Framework For Additive Manufacturing Research Articles

Additive manufacturing with varying material properties of thermosetting reactive polymers: a framework and comparison of different modes for implementing material transitions

Additive Manufacturing with Varying Material Properties enables controlled spatial variation of material properties in 3D-printed components, facilitating custom-tailored characteristics, added functionalities and reduced assembly processes. To promote this approach in building façade applications, this paper presents a novel framework for Additive Manufacturing with varying material properties using a thermosetting reactive polymer, specifically polyurethane. By dynamically changing the polyurethane’s chemical composition, the material properties can be precisely controlled. The framework’s individual aspects, including the material, hardware setup and computational system, are described in detail. Additionally, the research explores the implementation of material transitions with this framework, highlighting three different modes (horizontal, vertical and multi plane) and their impact on print time and material consumption. The paper concludes by discussing the potential of this approach for building façade applications, addressing current challenges and outlining future research directions.

Additive manufacturing for ultra-high vacuum components: Leveraging photo-polymer resin technologies

Over the past two decades, Additive Manufacturing (AM) technologies, commonly known as 3D printing, have witnessed exponential advancements, transforming the paradigms of instrument design and fabrication across an array of scientific and engineering disciplines. The utilization of Computer-Aided Design (CAD) and monolithic machining within the AM framework offers unprecedented levels of flexibility, precision, and mechanical stability. These attributes not only facilitate complex geometrical constructions but also substantially streamline the overall fabrication workflows. In this study, we provide experimental evidence to substantiate the viability of employing Masked Stereolithography Additive Manufacturing (MSLA) technology in concert with commercially available photo-polymer resins for the fabrication of components that are compatible with Ultra-High Vacuum (UHV) conditions. Utilizing high-temperature photo-polymer resins and specialized post-printing treatments—including an approximate 24-h vacuum bake—we have achieved a vacuum level of approximately 1 × 10−9 torr for a solid component encompassing a volume up to 16 cm3. This methodology paves the way for the expedited and cost-effective production of complex, UHV-compatible devices, thereby offering a substantial departure from conventional manufacturing techniques. The wide-ranging applicability of this technology holds considerable potential for transformative impacts across diverse sectors of research and development. By leveraging UHV-compatible MSLA technology, both academic researchers and industrial professionals are poised to benefit from an efficient and adaptable fabrication methodology, consequently catalyzing cutting-edge advancements in their respective fields of inquiry.

An integrated framework for collaborative robot-assisted additive manufacturing

Additive manufacturing (AM) is revolutionizing industry, allowing to prototype and fabricate custom-made parts with complex geometries rapidly and at an affordable cost. The use of robots to perform AM has great potentials due to its flexibility and ability to produce multi-directional fabrication paths, conducting to the production of parts that are unachievable using conventional 3-axis machines. In this study, it is proposed a novel multitasking collaborative robot-assisted AM framework featuring the system design, integration, generation of collision free robot paths/motion, robot control and filament extrusion control. Closed loop inverse kinematics was implemented to avoid singularities when generating AM paths for redundant robots featuring null space issues. The orientation control of the robot's end-effector (EEF) allows to eliminate the stair-like structures in fabricated parts by applying finishing layers, and by this way improving the appearance of curved surfaces, improving mechanical properties and better supporting loads in certain directions. Experimental tests carried out on 7-axis redundant robot manipulator show the viability of the system proposed.

Experimental investigations of the effectiveness of simultaneous topology/orientation optimization via SOMP and principal stress directions

This article presents an analysis of simultaneous topology and orientation optimization based on a principal stress method within the Solid Orthotropic Material with Penalization (SOMP) framework. Numerical case studies were done to assess the expected benefits of including orientation in the design process for minimum compliance structures under single load cases printed with orthotropic materials. In particular, comparisons were made between structures designed with and without consideration of orthotropic material orientations during the topology optimization (TO) process. Direct-Ink Writing (DIW) additive manufacturing (AM) was used to print experimental specimens, which were tested in bending to validate numerical results. The novelty of the work centers on the experimental evaluation of the performance of optimized topologies designed with SOMP and manufactured via DIW. Additionally, new knowledge is presented in the form of corresponding numerical and physical experiments showing that with a principal-stress based material orientation updating scheme, equivalent performance can be achieved with respect to compliance by 1) optimizing topology and orientation concurrently with orthotropic material orientations controlled during TO using maximum in-plane principal stress directions; or 2) optimizing topology assuming equivalent isotropic properties, and substituting the original orthotropic properties along principal stress orientations post-optimization. This experimentally validated finding confirms that including orientation in the compliance-based design framework for AM of structures with orthotropic materials is not advantageous. For single load cases, using the standard Solid Isotropic Material with Penalization (SIMP) method for design purposes and then aligning material orientations with principal stress orientations after the design is produced is sufficient for obtaining equivalent performance benefits.

