2022 International Solid Freeform Fabrication Symposium

Permanent URI for this collectionhttps://hdl.handle.net/2152/117170

Proceedings for the 2022 International Solid Freeform Fabrication Symposium. For more information about the symposium, please see the Solid Freeform Fabrication website.

The 33rd Annual International Solid Freeform Fabrication (SFF) Symposium – An Additive Manufacturing Conference, was held on July 25-27, 2022. Since the COVID pandemic was abating, the meeting was in-person only, the first time since 2019. There were 616 registrants from 13 countries, including 274 students. The total number of oral and poster presentations was 504. The meeting consisted of a Monday morning plenary, 55 parallel technical sessions and a poster session. The plenary session, “Emerging Women Leaders in AM” featured six outstanding mid-career researchers. Following the plenary session was a panel during which the plenary leaders discussed aspects of their research further.

The recipient of the 2022 International Outstanding Young Researcher in Freeform and Additive Manufacturing Award was Dr. Filomeno Martina, CEO of WAAM3D. Dr. Behrokh Khoshnevis from the University of Southern California won the International Freeform and Additive Manufacturing Excellence (FAME) Award.

There are 130 papers in this conference proceedings. Papers marked “REVIEWED” in the title area were peer reviewed by two external reviewers. We have sequentially numbered the pages of the papers to facilitate citation. Manuscripts for this and all preceding SFF Symposia are available for free download below and at the conference website: https://www.sffsymposium.org; select the “Proceedings Archive” pull-down menu item.

The editors would like to thank the Organizing Committee, the session chairs, the attendees for their enthusiastic participation, and the speakers both for their significant contribution to the meeting and for the relatively prompt delivery of the manuscripts comprising this volume. We are grateful to TMS conference management staff for their significant contributions to the meeting planning and proceedings production, particularly Trudi Dunlap and Tess De Jong. We look forward to the continued close cooperation of the additive manufacturing community in organizing the Symposium. We also want to thank the National Science Foundation (CMMI-2005490) for supporting this meeting financially by providing 94 student registration fee waivers.

Dave Bourell has been a member of the Conference Organizing Committee from the beginning in 1990. In 1995, he took over as the Chair of the Organizing Committee, a position he has held for 28 years, through this 2022 meeting. He has retired from The University of Texas at Austin effective September 1, 2022. He also stepped down as the Conference Chair. Dave expressed gratitude to the AM community for its commitment to the SFF Symposium over the years and for all the excellent connections made at the conference. Professor Joe Beaman took over as the Chair of the Organizing Committee effective September 1, 2022.

The next SFF Symposium is planned to be in person on August 14-16, 2023 at the Hilton Austin Hotel in Austin, Texas USA. The conference website will become active in mid-January 2023.


Recent Submissions

Now showing 1 - 20 of 185
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    Evaluation of Functionally Graded Lattice Properties of Laser Powder Bed Fused Stainless Steel 316L
    (2022) Ravichander, B.B.; Jagdale, S.H.; Theeda, S.; Kumar, G.
    The development of metal Additive Manufacturing (AM) techniques, in particular the laser powder bed fusion (LPBF) process, has led to an increase in the innovative design and fabrication of lightweight and complex porous metal structures. Despite the limitations of the LPBF process which limits the geometric accuracy of the porous structures, it eliminates the difficulties presented by conventional manufacturing techniques in the fabrication of highly complex structures. The properties of as-built porous structures depend on the unit cell design and porosity level. These lightweight metal structures have applications in medical and aerospace fields. The relationships between the lattice geometry and performance must be determined to successfully implement the functional lattice designs. In this study, functionally graded lattice structures are fabricated from steel using SLM technique and the effect of different lattice types on the manufacturability, density and mechanical properties are investigated.
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    Insight into Compressive Behaviour of Schwarz-P Lattices Fabricated by Material Extrusion
    (2022) Jameekornkul, P.; Wang, J.; Panesar, A.
