Statistical correlation between the printing angle and stress and strain of 3D printed models

In the strides of the most advanced technological achievements, the use of polymers is becoming increasingly evident both in everyday life and in engineering practice. Complex structures made of polymers attract more attention from scientists and researchers, as their application increases in the most diverse fields of science. This phenomenon requires constant improvement of knowledge and technologies for the production of polymeric structures and parts, but it is equally important to establish reliable databases on the behavior of newly-introduced materials under different load conditions. This work is based on the establishment of statistical correlation between parameters of 3D printed models and their mechanical characteristics in conditions of static axial loading

Improving precision of material extrusion 3D printing by in-situ monitoring and predicting 3D geometric deviation using Conditional Adversarial Networks

The field of additive manufacturing, especially 3D printing, has gained growing attention in the research and commercial sectors in recent years. Notwithstanding that the capabilities of 3D printing have moved on to enhanced resolution, higher deposition rate, and a wide variety of materials, the crucial challenge of verifying that the component manufactured is within the dimensional tolerance as designed continues to exist. Material extrusion 3D printing has long been established for rapid prototyping and functional testing in many research and industry fields. However, its inconsistency and intrinsic defects (surface roughness and geometric inaccuracies) hinder its application in several areas, most notably “certify-as-you- build” small-batch prototyping and large-batch production.In this study, we present an approach to reduce both inconsistency and the 3D geometric inaccuracies of products fabricated by material extrusion.1. This work developed and demonstrated an approach for layer-by-layer mapping of 3D printed parts, which can be used for validation of printed models and in situ adjustment of print parameters. This in situ metrology system scans each layer at the time of printing, providing a 3D model of the as-printed part. A high-speed optical scanning system was integrated with a Material Extrusion type 3D printer to achieve in situ monitoring of dimensional inaccuracies during printing, which leaves the door open to implement a closed-loop feedback system to compensate geometric errors during printing in the future and fabricate “certify-as-you-build” products.2. This work trained machine learning algorithms with data from this scanning system and predicted 3D geometric inaccuracies in new designs. Eight Conditional Adversarial Networks (CAN) machine learning models were trained on a limited number of scanned profile images of different layers, consisting of less than 50 actual images and 50 generated images, to predict the 3D geometric deviations of freeform shapes. The generated images were produced by randomly combining and cropping the actual images without any distortion. These CAN models produced predictions where at least 44.4%, 87.6%, 99.2% of data were within �0.05 mm, �0.10 mm, �0.15 mm of the actual measured value, respectively.3. This work developed an Iterative Forward approach to redesign the Computer-Aided- Design model by reverse engineering using the trained machine learning models, allowing for compensation of print imperfection at the design stage, in advance of the first printing. The compensation algorithms with eight different sets of different parameters were evaluated. It has been proven that the Iterative Forward approach improved the geometric deviation of the predicted profiles by making compensation to the CAD model

Process–Structure–Properties in Polymer Additive Manufacturing

Additive manufacturing (AM) methods have grown and evolved rapidly in recent years. AM for polymers is an exciting field and has great potential in transformative and translational research in many fields, such as biomedical, aerospace, and even electronics. Current methods for polymer AM include material extrusion, material jetting, vat polymerisation, and powder bed fusion. With the promise of more applications, detailed understanding of AM—from the processability of the feedstock to the relationship between the process–structure–properties of AM parts—has become more critical. More research work is needed in material development to widen the choice of materials for polymer additive manufacturing. Modelling and simulations of the process will allow the prediction of microstructures and mechanical properties of the fabricated parts while complementing the understanding of the physical phenomena that occurs during the AM processes. In this book, state-of-the-art reviews and current research are collated, which focus on the process–structure–properties relationships in polymer additive manufacturing

Leveraging Biomimicry and Additive Manufacturing to Improve Load Transfer in Brittle Materials

