Consumer additive manufacturing (3D printing) has rapidly grown over the last decade. While the technology for the most common type, Fused Filament Fabrication (FFF), has systematically improved and sales have increased, fundamentally, the capabilities of the machines have remained the same. FFF printers are still limited to depositing layers onto a flat build plate. This makes it difficult to combine consumer AM with other objects. While consumer AM promises to allow us to customize our world, the reality has fallen short. The ability to directly modify existing objects presents numerous possibilities to the consumer: personalization, adding functionality, improving functionality, repair, and novel multi-material manufacturing processes. Indeed, similar goals for industrial manufacturing drove the research and development of technologies like direct write and directed energy deposition which can deposit layers onto uneven surfaces. Replicating these capabilities on consumer 3-axis FFF machines is difficult mainly due to issues with reliability, repeatability, and quality. This thesis proposes, demonstrates, and tests a method for scanning and printing dimensionally-accurate (unwarped) digital forms onto physical objects using a modified consumer-grade 3D printer. It then provides an analysis of the machine design considerations and critical process parameters. / Master of Science / Consumer additive manufacturing (3D printing) has rapidly grown over the last decade. While the technology for the most common type, Fused Filament Fabrication (FFF), has systematically improved and sales have increased, fundamentally, the capabilities of the machines have remained the same. FFF printers are still limited to depositing layers onto a flat build plate. This makes it difficult to combine consumer AM with other objects. While consumer AM promises to allow us to customize our world, the reality has fallen short. The ability to directly modify existing objects presents numerous possibilities to the consumer: personalization, adding functionality, improving functionality, repair, and novel multi-material manufacturing processes. Indeed, similar goals for industrial manufacturing drove the research and development of technologies like direct write and directed energy deposition which can deposit layers onto uneven surfaces. Replicating these capabilities on consumer 3-axis FFF machines is difficult mainly due to issues with reliability, repeatability, and quality. This thesis proposes, demonstrates, and tests a method for scanning and printing dimensionally-accurate (unwarped) digital forms onto physical objects using a modified consumer-grade 3D printer. It then provides an analysis of the machine design considerations and critical process parameters.

Unlike traditional stochastic scaffold fabrication techniques, additive manufacturing (AM) can be used to create tissue-specific three-dimensional scaffolds with controlled porosity and pore geometry (meso-structure). However, due to the relatively few biocompatible materials available for processing in AM machines, direct fabrication of tissue scaffolds is limited. To alleviate material limitations and improve feature resolution, a new indirect scaffold fabrication method is developed. A four step fabrication process is explored: Fused Deposition Modeling (FDM) is used to fabricate scaffold patterns of varied pore size and geometry. Next, scaffold patterns are surface treated, and then mineralized via simulated body fluid (SBF); forming a bone-like ceramic throughout the scaffold pattern. Finally, mineralized patterns are heat treated to pyrolyze the pattern and sinter the minerals. Two scaffold meso-structures are tested: "tube" and "backfill." Two pattern materials are tested [acrylonitrile butadiene styrene (ABS) and investment cast wax (ICW)] to determine which material is the most appropriate for mineralization and sintering. Mineralization is improved through plasma surface treatment and dynamic flow conditions. Appropriate burnout and sintering temperatures to remove pattern material are determined experimentally. While the "tube scaffolds" were found to fail structurally, "backfill scaffolds" were successfully created using the new fabrication process. The "backfill scaffold" meso-structure had wall thicknesses of 470 – 530 µm and internal channel diameters of 280 – 340 µm, which is in the range of appropriate pore size for bone tissue engineering. "Backfill scaffolds" alleviated material limitations, and had improved feature resolution compared to current indirect scaffold fabrication processes. / Master of Science

Ion-containing macromolecules continue to stimulate new opportunities for emerging electro-active applications ranging from high performance energy devices to water purification membranes. Progress in polymer synthesis and engineering now permit well-defined, ion-containing macromolecules with tunable morphologies, mechanical performance, ion conductivity, and 3D structure in order to address these globally challenged technologies. Achieving tailored chemical compositions with high degrees of phase separation for optimizing conductivity and water adsorption remains a constant synthetic challenge and presents an exciting opportunity for engineering sophisticated macromolecular architectures. This dissertation will introduce unprecedented charged polymers using conventional free radical and anionic polymerization to incorporate ionic functionalities based on phosphonium cations. This new class of copolymers offers unique properties with ionic functionality for tailorable electro-active performance. / Ph. D.