    Lattice structures are increasingly being chosen for lightweight applications due to their high strength- to-weight ratio and energy absorption capability. This work investigates the mechanical performance of the Schwarz-Primitive (SP) lattices with a range of unit-cell sizes and relative densities. The SP lattices were fabricated using material extrusion with ASA (industrial grade) and ABS material, then tested along different orientations to build direction. Digital Image Correlation (DIC) was utilised to measure the local strain and deformation mechanism. The preliminary results indicate that stiffness and strength were related to densities abiding the Ashby-Gibson model in well-controlled tight bands, which will help inform design decisions for future adoption. Further experiments will be conducted to extend the finding of this study, gain a better understanding of graded lattices and provide insights on the potential use of fibre reinforcement in lattices.
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    Design and Analysis of a Topology Optimized Transtibial Prosthetic Socket Using Combined Static Gait Analysis
    (2022) Carbonell, R.M.; Crawford, R.H.
    This paper presents the design and analysis of an optimized transtibial prosthetic socket developed using the ground structure method of topology optimization (GSM). The socket wall between the distal 25% of the original socket and a proximal brim is replaced with an optimized truss geometry and a thin wall (1 mm). Separate trusses are developed for the loading conditions of three critical stances: heel strike, vertical (standing), and toe-off. The truss models are combined with critical components to create the final design. The proposed socket is 81.58% of the original socket volume and is designed for manufacturing using Selective Laser Sintering (SLS) and nylon- 12. The socket design is analyzed, with the material properties for sintered nylon-12, at 10% increments between heel strike and toe-off to determine the viability of both the socket and the corresponding methodology. Simulation results indicate that the design exceeds requirements for all tested stances.
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    Thin-Walled Part Properties in PBF-LB/P — Experimental Understanding and Nonlocal Material Model
    (2022) Jaksch, A.; Spinola, M.; Cholewa, C.; Pflug, L.; Stingl, M.; Drummer, D.
    to fully realizing the potential of lightweight design in powder bed fusion of polymers (PBF-LB/P). In this work, parts built with rectangular cross sections of different sizes and orientations are described by their geometry, surface roughness, mechanical characteristics, and specific component geometry dependent on energy input. Experimental findings are supported by a nonlocal material model developed to adequately describe weakened material behavior at the surface of PBF-LB/P parts. This approach allows the simulation of the elastic modulus and density for complex part geometries while simultaneously considering boundary effects. Furthermore, the volume-surface ratio for thin-walled components were linearly correlated to the rectangular cross sections in different building orientations. This uniformity indicates that this ratio is a suitable quantity to consider. Therefore, the process knowledge is improved, especially in new design standards for thin-walled structures in PBF-LB/P.
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    Validation and Comparison of Fem-Simulation Results of the Fused Deposition Modeling Process under Consideration of Different Mesh Resolutions
    (2022) Moritzer, E.; Hecker, F.
    The Fused Deposition Modeling (FDM) process is an Additive Manufacturing (AM) technology. In the FDM process, components are generated by feeding a thermoplastic polymer filament into a heated nozzle and depositing the molten material layer-by-layer in a defined way onto the building platform or an already existing component structure. The strand-by- strand deposition leads to a complex cooling situation which contributes to the non-uniform shrinkage of components in the FDM-process. Using an AM plug-in for the FEM-simulation software Abaqus, the thermal and mechanical aspects of a component can be simulated according to the temporal sequence of the manufacturing process. For this, the birth-death- method is used in the simulations. During the investigations, the simulation results regarding geometrical deviations are compared to the actual deviation of the manufactured specimens. Furthermore, the influences of the mesh resolution on the simulation results and the required time for the simulations are considered.
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    Single Part Tracking Enabled by Fluorescent Polysecure Tracing Particles in Am Parts
    (2022) Gartner, P.; Krischke, N.; Benfer, M.; Bender, M.; Lanza, G.; Fleischer, J.; Dost, G.