With the emergence of Additive Manufacturing (i.e., 3D printing) in construction, new strategically designed shapes can be created to improve load transfer through structural members and foundations. Cross-sections can be optimized to carry load using less material, or even using weaker constituent materials, like soils, which are cheap and abundant. The goal of this research is to investigate the benefits of using cellular patterns which leverage biomimicry in civil engineering applications, since nature has perfectly engineered materials and patterns which carry loads with the least amount of material possible. Most of the periodic cellular work to date has focused on metallic materials, which exhibit ductile performance. Therefore, this study is specifically related to brittle materials as there is a need to understand the load transfer mechanisms in this type of material. An initial investigation of biomimicry was carried out, and organisms thatpresented improved mechanical behavior due to geometry were identified. Analogue prototypes inspired by these biological findings were designed and specimens were 3D printed using a binderjetting device which offers a resulting part with a brittle behavior, mimicking a cemented soil. Solid samples using the same gross area were also printed to compare performance with the cellular shapes. Uniaxial compression tests were performed in the specimens and in cylinders used to track the properties of the material. The variability of the 3D printer utilized in this study and the material’s susceptibility to experimental differences were found to be important factors and some printer settings made it difficult to compare the cellular and solid specimens directly. Overall, the results show that the cellular structures exhibited a significant improvement in the load-toweight ratio compared to the solid configuration. Applying this improvement in material efficiency to building products can lead to more sustainable and cost-effective construction practices

Additive Manufacturing Process Parameter Effects on the Mechanical Properties of Fused Filament Fabrication Nylon

The purpose of this research was to determine how varying Fused Filament Fabrication (FFF) process parameters affect the mechanical properties of PA6 nylon dog-bone specimens produced on the Mark One 3D Printer. A design of experiment (DOE) was conducted using the factors of layer height and raster angle orientation. The mechanical properties measured in the experiment were tensile modulus, yield stress, percent strain at yield, ultimate tensile strength and percent strain at break. An analysis of variance (ANOVA) was performed to identify which factors were statistically significant in influencing mechanical properties. Results of the ANOVA showed that layer height was significant in influencing tensile modulus, ultimate tensile strength and percent strain at break; raster angle orientation was significant in influencing tensile modulus, yield stress, percent strain at yield, and percent strain at break. Both tensile modulus and ultimate tensile strength increased with decreasing layer height. The optimal condition that maximizes stiffness and strength is a layer height of 0.1 mm and a (±45) raster angle orientation

An Evaluation of Ultrasonic Shot Peening and Abrasive Flow Machining As Surface Finishing Processes for Selective Laser Melted 316L

Additive Manufacturing, and specifically powder bed fusion processes, have advanced rapidly in recent years. Selective Laser Melting in particular has been adopted in a variety of industries from biomedical to aerospace because of its capability to produce complex components with numerous alloys, including stainless steels, nickel superalloys, and titanium alloys. Post-processing is required to treat or solve metallurgical issues such as porosity, residual stresses, and surface roughness. Because of the geometric complexity of SLM produced parts, the reduction of surface roughness with conventional processing has proven especially challenging. In this Thesis, two processes, abrasive flow machining and ultrasonic shot peening, are evaluated as surface finishing processes for selective laser melted 316L. Results of these experiments indicate that AFM can reliably polish as-built internal passages to 1 µm Ra or better but is unsuitable for passages with rapidly expanding or contracting cross-sections. AFM can also polish relatively small passages, but lattice components may prove too complex for effective processing. USP cannot achieve such low surface roughness, but it is a versatile process with multiple advantages. Exterior surfaces were consistently processed to 1.7 to 2.5 µm Ra. Interior surfaces experienced only partial processing and demonstrated high geometric dependence. USP significantly hardened the surface, but steel media hardened the surface better than ceramic media did. Both AFM and USP are recommended processes for the surface finishing of SLM manufactured parts. Good engineering judgement is necessary to determine when to use these processes and how to design for post-processing

Influence of the Compaction Pressure and Sintering Temperature on the Mechanical Properties of Porous Titanium for Biomedical Applications

In the present work, the use of porous titanium is proposed as a solution to the difference in stiffness between the implant and bone tissue, avoiding the bone resorption. Conventional powder metallurgical technique is an industrially established route for fabrication of this type of material. The results are discussed in terms of the influence of compaction pressure and sintering temperature on the porosity (volumetric fraction, size, and morphology) and the quality of the sintering necks. A very good agreement between the predicted values obtained using a simple 2D finite element model, the experimental uniaxial compression behavior, and the analytical model proposed by Nielsen, has been found for both the Young’s modulus and the yield strength. The porous samples obtained by the loose sintering technique and using temperatures between 1000 °C −1100 °C (about 40% of total porosity) are recommended for achieving a suitable biomechanical behavior for cortical bone partial replacement.Ministry of Economy and Competitiveness of the State General Administration of Spain grant MAT2015-71284-