From 3D Models to 3D Prints: an Overview of the Processing Pipeline

Due to the wide diffusion of 3D printing technologies, geometric algorithms for Additive Manufacturing are being invented at an impressive speed. Each single step, in particular along the Process Planning pipeline, can now count on dozens of methods that prepare the 3D model for fabrication, while analysing and optimizing geometry and machine instructions for various objectives. This report provides a classification of this huge state of the art, and elicits the relation between each single algorithm and a list of desirable objectives during Process Planning. The objectives themselves are listed and discussed, along with possible needs for tradeoffs. Additive Manufacturing technologies are broadly categorized to explicitly relate classes of devices and supported features. Finally, this report offers an analysis of the state of the art while discussing open and challenging problems from both an academic and an industrial perspective.Comment: European Union (EU); Horizon 2020; H2020-FoF-2015; RIA - Research and Innovation action; Grant agreement N. 68044

SFCDecomp: Multicriteria Optimized Tool Path Planning in 3D Printing using Space-Filling Curve Based Domain Decomposition

We explore efficient optimization of toolpaths based on multiple criteria for large instances of 3D printing problems. We first show that the minimum turn cost 3D printing problem is NP-hard, even when the region is a simple polygon. We develop SFCDecomp, a space filling curve based decomposition framework to solve large instances of 3D printing problems efficiently by solving these optimization subproblems independently. For the Buddha model, our framework builds toolpaths over a total of 799,716 nodes across 169 layers, and for the Bunny model it builds toolpaths over 812,733 nodes across 360 layers. Building on SFCDecomp, we develop a multicriteria optimization approach for toolpath planning. We demonstrate the utility of our framework by maximizing or minimizing tool path edge overlap between adjacent layers, while jointly minimizing turn costs. Strength testing of a tensile test specimen printed with tool paths that maximize or minimize adjacent layer edge overlaps reveal significant differences in tensile strength between the two classes of prints.Comment: Minor edits to incorporate reviewers' comments. Published in IJCG

Repair of metallic components using hybrid manufacturing

Many high-performance metal parts users extend the service of these damaged parts by employing repair technology. Hybrid manufacturing, which includes additive manufacturing (AM) and subtractive manufacturing, provides greater build capability, better accuracy, and surface finish for component repair. However, most repair processes still rely on manual operations, which are not satisfactory in terms of time, cost, reliability, and accuracy. This dissertation aims to improve the application of hybrid manufacturing for repairing metallic components by addressing the following three research topics. The first research topic is to investigate and develop an efficient best-fit and shape adaption algorithm for automating 3D models\u27 the alignment and defect reconstruction. A multi-feature fitting algorithm and cross-section comparison method are developed. The second research topic is to develop a smooth toolpath generation method for laser metal deposition to improve the deposition quality for metallic component fabrication and repair. Smooth connections or transitions in toolpath planning are achieved to provide a constant feedrate and controllable deposition idle time for each single deposition pass. The third research topic is to develop an automated repair process could efficiently obtain the spatial information of a worn component for defect detection, alignment, and 3D scanning with the integration of stereo vision and laser displacement sensor. This dissertation investigated and developed key technologies to improve the efficiency, repair quality, precision, and automation for the repair of metallic components using hybrid manufacturing. Moreover, the research results of this dissertation can benefit a wide range of industries, such as additive manufacturing, manufacturing and measurement automation, and part inspection --Abstract, page iv

Fibre-reinforced additive manufacturing: from design guidelines to advanced lattice structures