    Traceability is widely recognized as a core enabler of many industry 4.0 technologies. The necessary identification of products is often realized through label-based systems, but tracing products with particular geometric constraints that prohibit the use of such systems remains an issue. A promising alternative of label based identification is the pattern based identification. This contribution portrays a novel method to utilize fluorescent particles integrated in polymer-based products and optical pattern recognition to facilitate the identification of products with specific geometric constraints. The particles are integrated into the polymer and the unique random distribution of fluorescent particles triggered by an LED flash is used to recognize individual products. To demonstrate the approach, polymer-based gear wheels were printed using ARBURG plastic freeforming and an automatic identification system was designed. The presented approach could be a reliable alternative to other surface-structure-based approaches for product identification and enable comprehensive tracing of components throughout value-chains.
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    X-Ray Analysis of Magnetically Induced Additive Manufacturing
    (2022) Sellers, R.; McCullough, C.; Gonzalez, E.; Light, A.; Wolff, S.; Wang, H.
    Through advancements in technology over the last several years, additive manufacturing has become increasingly mainstream in the manufacturing process. Additive manufacturing has several traits which would theoretically make it superior to traditional subtractive manufacturing techniques. While this ability to manufacture complex parts is certainly applicable to the external structure, additive manufacturing will allow for control over the internal structure of a part as well. From this, porous components can be created which match desired mechanical properties somewhat independently of the material actually used for manufacturing. However, many of these advancements require further refinement of the additive manufacturing processes intrinsic to them. One of the techniques suggested as a method of improving additive manufacturing processes is the incorporation of magnets into the manufacturing process. These magnets are used to direct the flow of the melted metal with more precision. Experiments were conducted in order to evaluate the effects of the introduction of magnets on parts printed using Laser Powder Bed Fusion. Stainless steel 316L, a relatively cheap and easy to print steel, was printed onto a Ti64 substrate using both spot welding and line scanning. It was observed that magnets had an effect on the melt pool and the keyhole depth through an analysis of the spot welding. Additionally, the various magnets also changed the flow of particles in the melted areas generated through line scanning. While quantifying the magnetic fields' effects will require additional research and time, there is strong evidence that they could be a viable solution to increasing additive manufacturing’s precision.
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    Investigation of the Process Parameters and Geometry Dependent Shrinkage Behavior of Raster Lines in the Fused Deposition Modeling Process
    (2022) Moritzer, E.; Hecker, F.
    Additive Manufacturing processes are able to generate components from raw material (filament, powder etc.) without the need of tools or conventional machining. One of the most common Additive Manufacturing processes is the Fused Deposition Modeling (FDM). Here, a thermoplastic polymer filament is fed into a heated nozzle where the filament is plasticized. The plasticized material is then deposited, layer-by-layer onto the building platform or the already existing component structure in a defined way. Thermoplastic polymers show a material specific shrinkage induced by the cooling process. The recurring heat input by depositing adjacent strands results in a complex cooling situation which contributes to the non-uniform shrinkage of the component. In the investigations, first, a Design of Experiments (DoE) is carried out to determine the influence of selected process parameters on the shrinkage behavior of the raster lines. Following, the geometrical deviations of simple geometries under consideration of different process parameters are determined and analyzed.
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    Effect of Build Orientation on Residual Stress and Microstructure in Inconel 625 Fabricated via Laser Powder Bed Fusion
    (2022) Andurkar, M.; Prorok, B.C.; Thompson, S.M.