An Assembly-Oriented Design Framework for Additive Manufacturing

The shape complexity capability of additive manufacturing (AM) is currently the main thrust of the design for AM (DFAM) research. In order to aid designers embracing that complexity-for-free characteristics of AM, many design approaches have been put forth. However, AM does not only benefit parts’ designs: its capability can be harnessed at assembly level to design performant and innovative products. Most of the few contributions on the topic are concerned with part consolidation of existing assemblies, but other advantages such as assembly-free mechanisms, multi-material components, or even component embedding can also improve product design complexity. This paper aims to put forth a thorough DFAM framework for new product development (made of multiple parts) and which consider all the assembly-related characteristics of AM. It considers what can be called AM-based architecture minimization, which includes, among others, part consolidation and assembly-free mechanisms as well. Within context of an ‘AM-factory’, in which the most appropriate machine(s) is/are selected for easing a whole assembly manufacturing before the detailed geometric definition is committed. For the sake of completeness, a methodology based on functional flows has also been investigated for the parts’ design. A gripper as case study has been introduced to illustrate the framework.

On the Impact of Additive Manufacturing Processes Complexity on Modelling

The interest in additive manufacturing (AM) processes is constantly increasing due to the many advantages they offer. To this end, a variety of modelling techniques for the plethora of the AM mechanisms has been proposed. However, the process modelling complexity, a term that can be used in order to define the level of detail of the simulations, has not been clearly addressed so far. In particular, one important aspect that is common in all the AM processes is the movement of the head, which directly affects part quality and build time. The knowledge of the entire progression of the phenomenon is a key aspect for the optimization of the path as well as the speed evolution in time of the head. In this study, a metamodeling framework for AM is presented, aiming to increase the practicality of simulations that investigate the effect of the movement of the head on part quality. The existing AM process groups have been classified based on three parameters/axes: temperature of the process, complexity, and part size, where the complexity has been modelled using a dedicated heuristic metric, based on entropy. To achieve this, a discretized version of the processes implicated variables has been developed, introducing three types of variable: process parameters, key modeling variables and performance indicators. This can lead to an enhanced roadmap for the significance of the variables and the interpretation and use of the various models. The utilized spectrum of AM processes is discussed with respect to the modelling types, namely theoretical/computational and experimental/empirical.

Towards the Possibility of Additive Manufacturing of XNA-Based Devices Using Molecular Engineering Principles

This paper considers a novel approach for integration between molecular engineering of XNA-based structures and additive manufacturing of XNA-based devices based on multiparametric characterization of XNAs by different functional descriptors (such as physical properties of XNA-based materials and precursors of XNA-based molecular devices) and the possibility of thermal or electron-beam processing as a prerequisite of the industrial technical process development for such device implementation. This can be performed in the framework of additive manufacturing by connecting the output of the XNA synthesizer or nucleic acid synthesizer with 3D-printer nozzles in such a way that oligos / AGCTX products are supported into the nozzles separately.

A design and optimization framework of variable-density lattice structures for additive manufacturing

With the development of additive manufacturing (AM), research interest is currently focused on lattice structures development due to their interesting mechanical properties. It implies the opportunity at the engineering level to be able to specify – beyond the shapes – mechanical properties distributed in the space to be manufactured. The article aims at introducing a design and optimization framework for AM, which highlights variable-density lattice structures. By processing both a topology optimization within a rough design space and a design of experiments driven parametric optimization, the development process of suitable and specific strength structures for AM becomes seamless and efficient.

Machine learning integrated design for additive manufacturing

For improving manufacturing efficiency and minimizing costs, design for additive manufacturing (AM) has been accordingly proposed. The existing design for AM methods are mainly surrogate model based. Due to the increasingly available data nowadays, machine learning (ML) has been applied to medical diagnosis, image processing, prediction, classification, learning association, etc. A variety of studies have also been carried out to use machine learning for optimizing the process parameters of AM with corresponding objectives. In this paper, a ML integrated design for AM framework is proposed, which takes advantage of ML that can learn the complex relationships between the design and performance spaces. Furthermore, the primary advantage of ML over other surrogate modelling methods is the capability to model input–output relationships in both directions. That is, a deep neural network can model property–structure relationships, given structure–property input–output data. A case study was carried out to demonstrate the effectiveness of using ML to design a customized ankle brace that has a tunable mechanical performance with tailored stiffness.