There is a link between the thermal and electrical properties of metal. The equation which links these two properties is called the Wiedemann-Franz Law. Also there is an emerging technology within Additive Manufacturing called Binder Jet Printing which can print high purity copper without heat stress within the material. Due to the Binder Jet Printings ability to print high resolution prints without any print through, this makes future use of this technology a necessity for future electrical and thermal components within computers . However a thermal and electrical conductivity analysis of binder jetted copper has never been performed, and needs to be for simulation with this material. Therefore within this thesis the relationship of the thermal and electrical properties of printed binder jetted copper part will be researched. To find the electrical resistivity of binder jetted copper, three sets of 2mm diameter rods where printed and then placed within a modified four wire resistance method test. For the thermal conductivity measurements a laser flash diffusivity machine was used, and three sets of 11 copper disks of approximately 1cm diameter by 1mm where printed. The data shows a strong linear trend linking electrical resistivity to the density ratio of the copper. Within the thermal conductance measurement, a lot more variability was seen within the three different prints. The 70% density ratio prints saw a large 13% spread in density ratios throughout the prints, which is believed to be caused by improper sintering due to temperature gradients near the door of the kiln. The 82% density prints saw better grouping of density ratios by placing the specimens in the back of the kiln. Lastly, the 92% prints saw the best density ratio grouping but the largest thermal conductivity variance. Even though the scatter plot for the thermal conductivity measurements are not as precise as the electrical resistivity measurements, it still shows a linear trend which matches the NASA data from 1971. Overall, these linear trends can be modeled and compiled into a new form of the Wiedemann-Franz law, which accounts for the density ratio of the binder jetted print. / Master of Science

Medical practitioners rely heavily on visualization of medical imaging to get a better understanding of the patient's anatomy. Most cancer treatment and surgery today are performed using medical imaging. Medical imaging is therefore of great importance to the medical industry. Medical imaging continues to depend heavily on a series of 2D scans, resulting in a series of 2D photographs being displayed using light boxes and/or computer monitors. Today, these 2D images are increasingly combined into 3D solid models using software. These 3D models can be used for improved visualization and understanding of the problem at hand, including fabricating physical 3D models using additive manufacturing technologies. Generating precise 3D solid models automatically from 2D scans is non-trivial. Geometric and/or topologic errors are common, and often costly manual editing is required to produce 3D solid models that sufficiently reflect the actual underlying human geometry. These errors arise from the ambiguity of converting from 2D data to 3D data, and also from inherent limitations of the .STL fileformat used in additive manufacturing. This thesis proposes a new, robust method for automatically generating 3D models from 2D scanned data (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)), where the resulting 3D solid models are specifically generated for use with additive manufacturing. This new method does not rely on complicated procedures such as contour evolution and geometric spline generation, but uses volume reconstruction instead. The advantage of this approach is that the original scan data values are kept intact longer, so that the resulting surface is more accurate. This new method is demonstrated using medical CT data of the human nasal airway system, resulting in physical 3D models fabricated via additive manufacturing. / Master of Science