    The reliability of parts produced by Laser Powder Bed Fusion (L-PBF) is still not at a great acceptance level. One of the major defects inherited in parts fabricated from L-PBF is a high level of residual stress. In this study, two build orientations i.e., vertical and diagonal, were used to fabricate Inconel 625 specimens to observe its effects on the residual stress magnitude and grain growth. A novel, Cos-α X-ray diffraction method was used to measure residual stress values along the top surface of the samples. Electron Backscattered Diffraction (EBSD) and kernel average misorientation (KAM) maps were employed to explain residual stress trends and differences between samples. Results indicate that the as-printed vertical sample possessed a higher tensile residual stress (77 ± 15 MPa) compared to the diagonally-printed sample (52 ± 12 MPa). The KAM map of the as-printed vertically oriented sample showed more pronounced local misorientations caused by dislocations compared to the diagonally-printed sample.
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    Hybrid Additive and Subtractive Manufacturing of Direct-Heated Tooling
    (2022) Weflen, E.D.; Peters, F.E.; Frank, M.C.
    Pre-heating is a common requirement for production tooling in applications such as compression and injection molding. While the carbon fiber reinforcements commonly used in large-area additive manufacturing improve the thermal conductivity of polymers, they are still far below that of metal tooling. This study presents a method for direct, local Joule heating of tooling without the need for additional heating elements. A current is induced in the composite tooling, resulting in resistance heating of the substrate. High conductivity material is locally embedded to achieve local control over the heating characteristics. Embedding of the conductive material is accomplished by selectively switching material compositions during the printing process. Demonstration tooling is produced using hybrid additive and subtractive manufacturing using an AMBIT XTRUDE in a HAAS machining center and evaluated with thermal imaging. Direct heating of tooling expands the potential applications of additive manufacturing by overcoming the challenges of low thermal conductivity materials.
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    Clamping Concept for 6 Side Hybrid Manufacturing
    (2022) Mischliwski, S.; András, D.; Weigold, M.
    For most technical applications, the surface quality and tolerances that result directly from additive processes are not suitable. Hybrid manufacturing as a combination of additive and subtractive manufacturing process steps can help solving this issue. In this work, a conceptional adjustable cast clamping process is introduced for a combination of Laser-based Powder-Bed-Fusion (LPBF) and milling. For component clamping during the milling process, the components are cast in place with a low-melting metal alloy, creating form-fit and force-fit connection. To prove the applicability, a rough estimation of occurring milling forces was conducted. In a subsequent series of tests, validation of clamping force was carried out using complex part geometries. A prototype fixture designed for this cast clamping process has been developed and tested. This fixture allows complex non-restricted 6-side machining of parts without moving it relative to the fixture or the need of any additional manual rework on part surfaces.
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    Inserting Components into Geometries Constructed onto a Non-Standard Substrate for Electronics Packaging
    (2022) Plant, R.; Chang, S.; Hague, R.; Tuck, C.; Wildman, R.
    Additive manufacturing (AM) has matured from its initial concept as a prototyping technique to an industrial manufacturing process. Consequently, AM processes must meet relevant standards for an increasing number of applications. Here, we investigate inserting components into geometries constructed onto a silicon nitride substrate, using stereolithography (SLA), for the purpose of electronics packaging. Compared to conventional processes, SLA avoids high temperatures and stresses while permitting much greater flexibility to arrange components in three dimensions. This facilitates an increased feature density and the construction of packages for use in complex spaces. A characteristic of interest to this application, is the SLA material-substrate interaction and the resulting quality of adhesion. The adhesion mechanism between SLA and silicon nitride is investigated and substantially enhanced by a pre-treatment process. A process for then inserting large and complex geometries and components into the SLA build process is identified and compliance of the product with relevant standards is reviewed.
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    Resin Development for On-Orbit Fabrication of Spacecraft Structures by Direct Solar Photopolymerization
    (2022) Yerazunis, W.; Weiss, A.; Radyjowski, P.; Cottrell, R.
