Additive Manufacturing is a fast-developing technology that is considered to be a game changer in the manufacturing industry. However, a technological innovation itself has no single objective value for a company. Indeed, it is widely acknowledged that the key aspect of a successful commercialization of a technological innovation is the linkage of the technology and the business model. Based on a qualitative study, which presents how companies have to develop their business model to commercialize AM, we conducted interviews with two Swedish small and medium-sized enterprises, which plan to invest in Additive Manufacturing. These two companies are HGF, a manufacturer of thermoplastic elastomers and rubber products, and Tylö, a manufacturer of heaters, steam generators, saunas, steam showers, and infrared saunas. In our analysis, we decided to analyse the cases successively, according to the nine building blocks of the Business Model Canvas. Firstly, we conducted a within-case analysis to analyse each case isolated from each other, and secondly a cross-case analysis to find possible nexuses, relations or, contrasts. The chapter conclusion provides an overall discussion of the most important findings emerging from the analysis with regard to the required changes within the current business model to capture value from the technology. We could find some disparities for two building blocks (channels and revenue streams). Thus, this implies that there is no universal approach to develop the business model to introduce Additive Manufacturing. Nevertheless, most of the required adjustments show accordance. While three building blocks turned out to remain largely the same (key partnerships, cost structure, and customer segments), four building blocks require important changes (key activities, key resources, value propositions, and customer relationships. The most important implications for those building blocks are presented in the following: Key activities: Upgrade product development Key resources: Establish additional production facilities (3D-printers, etc.) Gather new knowledge about AM Value propositions: Offer customized products Customer relationships: Closer relationship with the (end) customer  Enhance customer co-creation

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.

Metal Additive Manufacturing (AM) provides the means to fabricate complex metallic parts with reduced time to market and material waste and improved design freedom. Industries with strict materials qualifications such as aerospace, biomedical, and automotive are increasingly looking to AM to meet their production needs. However, significant materials-related challenges impede the widespread adoption of these technologies for critical components. In particular, fatigue resistance in as-built parts has proven to be inferior and unpredictable due to the large and variable presence of porosity. This presents a challenge for the qualification of any load bearing part without extensive post-processing, such as Hot Isostatic Pressing, and thorough inspection. Improved understanding of the underlying mechanisms behind defect formation will assist in designing process improvements to minimize or eliminate defects without relying entirely on postprocessing. In this work, the effects of powder, processing parameters, and post-processing on porosity formation in powder-bed metal AM processes are investigated using X-ray microtomography and a newly developed in-situ high speed radiography technique, Dynamic Xray Radiography. High resolution X-ray computed tomography is used to characterize defect morphology, size, and spatial distribution as a function of process and material inputs. Dynamic X-ray Radiography, which enables the in-situ observation of the laser-metal interactions at frame rates on the order of 100 kHz (and faster), is utilized to understand the dynamic behavior and transitions that occur in the vapor depression across process space. Experimental validation of previously held assumptions regarding defect formation as well as new insights into the influence of the vapor cavity on defect formation are presented.

The selective laser sintering (SLS) process or the additive manufacturing (AM) enables the construction of a three-dimensional object through melting and solidification of metal powder. The primary advantage of AM over the conventional process is providing the manufacturing flexibility, especially for highly complicated products. The quality of AM products depends upon various processing parameters such as laser power, laser scanning velocity, laser scanning pattern, layer thickness, and hatch spacing. The improper selection of these parameters would lead to parts with defects, severe distortion, and even cracking. I herein perform the numerical and experimental analysis to investigate the interplay between processing parameters and the defect generation. The analysis aims to resolve issues at two different scales, micro-scale and product-scale. At the micro-scale, while the numerical model is developed to investigate the interaction of the laser and materials in the AM process, its advantages and disadvantages compared to an analytical approach (Rosenthal’s equation), which provides a quicker thermal solution, are thoroughly studied. Additionally, numerical results have been verified by series of experiments. Based on the analysis, it is found that the simultaneous consideration of multiple processing parameters could be achieved using the energy density. Moreover, together with existing criteria, a processing window is numerically developed as a guideline for AM users to avoid common defects at this scale including the lack of fusion, balling effect, and over-melting. Thermal results at a micro-scale are extended as an input to determine the residual stress initiation in AM products. The effect of energy density and substrate temperature on a residual stress magnitude is explored. Results show that the stress magnitude within a layer is a strong function of the substrate temperature, where a higher substrate temperature results in a lower stress. Moreover, the stress formation due to a layer’s addition is studied, in which the stress relaxation at locations away from a top surface is observed. Nevertheless, even though the micro-scale analysis can resolve some common defects in AM, it is not capable of predicting product-scale responses such as residual stress development and entire product’s distortion. As a result, the multiscale modeling platform is developed for the numerical investigation at the product level. Three thermal models at various scales are interactively used to yield an effective thermal development calculation at a product-scale. In addition, the influence of the multiple layers, energy densities and scanning patterns on the residual stress formation has been addressed, which leads to the prediction of the residual stress development during the fabrication. The distortion of products due to the residual stress can be described by the product-scale model. Furthermore, among many processing parameters, the energy input and the scanning length are found to be important factors, which could be controlled to achieve the residual stress reduction in AM products. An optimal choice of a scanning length and energy input can reduce an as-built residual stress magnitude by almost half of typically encountered values. Ultimately, the present work aims to illustrate the integration of the computational method as tools to provide manufacturing qualification for part production by the AM process.