Digital light Projection based Additive Manufacturing (AM) enables fabrication of complex three-dimensional (3D) geometries for applications ranging from rapid prototyping jet parts to scaffolds for cell cultures. Despite the ability in producing complex, three-dimensional architectures, the state of art DLP AM systems is limited to a single homogenous photo-polymer and it requires a large volume of resin bath to begin with. Extensible Multi-material Stereolithography (EMSL) is a novel high-resolution projection stereolithography system capable of manufacturing hybrid 3D objects. This system provides new capabilities, allowing more flexible design criteria through the incorporation of multiple feedstock materials throughout the structure. With EMSL manufacturing ability, multi-material programmable negative Poissons ratio honeycomb reentrant structures are realized. Researchers have been studying auxetic structures over decades, the mechanical property control of auxetic structure mainly relies on geometry design in previous studies. Now with the help of EMSL system, other design variables associated with auxetic structures, such as material properties of local structural members, are added into design process. The additional variables are then proved to have significant effects on the material properties of the auxetic structures. The ability to accurately manufacture multi-material digital design will not only allow for novel mechanical and material researches in laboratory, but also extend the additive manufacturing technology to numerous future applications with characteristics such as multiple electrical, electromechanical and biological properties. The design and optimization of EMSL system realizes novel structures have not been producible, therefore it will stimulate new possibilities for future additive manufacturing development. / Master of Science

The layer-by-layer nature of additive manufacturing (AM) allows for access to the entire build volume of a component during manufacture including the internal structure. Voids are accessible during the build process and allow for components to be embedded and sealed with subsequently printed layers. This process, in conjunction with direct write (DW) of conductive materials, enables the direct manufacture of parts featuring embedded electronics, including interconnects and sensors. The scope of previous works in which DW and AM processes are combined has been limited to single material AM processes. The PolyJet process is assessed for hybridization with DW because of its multi-material capabilities. The PolyJet process is capable of simultaneously depositing different materials, including rigid and elastomeric photopolymers, which enables the design of flexible features such as membranes and joints. In this work, extrusion-based DW is integrated with PolyJet AM technology to explore opportunities for embedding conductive materials on rigid and elastomeric polymer substrates. Experiments are conducted to broaden the understanding of how silver-loaded conductive inks behave on PolyJet material surfaces. Traces of DuPont 5021 conductive ink as small as 750?m wide and 28?m tall are deposited on VeroWhite+ and TangoBlack+ PolyJet material using a Nordson EFD high-precision fluid dispenser. Heated drying at 55°C is found to accelerate material drying with no significant effect on the conductor's geometry or conductivity. Contact angles of the conductive ink on PolyJet substrates are measured and exhibit a hydrophilic interaction, indicating good adhesion. Encapsulation is found to negatively impact conductivity of directly written conductors when compared to traces deposited on the surface. Strain sensing components are designed to demonstrate potential and future applications. / Master of Science

Effective quality improvement in the manufacturing industry is continually pursued. There is an increasing demand for real-time fault detection, and avoidance of destructive post-process testing. Therefore, it is desirable to employ sensors for in-process monitoring, allowing for real-time quality assurance. Chapter 3 describes the application of sensor based monitoring to additive manufacturing, in which sensors are attached to a desktop model fused deposition modeling machine, to collect data during the manufacturing process. A design of experiments plan is conducted to provide insight into the process, particularly the occurrence of process failure. Subsequently, machine learning classification techniques are applied to detect such failure, and successfully demonstrate the future potential of this platform and methodology. Chapter 4 relates the application of online, image-based quantification of the surface quality of workpieces produced by cylindrical turning. Representative samples of cylindrical shafts, machined by turning under various conditions, are utilized, and an apparatus is constructed for acquiring images while the part remains mounted on a lathe. The surface quality of these specimens is analyzed, employing an algebraic graph theoretic approach, and preliminary regression modeling displays an average surface roughness (Ra) prediction error of less than 8%. Prediction occurs in less than 2 seconds, showing the capability for future application in a real-time, quality control setting. Both of these cases, in additive manufacturing and in turning, are validated using real experimental data and analysis, showing application of sensor-based online process monitoring in multiple manufacturing areas. / Master of Science