In pursuit of achieving ultimate lightweight designs with additive manufacturing (AM), engineers across industries are increasingly gravitating towards composites and architected cellular solids; more precisely, fibre-reinforced polymers and functionally graded lattices (FGLs). Control over material anisotropy and the cell topology in design for AM (DfAM) offer immense scope for customising a part’s properties and for the efficient use of material. This research expands the knowledge on the design with fibre-reinforced AM (FRAM) and the elastic-plastic performance of FGLs. Novel toolpath strategies, design guidelines and assessment criteria for FRAM were developed. For this purpose, an open-source solution was proposed, successfully overcoming the limitations of commercial printers. The effect of infill patterns on structural performance, economy, and manufacturability was examined. It was demonstrated how print paths informed by stress trajectories and key geometric features can outperform conventional patterns, laying the groundwork for more sophisticated process planning. A compilation of the first comprehensive database on fibre-reinforced FGLs provided insights into the effect of grading on the elastic performance and energy absorption capability, subject to strut-and surface-based lattices, build direction and fibre volume fraction. It was elucidated how grading the unit cell density within a lattice offers the possibility of tailoring the stiffness and achieving higher energy absorption than ungraded lattices. Vice versa, grading the unit cell size of lattices yielded no effect on the performance and is thus exclusively governed by the density. These findings help exploit the lightweight potential of FGLs through better informed DfAM. A new and efficient methodology for predicting the elastic-plastic characteristics of FGLs under large strain deformation, assuming homogenised material properties, was presented. A phenomenological constitutive model that was calibrated based upon interpolated material data of uniform density lattices facilitated a computationally inexpensive simulation approach and thus helps streamline the design workflow with architected lattices.Open Acces

Energy management system for biological 3D printing by the refinement of manifold model morphing in flexible grasping space

The use of 3D printing, or additive manufacturing, has gained significant attention in recent years due to its potential for revolutionizing traditional manufacturing processes. One key challenge in 3D printing is managing energy consumption, as it directly impacts the cost, efficiency, and sustainability of the process. In this paper, we propose an energy management system that leverages the refinement of manifold model morphing in a flexible grasping space, to reduce costs for biological 3D printing. The manifold model is a mathematical representation of the 3D object to be printed, and the refinement process involves optimizing the morphing parameters of the manifold model to achieve desired printing outcomes. To enable flexibility in the grasping space, we incorporate data-driven approaches, such as machine learning and data augmentation techniques, to enhance the accuracy and robustness of the energy management system. Our proposed system addresses the challenges of limited sample data and complex morphologies of manifold models in layered additive manufacturing. Our method is more applicable for soft robotics and biomechanisms. We evaluate the performance of our system through extensive experiments and demonstrate its effectiveness in predicting and managing energy consumption in 3D printing processes. The results highlight the importance of refining manifold model morphing in the flexible grasping space for achieving energy-efficient 3D printing, contributing to the advancement of green and sustainable manufacturing practices.Comment: 33 pages, 10 figures, Journa

