeatable test environment, and successfully demonstrated the capability for point wise temperature control of the sintering cross section, enabling the ability to examine the effects of slower controlled heating rates. Available power on the system was 2.22 W/cm2 for heating, with a temperature control loop time of 160 – 180 ms. The results of the preliminary study on feature resolution also suggested a positive correlation between point wise closed loop temperature control and improved feature resolution, giving motivation for further study.

To ensure the widespread adoption of metal Additive Manufacturing (AM) processes, a complete understanding of the interactions between process variables is necessary. The process variables of beam power, beam velocity, deposition geometry, and beam diameter have been shown in prior works to have major effects on resultant melt pool and solidification characteristics, but this list is incomplete. Without accounting for part temperatures prior to deposition, unintended outcomes may result. In the current work, Ti-6Al-4V is studied in the Powder Bed Fusion (PBF) processes to gain an in-depth understanding of how part temperature interactions with other process variables affect physical properties of the process such as melt pool size and variability, part distortion, porosity, and microstructural characteristics. This research is performed through a combination of finite element modelling, single melt track experiments, full part production, and in-situ monitoring in order to gain a full understanding of the underlying relationships between part temperature and part outcomes. In the Arcam Electron Beam Melting (EBM®) process, this knowledge is used to generate a feedback control strategy to constrain prior beta grain width to remain constant while part surface temperatures are allowed to vary. In the Laser Powder Bed Fusion (LPBF) process, deposition is investigated at elevated substrate temperatures and several findings show that unintended part temperature increases can lead to undesirable consequences while prescribed part temperature changes can increase the available processing window and allow for more uniform deposition. This work also shows that both global temperature changes due to substrate heating and local temperature changes due to the choice of scan strategy can be combined into one metric: the temperature encountered by the melt pool during deposition. A combination of destructive and non-destructive characterization methods are utilized to understand and measure the changes to the melt pool and microstructural development that are seen during deposition. The feasibility of using a commercial high speed camera as a tool for thermography is characterized and the ability to discern cooling rates and thermal gradients within and surrounding the melt pool provide validation for trends in melt pool properties generated from simulations. This work provides a greater understanding of the role of part temperature during deposition and presents methodologies to account for the changes to the melt pool and resultant part due to both prescribed and unintended temperature changes during deposition.

abstract: Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. The proposed study focuses on the data-driven approach to predict the mechanical properties of additively manufactured metals, specifically Ti-6Al-4V. Extensive data for Ti-6Al-4V using three different Powder Bed Fusion (PBF) additive manufacturing processes: Selective Laser Melting (SLM), Electron Beam Melting (EBM), and Direct Metal Laser Sintering (DMLS) are collected from the open literature. The data is used to develop models to estimate the mechanical properties of Ti-6Al-4V. For this purpose, two models are developed which relate the fabrication process parameters to the static and fatigue properties of the AM Ti-6Al-4V. To identify the behavior of the relationship between the input and output parameters, each of the models is developed on both linear multi-regression analysis and non-linear Artificial Neural Network (ANN) based on Bayesian regularization. Uncertainties associated with the performance prediction and sensitivity with respect to processing parameters are investigated. Extensive sensitivity studies are performed to identify the important factors for future optimal design. Some conclusions and future work are drawn based on the proposed study with investigated material. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

Additive manufacturing can be used to produce complex, custom geometries, consolidating different parts into one. This reduces the required number of assemblies and allows distributed manufacturing with short lead times. Defects, such as porosity and surface roughness, associated with parts manufactured by laser powder bed fusion, can severely limit industrial application. The effect these defects have on corrosion and hence long term structural integrity must also be taken into consideration. This project aimed to characterise porosity in both solid and lattice cube samples produced by laser powder bed fusion, with the differences in porosity induced by changes in the process parameters, and subsequently, characterising the effect porosity has on corrosion. The alloy used in this investigation is AlSi10Mg, which is widely used in the aerospace and automotive industries. Samples were studied before and after corrosion using X-Ray computed tomography (CT scanning), metallographic examination and scanning electron microscopy (SEM), as well as compression testing for the lattice cubes. It was found that higher laser power leads to more porosity and lower surface roughness. CT scanning was a very effective method to study corrosion using aligned CT images of before-after states. Porosity did not have an effect on the corrosion during the early corrosion stages (168 hours). The manufacturing process parameters induced differences in porosity and surface conditions, but did not strongly affect corrosion. It is probable that crack initiation sites such as internal porosity and defects are filled with corrosion product, delaying the onset of cracking and failure, and the corrosion product that fill the voids adding to the full strength of the lattice will also slightly increase the compressive strength of the samples. / Dissertation (MEng (Metallurgical Engineering))--University of Pretoria, 2021. / Materials Science and Metallurgical Engineering / MEng (Metallurgical Engineering) / Unrestricted

Selective Laser Melting is a rapidly developing additive manufacturing technique that can be used to create unique metal parts with tailormade properties not possible using traditional manufacturing. To understand the process from a most basic level, this study investigates system capabilities when melting single tracks of material. Individual tracks allow for a wide range of scan speeds and laser powers to be utilized and the melt pools analyzed. I discuss how existing studies and simulations can be used to narrow down the selection of potentially successful parameter combinations as well as the limitations of interpretation for single track information. Once we attain a solid understanding of what parameters perform well at a bead level, we can move onto looking at complete 3D parts. A challenge we have faced is creating near fully dense parts and determining a reliable density measurement technique that is accessible for operators at our university. Our results show that the previously determined optimized scan speed and laser power can consistently create parts with >99.5% density over a range of sizes using an analysis method utilizing readily available equipment and software.