A quantitative understanding of thermal field evolution is vital for quality control in additive manufacturing (AM). Because of the unknown material parameters, high computational costs, and imperfect understanding of the underlying science, physically-based approaches alone are insufficient for component-scale thermal field prediction. Here, I present a new framework that integrates physically-based and data-driven approaches with quasi in situ thermal imaging to address this problem. The framework consists of (i) thermal modeling using 3D finite element analysis (FEA), (ii) surrogate modeling using functional Gaussian process, and (iii) Bayesian calibration using the thermal imaging data. Based on heat transfer laws, I first investigate the transient thermal behavior during AM using 3D FEA. A functional Gaussian process-based surrogate model is then constructed to reduce the computational costs from the high-fidelity, physically-based model. I finally employ a Bayesian calibration method, which incorporates the surrogate model and thermal measurements, to enable layer-to-layer thermal field prediction across the whole component. A case study on fused deposition modeling is conducted for components with 7 to 16 layers. The cross-validation results show that the proposed framework allows for accurate and fast thermal field prediction for components with different process settings and geometric designs. / Master of Science / This paper aims to achieve the layer to layer temperature monitoring and consequently predict the temperature distribution for any new freeform geometry. An engineering statistical synergistic model is proposed to integrate the pure statistical methods and finite element modeling (FEM), which is physically meaningful as well as accurate for temperature prediction. Besides, this proposed synergistic model contains geometry information, which can be applied to any freeform geometry. This paper serves to enable a holistic cyber physical systems-based approach for the additive manufacturing (AM) not only restricted in fused deposition modeling (FDM) process but also can be extended to powder-based process like laser engineered net shaping (LENS) and selective laser sintering (SLS). This paper as well as the scheduled future works will make it affordable for customized AM including customized geometries and materials, which will greatly accelerate the transition from rapid prototyping to rapid manufacturing. This article demonstrates a first evaluation of engineering statistical synergistic model in AM technology, which gives a perspective on future researches about online quality monitoring and control of AM based data fusion principles.

Additive Manufacturing (AM) is a unique method of fabrication that, in contrast to traditional manufacturing methods, builds objects layer by layer. The ability of AM (when partnered with 3D scanning) to clone physical objects has raised concerns in the area of intellectual property (IP). To address this issue, the goal of this dissertation is to characterize and model a method to incorporate unique security features within AM builds. By adding optically detectable nanoparticles into transparent AM media, Physical Unclonable Function (PUFs) can be embedded into AM builds and serve as an anti-counterfeiting measure. The nanoparticle selected for this work is a Quantum Dot (QD), which absorbs UV light and emits light in the visible spectrum. This unique interaction with light makes the QDs ideal for a security system since the challenge (UV light) is a different signal from the response (the visible light emitted by the QDs). PolyJet, the AM process selected for this work, utilizes inkjet to deposit a photopolymer into layers, which are then cured with a UV light. An investigation into the visibility of the QDs within the printed PolyJet media revealed that the QDs produce PUF patterns visible via fluorescent microscopy. Furthermore, rheological data shows that the ink-jetting properties of the printing media are not significantly affected by QDs in sufficient concentrations to produce PUFs. The final objective of this study is to characterize the effects of the QDs on photocuring. The mathematical model to predict the critical exposure of the QD-doped photopolymer utilizes light scattering theory, QD characterization results, and photopolymer-curing characterization results. This mathematical representation will contribute toward the body of knowledge in the area of Additive Manufacturing of nanomaterials in photopolymers. Overall, this work embodies the first investigations of the effects of QDs on rheological characteristics of ink-jetted media, the effects of QDs on curing of AM photopolymer media, visibility of nanoparticles within printed AM media, and the first attempt to incorporate security features within AM builds. Finally, the major scientific contribution of this work is the theoretical model developed to predict the effects of QDs on the curing properties of AM photopolymers. / Ph. D.