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3D printable materials for RF devices need improvement in order to satisfy the demand for higher frequency and lower loss performance. Characterization of materials that have shown improvements of conductor conductivity have been performed. By using a laser machining technique the loss of a 3D printed 2.45 GHz microstrip Square Open Loop Resonator (SOLR) bandpass filter has been shown to improve by 2.1dB, along with an increase in bandwidth from 10% to 12.7% when compared to a SOLR filter that has not been laser machined. Both laser machined and microwaved silver inks have been mapped for conductivity using a Near Field Microwave Microscope (NFMM) and have shown improvement of conductivity compared to inks that have been cured using standard methods.

Additive manufacturing (AM) is a manufacturing technique that adds material, such as polymers, ceramics, and metals, in patterned layers to build three-dimensional parts for applications related to medicine, aviation, and energy. AM processes for metals like selective laser melting (SLM) hold the unique advantage of fabricating metal parts with complex architectures that cannot be produced by conventional manufacturing techniques. Thermal transport can be a focal point of unique AM products and is likewise important to metal AM processes. This dissertation investigates AM metal meshes with spatially varied thermal conductivities that can be used to maximize the charge and discharge rates for thermal energy storage and thermal management by phase change materials (PCMs). Further, manufacturing these meshes demands excellent thermal control in the metal powder bed for SLM processes. Since the thermal conductivities of metal powders specific to AM were previously unknown, we made pioneering measurements of such powders as a function of gas infiltration. In the past, thermal transport was improved in phase change materials for energy storage by adding spatially homogeneous metal foams or particles into PCMs to create composites with uniformly-enhanced (UE) thermal conductivity. Spatial variation can now be realized due to the emergence of metal AM processes whereby graded AM meshes are inserted into PCMs to create PCM composites with spatially-enhanced (SE) thermal conductivity. As yet, there have been no studies on what kind of spatial variation in thermal conductivity can further improve charge and discharge rates of the PCM. Making such mesh structures, which exhibit unsupported overhangs that limit heat dissipation pathways during SLM processes, demands understanding of heat diffusion within the surrounding powder bed. This inevitably relies on the precise knowledge of the thermal conductivity of AM metal powders. Currently, no measurements of thermal conductivity of AM powders have been made for the SLM process. In chapter 2 and 3, we pioneer and optimize the spatial variation of metal meshes to maximize charge and discharge rates in PCMs. Chapter 2 defines and analytically determines an enhancement ratio of charge rates using spatially-linear thermal conductivities in Cartesian and cylindrical coordinates with a focus on thermal energy storage. Chapter 3 further generalizes thermal conductivity as a polynomial function in space and numerically optimizes the enhancement ratio in spherical coordinates with a focus on thermal management of electronics. Both of our studies find that higher thermal conductivities of SE composites near to the heat source outperform those of UE composites. For selected spherical systems, the enhancement ratio reaches more than 800% relative to existing uniform foams. In chapter 4, the thermal conductivities of five metal powders for the SLM process were measured using the transient hot wire method. These measurements were conducted with three infiltrating gases (He, N2, and Ar) within a temperature range of 295-470 K and a gas pressure range of 1.4-101 kPa. Our measurements indicate that the pressure and the composition of the gas have a significant influence on the effective thermal conductivity of the powder. We find that infiltration with He provides more than 300% enhancement in powder thermal conductivity, relative to conventional infiltrating gases N2 and Ar. We anticipate that this use of He will result in better thermal control of the powder bed and thus will improve surface quality in overhanging structures.

The complexity of components fabricated in today's industry is ever increasing. This increase is partly due to market pressure but it is also a result from progress in fabrication technologies that opens up new possibilities. The increased use of additive manufacturing and multi-material systems, especially, has driven the complexity of parts to new heights. The new complex material systems brings benefits in many areas such as; mechanical properties, weight optimisation, and sustainability. However, the increased complexity also makes material integrity investigations and dimensional control more difficult. In additive manufacturing, for example, internal features can be fabricated which cannot be seen or measured with conventional tools. There is thus a need for non-destructive inspection methods that can measure these geometries. Such a method is X-ray computed tomography. Computed tomography utilizes the X-rays ability to penetrate material to create 3D digital volumes of components. Measurements and material investigations can be performed in these volumes without any damage to the investigated component. However, computed tomography in material science is still not a fully mature method and there are many uncertainties associated with the investigation technique. In the work presented in this thesis geometries fabricated by various additive manufacturing processes have been investigated using computed tomography. Also in this work, a dual-energy computed tomography tool has been developed with the aim to increase the measurement consistency of computed tomography when investigating complex geometries and material combinations. / MultiMatCT

Additive manufacturing (AM) is a particularly useful manufacturing method for components designed using topology optimization (TO) since it allows for a greater part complexity than any traditional manufacturing method. However, the AM process potentially leads to anisotropic material properties due to the layer-by-layer buildup of parts and the fast and directional cooling. For Ti6Al4V tensile specimens built using electron beam melting (EBM), it has been observed that flat built specimens show superior strength and elastic moduli compared to top built specimens. Designs with the loading direction parallel to the build layers are therefore expected to show greater reliability. In this thesis a procedure is developed to optimize the AM build orientation considering anisotropic elastic material properties. A transversely isotropic material model is used to represent the in-plane and out-of-plane characteristics of AM produced parts. Two additional design variables are added to the TO formulation in order to control the orientation of the material using a coordinate transformation. Sensitivity analysis for the material direction variables is conducted for compliance as well as maximum von-Mises stress using a -norm stress aggregation function. The procedures for the AM build orientation optimization and stress constraints are implemented in the finite element software TRINITAS and evaluated using a number of examples in 2D and 3D. It is found that the procedure works well for compliance as well as stress but that a combination of these may lead to convergence issues due to contradicting optimal material orientations. An evaluation of the -norm stress aggregation function showed that a single global stress measure in combination with a stress correction procedure works well for most problems given that the mesh is refined enough to resolve the stresses accurately.