Level Sets of Weak-Morse Functions for Triangular Mesh Slicing

In the context of CAD CAM CAE (Computer-Aided Design, Manufacturing and Engineering) and Additive Manufacturing, the computation of level sets of closed 2-manifold triangular meshes (mesh slicing) is relevant for the generation of 3D printing patterns. Current slicing methods rely on the assumption that the function used to compute the level sets satisfies strong Morse conditions, rendering incorrect results when such a function is not a Morse one. To overcome this limitation, this manuscript presents an algorithm for the computation of mesh level sets under the presence of non-Morse degeneracies. To accomplish this, our method defines weak-Morse conditions, and presents a characterization of the possible types of degeneracies. This classification relies on the position of vertices, edges and faces in the neighborhood outside of the slicing plane. Finally, our algorithm produces oriented 1-manifold contours. Each contour orientation defines whether it belongs to a hole or to an external border. This definition is central for Additive Manufacturing purposes. We set up tests encompassing all known non-Morse degeneracies. Our algorithm successfully processes every generated case. Ongoing work addresses (a) a theoretical proof of completeness for our algorithm, (b) implementation of interval trees to improve the algorithm efficiency and, (c) integration into an Additive Manufacturing framework for industry applications.

Smart additive manufacturing: Current artificial intelligence-enabled methods and future perspectives

Additive manufacturing (AM) has been increasingly used in production. Because of its rapid growth, the efficiency and robustness of AM-based product development processes should be improved. Artificial intelligence (AI) is a powerful tool that has outperformed humans in numerous complex tasks. AI-enabled intelligent agents can reduce the workforce required to scale up AM production and achieve higher resource utilization efficiency. This study provides an introduction of AI techniques. Then, the current development of AI-enabled AM product development is investigated. Existing intelligent agents are used for problems in product design, process design and production stages. Based on the review, current research gaps and future research directions are identified. To guide future development of more efficient and comprehensive intelligent agents, a smart AM framework based on cloud-edge computing is proposed. Global consideration can be realized in the cloud environment, and a fast response can be achieved at the edge nodes.

Experimental validation and microstructure characterization of topology optimized, additively manufactured SS316L components

The integration of topology optimization (TO) and additive manufacturing (AM) has the potential to revolutionize modern design and manufacturing. However, few instances of manufactured optimized designs are documented, and even fewer examples of experimentally-tested designs are available. The lack of validation combined with the influence of AM process on material properties leaves a gap in our understanding of process-microstructure-property relationships that is essential for developing holistic design optimization frameworks. In this work, a functional design was topologically optimized and fabricated using both directed energy deposition (DED) and selective laser melting (SLM) methods. This is the first direct comparison of these AM methods in the context of TO. Mechanical properties of SS316L and the optimized components in as-fabricated and heat-treated conditions were investigated under uniaxial displacement-controlled tensile loading and compared to finite element modeling (FEM) predictions. Optimized samples provided regions of both compressive and tensile loading in the test specimen. Experimental results showed the FEM predictions to be conservative. Microstructural analysis revealed that this difference is due to refined microstructures formed during the additive manufacturing process that strengthen the material in regions with high stress levels. Moreover, SLM samples showed higher yield strength compared to DED samples due to a more refined grain size and denser dislocation structures. TO results are sensitive to the AM method, post-processing conditions, and differences in mechanical properties. Thus, a TO for AM framework can be best optimized with the incorporation of microstructure features to account for localized microstructural variations in fabricated components.

Enablers, Barriers, and Critical Success Factors for Effective Adoption of Color-Jet 3D Printing Technology

Color-jet 3D printing (CJP) technology-based machines are now being developed, and there is a need to identify the successful adoption of this technology for additive manufacturing (AM). Extensive literature review complemented with experts’ advice utilized systematically helped in the identification of 12 critical factors for the effective adoption of color-jet printing technology. A hierarchical structural model is developed using interpretive structural modeling (ISM) and analyzed using Matriced Impacts Croise’s Multiplication Appliquée a UN Classement (MICMAC). Identified software and the machine cost are primary drivers for this color-jet 3D printing machines (technology). The value of this technology is to provide the product at a lower cost and give useful applications in the area of medical, engineering and concept building. There is a need for developing better quality core material and post-processing material, further supported by enabling machine hardware and software. Accuracy and color texture of the part produced are essential to provide a technological advantage over existing technologies. Post-processing assists in a big way in imparting necessary properties to the part produced. Presently, the infiltrate/post-processing materials are limited, and for large-scale acceptability, one needs extensive multidisciplinary research and development. This research provides a structural model toward the adoption of color-jet 3D printing technology, which can also help users in evaluating this technology in broader AM framework.