    One of the paradoxes of spacecraft design is that spacecraft are destined to operate in orbit where maneuvering thruster firings produce stresses below 0.01 G, but the spacecraft must be strong enough (and heavy enough) to survive the roughly 10 G’s of linear acceleration and 50 G’s of vibration in a rocket launch. In this paper, we follow on previous work to develop and test an alternative: the post-launch freeform additive manufacture of a major communications satellite structural element in UV cured resin, using solar UV to trigger polymerization. Here we develop the chemistry of a UV curable liquid resin that not only has a very low (below our chamber limit of 0.2 kPa) vapor pressure post-degassing, but also is not dependent on oxygen presence to activate the thermal inhibitors that prevent premature polymerization. In tests, we successfully freeform 3D printed a small (60 mm) parabolic dish at chamber limit pressure using simulated solar UV flooding the chamber.
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    Machine Learning in Additive Manufacturing: A Review of Learning Techniques and Tasks
    (2022) Pike, J.A.; Klett, J.; Kunc, V.; Duty, C.E.
    Due to recent advances, Machine Learning (ML) has gained attention in the Additive Manufacturing (AM) community as a new way to improve parts and processes. The capability of ML to produce insights from large amounts of data by solving tasks such as classification, regression, and clustering provide possibilities to impact every step of the AM process. In the design phase, ML can optimize part design with respect to geometry, material selection, and part count. Prior to printing, process simulations can offer understanding into the how the part will be printed, and energy, time, and cost estimates of a print can be made to assist with resource planning. During printing, AM can benefit from in-situ printing optimization and quality monitoring. Lastly, ML can characterize printed parts from in-situ or ex-situ data. This article describes some of the ML learning techniques and tasks commonly employed in AM and provides examples of their use in previous works.
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    Anomal Detection for In-situ Quality Control of Directed Energy Deposition (DED) Additive Manufacturing
    (2022) Dehghan-Niri, E.; Hespeler, S.C.; Juhasz, M.; Halliday, H.S.; Lang, M.
    One common cause for the rejection of parts produced during metal Additive Manufacturing (AM) is the presence of unacceptable defects within the part. While powerful, post-processing nondestructive techniques can be unapproachable due to time constraints or simply impractical for certain inspection and quality control applications of the AM, especially with parts of high complexity. The AM process requires a layer-by- layer execution to build parts, allowing for a unique opportunity to collect data and monitor the process in real/semi-time. The incipient phase of AM monitoring and control typically consists of developing an automated unsupervised statistical anomaly detection algorithm that is capable of detecting irregularities through parameter measurement and sensing features. In this paper, we develop a simple and effective method for detecting anomalies through use of statistical distances from data collected during the laser-based Directed Energy Deposition (DED) AM process.
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    Optimization of Laser Process Parameters Using Machine Learning Algorithms and Performance Comparison
    (2022) Theeda, S.; Ravichander, B.B.; Jagdale, S.H.; Kumar, G.
    Laser powder bed fusion (L-PBF) can be used to produce near net-shaped functional metal components. Despite offering high flexibility in producing components with intricate geometries, L-PBF has many constraints in terms of controllability and repeatability because of large number of processing parameters. There is a need for a robust computational model which can predict the properties of L-PBF parts using a wide range of processing parameters. In this work, several Machine learning-based algorithms like Random Forest, k Nearest Neighbors, XGBOOST, Support Vector Machine (SVM), and Deep Neural Networks are used to model the property- processing parameters relation for SS 316L samples prepared by LPBF. Laser power, scan speed, hatch spacing, scan strategy, volumetric energy density, and density are used as the input to these models. The developed model is then used to predict and analyze the surface roughness of as- fabricated SS 316L specimens. The prediction and experimental results are compared for the above-mentioned models to evaluate the capabilities and accuracy of each model.
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    HDF5 Hierarchies for Additive Manufacturing digital representations and Enhanced Analytics
    (2022) Monnier, L.V.; Ko, H.