Additive manufacturing (AM) has the possibility of producing complex-shaped components which can not be produced by conventional manufacturing methods. This gives the opportunity for designers to freely think outside the design spectra which is otherwise limited by conventional manufacturing methods. AM of metal has rapidly been developed for the last three decades, and they now are reaching industrial acceptance levels, metal feedstock for use in AM is also rapidly growing. AM of metals is especially of interest for the tooling industry. The design freedom which AM offers the tooling manufacturer can design complex cooling channels within moulds, which could reduce cycle time and enhance the quality of components produced with the moulds. Maraging steels have been proven to both be able to be processed with AM but also have comparable performance to traditionally carbon-based used tool steels. Laser Powder Bed Fusion (LPBF) is one of the most promising AM systems today, by using powder as a feedstock it can produce high-resolution parts without needing to process them after they have been produced. However, there is a need to better understand processing within the LPBF system. This master thesis is aimed to process a newly developed maraging steel from Uddeholm, and conduct process parameter experiment and study their correlation to be able to produce samples with as few defects possible. It is crucial to conform to a good methodology for how to find those correlations and see how they influence the printed material. LPBF process has a multi-complex variable system, and by narrowing down the complexity by focus on the most influencing parameters as has been proven by many researchers. Even with a reduced focus, it is still a multi-variable problem. In this study a methodology of finding process parameters relations, a Design Of Experiment software was used, namely, MODDE. By screening of process parameter ranges, within the software, a statistical evaluation of operational process window can be found with fewer conducted experiment. Development of process parameter can traditionally be time-consuming and result in an unnecessary large number of experiments to find the operational window. The experiment showed that laser power and point distance had the most influencing effect on relative density, followed by exposure time and hatch distance. The experiment was firstly conducted with a layer thickness of 50 µm, the achieved relative density resulted in over 99.8 percent. However, a large lack of fusion defects was observed inside the specimens. Even though a high relative density was measured, a pore analysis has to be conducted to fully understand the size and shape of defects since they can have a severe impact on mechanical properties. It was believed that the layer thickness was too high and that the defects could be reduced by printing a set with same process parameters but with a lower layer thickness of 40 µm instead. The reduction of layer thickness did result in a significant decrease of the defects observed. However, future work after this thesis must be continued to further optimize and to increase the solidity of printed material to reach closer to its conventional produced relatives / Additiv tillverkning har möjligheten att producera komplext konstruerade komponenter som inte kan produceras med konventionella tillverkningsmetoder. Detta ger konstruktörer möjligheten att fritt tänka utanför designspektra som annars begränsas av konventionella tillverkningsmetoder. Additiv tillverkning av metall har snabbt utvecklats under de senaste tre decennierna och har nu nått industriella acceptansnivåer. Metallråvara för användning i additiv tillverkning växer snabbt. Additiv tillverkning av metaller är särskilt intressant för verktygsindustrin, designfriheten som additiv tillverkning kan erbjuda verktygstillverkaren för att kunna utforma komplexa kylkanaler inuti formar. Det kan således reducera cykeltiden och förbättra kvaliteten på komponenter som produceras med formarna. Maråldringsststål har visat sig att både kunna processas i additiv tillverkning och har jämförbara egenskaper med traditionellt kolbaserade verktygsstål. Pulverbäddsystemet är ett av de mest lovande systemen idag, genom att använda pulver som råmaterial kan systemet producera komponenter med hög noggranhet utan att behöva bearbeta dem efter att processen är klar. Det finns emellertid ett behov av att bättre förstå själva processen inom pulverbädds teknologin. Den här masteruppsatsen syftar till att additivt tillverka ett nyutvecklat maråldringsstål från Uddeholm. Samt att genomföra processparameterexperiment och studera deras korrelation för att kunna producera prover med så få defekter som möjligt. Det är avgörande att hitta en metod för hur man hittar korrelationerna och se hur de påverkar det tillverkade materialet. Pulverbäddsystemet har ett multikomplext variabelsystem. För att minska komplexiteten kan fokus läggas på de mest inflytelserika processparametrarna, vilket har bevisats av många forskare. Även med ett reducerat fokus är det fortfarande ett flervariabelsproblem. I denna studie användes en metod för att hitta relationer mellan processparametrar och en Design Of Experiment-programvara, nämligen MODDE. Genom screening av processparametrar, inom programvaran, kan en statistisk utvärdering av operativt processfönster hittas med färre genomförda experiment. Utvecklingen av processparametrar kan traditionellt vara tidskrävande och resultera i ett onödigt stort antal experiment för att hitta det operativa fönstret av processparametrar. Experimentet visade att lasereffekt och punktavstånd påverkande den relativa densiteten mest, följt av exponeringstiden och spåravståndet. Experimentet genomfördes först med en lagertjocklek av 50 mikrometer, lagertjockleken resulterade i en relativ densitet på över 99,8 procent. Emellertid observerades stora fusionsdefekter inuti proverna. Även om en hög relativ densitet mättes, måste en poranalys genomföras för att fullt ut förstå storleken och formen på defekter eftersom de kan ha en avgörande inverkan på mekaniska egenskaperna. Det misstänktes att lagertjockleken var för hög och att defekterna kunde minskas genom att tillverka en ytterligare uppsättning av samma processparametrar men med en lägre lagertjocklek på 40 mikrometer istället. Minskningen av lagertjockleken resulterade i en signifikant minskning av de observerade defekterna. Framgent efter den här avhandlingen måste dock arbetet fortsätta att ytterligare optimera och öka soliditeten i det additivt tillverkade materialet. Det för att uppnå bättre prover och komma ännu närmre det konventionellt tillverkade materialets egenskaper.