Analysis to Support Design for Additive Manufacturing with Desktop 3D Printing

[ES] En los últimos años, la fabricación aditiva a través de la extrusión de materiales ha experimentado un desarrollo y adopción acelerados gracias a la amplia disponibilidad de máquinas y materiales de bajo costo. El tamaño de estas máquinas se ha reducido del tamaño del taller al tamaño del escritorio, lo que permite su uso en configuraciones de oficina o en el hogar. Este cambio ha permitido la adopción de la tecnología por la gama más amplia de usuarios que nunca, con o sin experiencia en diseño de ingeniería. Este nuevo paradigma ha creado el desafío de cómo habilitar que estos nuevos usuarios aprovechen las capacidades proporcionadas por esta tecnología. Esta tecnología permite la creación de geometrías complejas y productos personalizados con un coste inferior a los procesos de fabricación convencionales. Además, la gran cantidad de usuarios dispuestos a compartir sus diseños permite encontrar soluciones de diseño desde otros diseñadores. Sin embargo, la amplia gama de configuraciones de máquina, parámetros y materiales requiere brindar soporte para obtener resultados exitosos para cualquier combinación. Esta tesis aborda este desafío identificando las características de diseño y fabricación a considerar e investigando las consideraciones mecánicas y de pos procesamiento. Se propone y evalúa un nuevo marco de diseño que permite a los nuevos usuarios aprovechar las capacidades y considerar las limitaciones. Esta investigación encuentra que es posible crear un conjunto de herramientas de diseño que permita a los usuarios no capacitados diseñar productos utilizando la complejidad habilitada por la tecnología al tiempo que garantiza la funcionalidad y la capacidad de fabricación del producto.[CA] En els últims anys, la fabricació additiva a través de l'extrusió de materials ha experimentat un desenvolupament i adopció accelerats gràcies a l'àmplia disponibilitat de màquines i materials de baix cost. La grandària d'aquestes màquines s'ha reduït de la grandària del taller a la grandària de l'escriptori, la qual cosa permet el seu ús en configuracions d'oficina o en a casa. Aquest canvi ha permés l'adopció de la tecnologia per la gamma més àmplia d'usuaris que mai, amb o sense experiència en disseny o enginyeria. Aquest nou paradigma ha creat el desafiament de com habilitar que aquests nous usuaris aprofiten les capacitats proporcionades per aquesta tecnologia. Aquesta tecnologia permet la creació de geometries complexes i productes personalitzats amb un cost inferior als processos de fabricació convencionals. A més, la gran quantitat d'usuaris disposats a compartir els seus dissenys permet trobar solucions de disseny des d'altres dissenyadors. No obstant això, l'àmplia gamma de configuracions de màquina, paràmetres i materials requereix brindar suport per a obtindre resultats reeixits per a qualsevol combinació. Aquesta tesi aborda aquest desafiament identificant les característiques de disseny i fabricació a considerar i investigant les consideracions mecàniques i de post processament. Es proposa i avalua un nou marc de disseny que permet als nous usuaris aprofitar les capacitats i considerar les limitacions. Aquesta investigació troba que és possible crear un conjunt d'eines de disseny que permeta als usuaris no capacitats dissenyar productes utilitzant la complexitat habilitada per la tecnologia al mateix temps que garanteix la funcionalitat i la capacitat de fabricació del producte.[EN] In recent years, additive manufacturing through material extrusion has experienced accelerated development and adoption thanks to the wide availability of low-cost machines and materials. The size of these machines has been reduced from shop floor to desktop size, enabling their usage in office setups or at home. This change has allowed the adoption of the technology by the broadest range of users than ever, with or without an engineering design background. This new paradigm has created the challenge of how to enable these novel users to leverage the capabilities provided by this technology. This technology allows the creation of complex geometry and customised products with a cost lower than conventional manufacturing processes. Furthermore, the large number of users willing to share their designs allows finding design solutions from other designers. However, the wide range of machine configurations, parameters and materials requires providing support to obtain successful results under any combination. This thesis addresses this challenge by identifying the design and manufacturing characteristics to be considered and investigating the mechanical and post-processing considerations. A new design framework that enables new users to leverage the capabilities and consider the limitations is proposed and evaluated. This research finds that it is possible to create a design toolkit that enables untrained users to design products using the complexity enabled by the technology whilst ensuring the product's functionality and manufacturability.Fernández Vicente, M. (2022). Analysis to Support Design for Additive Manufacturing with Desktop 3D Printing [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185344TESI

Fabrication Sequence Optimization for Minimizing Distortion in Multi-Axis Additive Manufacturing

Additive manufacturing of metal parts involves phase transformations and high temperature gradients which lead to uneven thermal expansion and contraction, and, consequently, distortion of the fabricated components. The distortion has a great influence on the structural performance and dimensional accuracy, e.g., for assembly. It is therefore of critical importance to model, predict and, ultimately, reduce distortion. In this paper, we present a computational framework for fabrication sequence optimization to minimize distortion in multi-axis additive manufacturing (e.g., robotic wire arc additive manufacturing), in which the fabrication sequence is not limited to planar layers only. We encode the fabrication sequence by a continuous pseudo-time field, and optimize it using gradient-based numerical optimization. To demonstrate this framework, we adopt a computationally tractable yet reasonably accurate model to mimic the material shrinkage in metal additive manufacturing and thus to predict the distortion of the fabricated components. Numerical studies show that optimized curved layers can reduce distortion by orders of magnitude as compared to their planar counterparts