State of art review on sustainable additive manufacturing

PurposeThe purpose of this paper is to report the state of art review on sustainable additive manufacturing (AM).Design/methodology/approachAM processes are becoming environmentally conscious and sustainable. In total, 63 papers are being collected from peer-reviewed journal sources. The review is presented on triple bottom line sustainable aspects, namely, environment, economy and society.FindingsIn the environmental dimension, papers on energy consumption, design optimization and life cycle assessment aspects are being collected and presented. The key inferences and insights are being derived from the mentioned perspectives and a framework for sustainable AM is proposed.Research limitations/implicationsThe review is limited to journal articles from the study on sustainable AM. Book chapters are being excluded.Practical implicationsThe study also discussed various perspectives of sustainable AM and provided insights on sustainable AM to practitioners.Originality/valueSystematic review on sustainable additive manufacturing is the original contribution of the authors.

Hot cracking mechanism affecting a non-weldable Ni-based superalloy produced by selective electron Beam Melting

A non weldable nickel-based superalloy was fabricated by powder bed-based selective electron beam melting (S-EBM). The as-built samples exhibit a heterogeneous microstructure along the build direction. A gradient of columnar grain size as well as a significant gradient in the γ′ precipitate size were found along the build direction. Microstructural defects such as gas porosity inherited from the powders, shrinkage pores and cracks inherited from the S-EBM process were identified. The origins of those defects are discussed with a particular emphasis on crack formation. Cracks were consistently found to propagate intergranular and the effect of crystallographic misorientation on the cracking behavior was investigated. A clear correlation was identified between cracks and high angle grain boundaries (HAGB). The cracks were classified as hot cracks based on the observation of the fracture surface of micro-tensile specimens machined from as-built S-EBM samples. The conditions required to trigger hot cracking, namely, presence of a liquid film during the last stage of solidification and thermal stresses are discussed within the framework of additive manufacturing. Understanding the cracking mechanism enables to provide guidelines to obtain crack-free specimens of non-weldable Ni-based superalloys produced by S-EBM.

The influence of passive-dynamic ankle-foot orthosis bending axis location on gait performance in individuals with lower-limb impairments

BackgroundPassive-dynamic ankle-foot orthoses are commonly prescribed to augment impaired ankle muscle function, however their design and prescription are largely qualitative. One design includes a footplate and cuff, and flexible strut connecting the two. During gait, deflection occurs along the strut, with the greatest deflection at a central bending axis. The vertical location of the axis can affect lower extremity biomechanics. The goal of this study was to investigate the influence of bending axis location on gait performance. MethodsFor thirteen participants with unilateral ankle muscle weakness, an additive manufacturing framework was used to fabricate passive-dynamic ankle-foot orthosis struts with central and off-center bending axes. Participants walked overground while electromyographic, kinetic and kinematic data were collected for three different bending axes: proximal (high), central (middle) and distal (low), and the participants indicated their order of bending axis preference after testing. Gait measures and preference effect sizes were examined during six regions of the gait cycle. FindingsA few differences between bending axes were observed: in the first double-leg support peak plantarflexion angle, peak dorsiflexion moment and positive hip work, in the early single-leg support peak knee extension moment and positive ankle and knee work, and in the late single-leg support gastrocnemius activity and vertical ground reaction force impulse. In addition, preference was strongly related to various gait measures. InterpretationDespite the observed statistical differences, altering bending axis location did not produce large and consistent changes in gait performance. Thus, individual preference and comfort may be more important factors guiding prescription.

A Design Framework to Replace Conventional Manufacturing Processes with Additive Manufacturing for Structural Components: A Formula Student Case Study

Additive Manufacturing (AM) offers great flexibility in producing parts and products that are geometrically complex. Therefore, several design methods have been developed aiming to exploit the AM capabilities and advantages over conventional manufacturing. However, it is crucial to further investigate the potential of AM to enable substitution of established manufacturing processes used in the production of structural components. In this study, a design framework for AM is presented, focusing on replacing conventionally manufactured structural components, operating under load conditions with re-designed ones, capable of exploiting AM process advantages. The proposed framework is validated by a case study dealing with the redesign of a formula-style race car's structural component. Topology optimization and FE Analysis are implemented in order to redesign a suspension component and predict the structural integrity of the new component. Finally, the freedom of design and the manufacturing capabilities of AM in manufacturing sectors demanding low weight and high stiffness characteristics of components are further outlined and more applications of the suggested design framework are described.

Evaluating the Design for Additive Manufacturing: A Process Planning Perspective

The emergence of Additive Manufacturing (AM) has greatly liberated the designers’ hands, since the usual design constraints in machining or other traditional processing technologies partially or even totally disappeared in AM and it seems that AM can form any desired very complex geometries through a layer by layer construction manner. However, AM processes still have their own processing characteristics and limits. To help designers to benefit more from the unique characteristics of AM and avoid the processing limits or low down the later processing difficulty after design, this paper proposes a two-level evaluation framework to assess the design from a process planning perspective. The proposed evaluation framework is associated with a two-level process planning framework for AM, and within each level, several indicators for assessment are defined and used to convey the information from process planning for improving the design.