This thesis is about the investigation of the spectral interaction of electromagnetic radiation with metal powders. For this purpose, spectral data of powders for laser powder bed fusion processes are investigated in three papers using different techniques. In paper A the spectral radiation behavior of the laser interaction zone is considered, in paper B and C the absorbance behavior of different metal powders depending on their state and measurement method.   Paper A investigates the spectral signal of the process light generated by laser material interaction in laser powder bed fusion. The detection is performed by a coaxially guided measuring beam and a quasi-coaxial measuring beam simultaneously guided by another scanning optics. The signal characteristics depend on the angle of incidence of the measuring beam to the laser material interaction zone. Using high-speed recordings and optical simulations, a model for describing the signal behavior could be determined. The measured spectral intensity distribution representing the degree for energy coupling can be corrected with a correction factor over the whole field for solid materials. This correction includes a function describing the numerical aperture of the measuring channel and the laser intensity on the working field. For the investigated powder, the measurement signal fluctuated strongly and no transferable model could be formed. The reason for this was the different absorbance behavior of the powders investigated. Paper B therefore deals in detail with the spectral absorbance behavior of metal powders for additive manufacturing. Using a high-precision spectrometer, 39 powders were measured reflectively over a wide spectral range and the absorbance determined. By varying the degree of use, aging, grain size and impurities, various influence parameters are determined experimentally and discussed theoretically. Based on 20 derived laser wavelengths, technically usable wavelengths with better process efficiency and stability are proposed. From the obtained absorbance, the efficiency of energy coupling can be estimated and form a broad data base for the optimization of laser parameters. In order to perform the absorbance determinations also in situ in a laser powder bed fusion system paper C describes a possibility of an inline absorbance determination by high resolution coaxial imaging. A method is discussed for geometrically correct and gapless imaging of the processing plane, recorded through the laser optics. By imaging at six different wavelengths, metal powders can be distinguished by their absorbance spectrum and impurities can be detected. In an experimental implementation the functionality of the method is proven. The results are validated by optical simulations, ray tracing and comparative measurements with a high-precision spectrometer.

Indiana University-Purdue University Indianapolis (IUPUI) / Powder bed fusion (PBF) process is a metal additive manufacturing process, which can build parts with any complexity from a wide range of metallic materials. Research in the PBF process predominantly focuses on the impact of a few parameters on the ultimate properties of the printed part. The lack of a systematic approach to optimizing the process parameters for a better performance of given material results in a sub-optimal process limiting the potential of the application. This process needs a comprehensive study of all the influential parameters and their impact on the mechanical and microstructural properties of a fabricated part. Furthermore, there is a need to develop a quantitative system for mapping the material properties and process parameters with the ultimate quality of the fabricated part to achieve improvement in the manufacturing cycle as well as the quality of the final part produced by the PBF process. To address the aforementioned challenges, this research proposes a framework to optimize the process for 316L stainless steel material. This framework characterizes the influence of process parameters on the microstructure and mechanical properties of the fabricated part using a series of experiments. These experiments study the significance of process parameters and their variance as well as study the microstructure and mechanical properties of fabricated parts by conducting tensile, impact, hardness, surface roughness, and densification tests, and ultimately obtain the optimum range of parameters. This would result in a more complete understanding of the correlation between process parameters and part quality. Furthermore, the data acquired from the experiments are employed to develop an intelligent parameter suggestion multi-layer feedforward (FF) backpropagation (BP) artificial neural network (ANN). This network estimates the fabrication time and suggests the parameter setting accordingly to the user/manufacturers desired characteristics of the end-product. Further, research is in progress to evaluate the framework for assemblies and complex part designs and incorporate the results in the network for achieving process repeatability and consistency.