    Advancement in Additive Manufacturing (AM) technologies and data acquisition techniques have led to an increase in AM data generated. However, due to the large volume and the diversity of AM data available it is becoming challenging to efficiently store, analyze, and represent AM processes. HDF5 has the potential to allow an easy access to big data by offering a hierarchical data catalog. Thus, AM processes could be represented through a hierarchy based on the data analytic needs and directly link the corresponding AM data. This paper investigates the use of data formats to represent big data and AM dataset. Existing AM ontologies and models are reviewed in order to effectively encapsulate AM information and incorporate the hierarchy into an HDF5 AM wrapper. Three hierarchies are proposed to represent specific perspectives of AM processes: the digital twin of AM Product Lifecycle, the AM V model representation, and the material centric characteristics.
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    Binder Jetting of 316L process simulation tools evaluation
    (2022) Caballero, K.; Medrano, V.A.; Arrieta, E.; Sandoval, H.; Wicker, R. B.; Medina, F.
    Binder Jetting has become one of the most popular Additive Manufacturing technologies over the years due to its low cost and fast production times, nevertheless this technology has a steep learning curve due to the shrinkage induced to parts during sintering. Since shrinkage is not uniform along the part, it’s hard to efficiently determine what areas will be distorted hence this needs to be taken into consideration when designing a new part and many iterations need to be printed until dimensional accuracy is achieved, as a result production time and cost significantly increase. New Binder Jetting simulation tools are being developed and tested; this software will help the technology be more robust and user-friendly for the industry. The software computes a sintering simulation and can provide displacement results making support positioning more efficient, in addition, newer versions of the software can export a compensated model which will be able to be sintered without supports. To evaluate the simulation software, a dimensional test artifact model was designed and printed, then compared with the software predicted model simulation results. The simulation software was used in an initial evaluation of the test artifact geometry to identify areas of concern in the model and document them so efficiency when predicting material behavior during the sintering process can be evaluated. In addition, an evaluation of the effects of different sintering process parameters on the physical and mechanical properties of the material will be analyzed considering the inert sintering atmosphere of the process. Finally, printing parameters of the machine such as layer thickness, binder saturation, and recoat speed among others will also be evaluated.
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    Feasibility Study of Large-Sized Aluminum Facades by Using Wire Arc Additive Manufacturing
    (2022) Yamagata, Y.; Sagawa, T.; Nitawaki, M.; Abe, T.
    Over the past few years, there has been growing interest in the fabrication of construction components by using wire arc additive manufacturing (WAAM). We focused on the finishing materials as a potential application for WAAM and began to consider fabricating aluminum building facades. However, there are several issues, such as fabrication size of 4-5m, aesthetics, and structural performance. Therefore, a trial fabrication and a non- destructive static loading test were conducted. In the study, an aluminum chair was used as a model because it contains the engineering basis of the building facades. In the trial fabrication, a method of leveling the build surface for each of the multiple layers was found to be effective for large-sized fabrication. Bead blasting was also effective in removing oxides from aluminum surfaces and adjusting the appearance. In the loading test, both displacement and strain measurements agreed well with the FEM analytical values. The results showed that WAAM has the possibility of fabricating large-sized aluminum building facades with the structural performance expected in the FEM analysis.
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    Geometric Challenges in Designing Parts for Machining using Wire-fed DED
    (2022) Vaughan, D.M.; Meyer, L.; Masuo, C.; Nycz, A.; Noakes, M.W.; Vaughan, J.; Walters, A.; Carter, B.; Wallace, R.
    Wire-fed DED using MIG welding systems allows for high deposition rates above 30lbs/hr, enabling much larger parts to be printed than would be possible on other DED systems. However, a drawback to this high deposition rate is a relatively low bead resolution on the printed part. Post-processing using machining is usually required on any mating surfaces printed using wire-fed DED. Problems such as residual stress in the build plate and printed part, underbuilding, and path interpolations can all lead to insufficient material deposition and deviation from the desired shape. These areas where the printed part varies from the model can leave defects on post-processed surfaces. This paper will cover common geometry issues that can arise from wire-fed DED and design changes that can be made to ensure that the printed design contains the required material to achieve the finished part.