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.

The traditional approaches to training surgeons are becoming increasingly difficult to apply to modern surgical procedures. The development of Minimally Invasive Surgery (MIS) techniques demands new and complex psychomotor skills, and means that the apprentice-based system described by 'see one, do one, teach one' can no longer be expected to fully prepare surgeons for operations on real patients, placing patient safety at risk. The use of cadavers and animals in surgical training raises issues of ethics, cost and anatomical similarity to live humans. Endoscopic sinus surgery involves further risk to the patient due to the proximity of vital structures such as the brain, eyes, optic nerve and internal carotid artery. In recent years, simulation has been used to overcome these problems, exposing surgeons to complex procedures in a safe environment, similarly to its use in aviation. However, the cases simulated in this manner may not be customised by training staff to present desired pathology. This thesis describes the design and development of a new tool for the creation of customised cases for the training of sinus surgery. Users who are inexperienced and non-skilled in the use of three-dimensional (3D) Computer Aided Design (CAD) modelling software may use the tool to implement pathology to the virtual sinus model, which was constructed from real CT data. Swelling is applied in five directions (four horizontal, one vertical) to the cavity lining of the frontal and sphenoid sinuses. Tumours are individually customised and positioned in the frontal, sphenoid and ethmoid sinuses. The customised CAD model may then be latterly manufactured using Three-Dimensional Printing (3DP) to produce the complex anatomy of the sinuses in a full colour physical part for the realistic simulation of surgical procedures. An investigation into the colouring of the physical model is also described, involving the study of endoscopic videos to ascertain realistic shades. The program was evaluated by a group of medical professionals from a range of fields, and their feedback was taken into account in subsequent redevelopment of the program, and to suggest further work.

Additive manufacturing (AM) is a general name used for manufacturing methods which have the capabilities of producing components directly from 3D computeraided design (CAD) data by adding material layer-by-layer until a final componentis achieved. Included here are powder bed technologies, laminated object manufacturing and deposition technologies. The latter technology is used in this study. Laser Metal Powder Deposition (LMPD) is an AM method which builds components by fusing metallic powder together with a metallic substrate, using a laser as energy source. The powder is supplied to the melt-pool, which is created by the laser, through a powder nozzle which can be lateral or coaxial. Both the powder nozzle and laser are mounted on a guiding system, normally a computer numerical control (CNC) machine or a robot. LMPD has lately gained attentionas a manufacturing method which can add features to semi-finished components or as a repair method. LMPD introduce a low heat input compared to conventional arc welding methods and is therefore well suited in, for instance, repair of sensitive parts where too much heating compromises the integrity of the part. The main part of this study has been focused on correlating the main process parameters to effects found in the material which in this project is the superalloy Alloy 718. It has been found that the most influential process parameters are the laser power, scanning speed, powder feeding rate and powder standoff distance.These process parameters have a significant effect on the temperature history ofthe material which, among others, affects the grain structure, phase transformation, and cracking susceptibility of the material. To further understand the effects found in the material, temperature measurements has been conducted using a temperature measurement method developed and evaluated in this project. This method utilizes a thin stainless steel sheet to shield the thermocouple from the laser light. This has proved to reduce the influence of the laser energy absorbed by the thermocouples.

Policymakers in the United States and elsewhere have recognized that a broad and competitive manufacturing sector is crucial to a robust economy and that to remain competitive, a nation must invent and master new ways of making things. Moving technologies from laboratory to commercial success poses considerable challenges however. If the technology is radically new, this transition can be so risky and investment-heavy that only very large private firms can attempt it. One such new technology is metal additive manufacturing (MAM). MAM provides a vivid illustration of the tensions policymakers must resolve in simultaneously supporting the commercialization of early-stage innovations of strategic national interest, while fulfilling the government’s duty to ensure human health and safety. After an initial chapter with a general overview of additive manufacturing technologies, this dissertation explores these tensions from the perspective of two very different industrial contexts: the U.S. as a technology leader and trailblazer in the development of the technology, and Portugal as a technology follower with severely constrained resources. In the first case study, I use the extreme case of MAM (an emerging technology with many sources of process uncertainty) in commercial aviation (an industry where lapses in safety can have catastrophic consequences) to unpack how the characteristics of a technology may influence the options for regulatory intervention. Although my work focuses on the U.S. and the Federal Aviation Administration’s regulation, I expect this work to have an international scope, given that in most countries regulation is heavily influenced by, if not an exact copy of, the U.S. regulation. Based on my findings, I propose an adaptive regulatory framework in which standards are periodically revised and in which different groups of companies are regulated differently as a function of their technological capabilities. I conclude by proposing a generalizable framework for regulating emerging process-based technologies in safety-critical industries in which the optimal regulatory configuration depends on the industry structure (number of firms), the performance and safety requirements, and the sources of technological uncertainty. In the second case study, I analyze the adoption of polymer (PAM) and metal (MAM) additive manufacturing technologies in the Portuguese molds industry, both of which offer important benefits to their products. Leveraging archival data (related to the history of Portuguese institutions, and the development of additive manufacturing both globally and in Portugal), insights from 45 interviews across academia, industry, and government; and 75 hours of participant observations, we develop insights about why institutional instability affected the adoption of Polymer Additive Manufacturing (PAM) and Metal Additive Manufacturing (MAM) differently. In both cases, Portugal invested in the technology relatively early, and in the case of PAM the research community has been able to move towards high-tech applications. In contrast, the adoption of MAM has been modest despite its potential to greatly improve the performance and competitiveness of metal molds. From the comparison between PAM and MAM, we generate theory about which technological and contextual factors affect their ‘technological forgiveness’, defined as the resiliency of a new technology’s adoption to institutional instability. We conclude by proposing a generalizable framework for ‘forgiveness’ in different industrial contexts. The final chapter of this dissertation contains practical recommendations for regulators and managers interested in adopting the technology. Policymakers in the aviation industry may want to encourage the creation of programs to gather more flight experience with MAM parts. Small aircraft and other applications with higher risk tolerance than commercial aviation might represent more important channels to gather information, as the history of composite materials suggests. More importantly, regulators may need to introduce clauses in their rules to regulate MAM to avoid situations of ‘regulatory lock-in’ which could harm the long-term potential of the technology. Despite the potential of additive manufacturing, we believe that near-term expectations for it are overblown. In general, additive manufacturing holds great promise, but in many areas the cart has gotten ahead of the horse. Much of the technology is still under development. The history of comparable technologies such as composite materials and high-performance castings shows that the problems may take decades to resolve. For now, additive manufacturing is cost-competitive only in niche applications — for instance, those involving plastics. Businesses that want to plunge into additive manufacturing should be cognizant of the challenges. Determining whether it makes sense to invest in additive manufacturing will require experimentation and learning.