Complex Internal Features Research Articles

Study on hybrid 3D printing and milling process for customized polyether-ether-ketone components.

Polyether-ether-ketone (PEEK) has been widely applied in various fields due to its excellent mechanical properties and biocompatibility. The efficient and high-quality customized manufacturing of PEEK components are investigated in this study by the hybrid 3D printing and milling process. At first, the alternating hybrid process is selected and verified by comparing two typical hybrid process categories and conducting experiments, respectively. Second, a set of procedures are designed to automate the engineering application of the hybrid process trying to avoid the disadvantages of manual programing. Then, considering the tool length and possible interferences during the hybrid process, a model segmentation algorithm, namely, the exchange principle of avoiding interference (EPAI) is proposed. Based on the introduced EPAI and the programing language Python, the additive and subtractive hybrid manufacturing (ASHM) data processing procedure is proposed and realized by post-processing of the conventional 3D printing codes. Finally, the feasibility experiments have been conducted. The experimental results verify the hybrid manufacturing process in the fabrication of parts with complex internal features. The surface roughness Ra and dimensional error L of the parts have been reduced by 75.5% and 85.2%, respectively, while the shear strength τ has been increased by 14.1%. Compared with conventional milling process, the material consumption is reduced by 48.7%.

Automated brightfield layerwise evaluation in three-dimensional micropatterning via two-photon polymerization.

Two-photon polymerization (TPP) is an advanced 3D fabrication technique capable of creating features with submicron precision. A primary challenge in TPP lies in the facile and accurate characterization of fabrication quality, particularly for structures possessing complex internal features. In this study, we introduce an automated brightfield layerwise evaluation technique that enables a simple-to-implement approach for in situ monitoring and quality assessment of TPP-fabricated structures. Our approach relies on sequentially acquired brightfield images during the TPP writing process and using background subtraction and image processing to extract layered spatial features. We experimentally validate our method by printing a fibrous tissue scaffold and successfully achieve an overall system-adjusted fidelity of 87.5% in situ. Our method is readily adaptable in most TPP systems and can potentially facilitate high-quality TPP manufacturing of sophisticated microstructures.

Nested Biofabrication: Matryoshka-Inspired Intra-Embedded Bioprinting.

Engineering functional tissues and organs remains a fundamental pursuit in bio-fabrication. However, the accurate constitution of complex shapes and internal anatomical features of specific organs, including their intricate blood vessels and nerves, remains a significant challenge. Inspired by the Matryoshka doll, here a new method called "Intra-Embedded Bioprinting (IEB)" is introduced building upon existing embedded bioprinting methods. a xanthan gum-based material is used which served a dual role as both a bioprintable ink and a support bath, due to its unique shear-thinning and self-healing properties. IEB's capabilities in organ modeling, creating a miniaturized replica of a pancreas using a photocrosslinkable silicone composite is demonstrated. Further, a head phantom and a Matryoshka doll are 3D printed, exemplifying IEB's capability to manufacture intricate, nested structures. Toward the use case of IEB and employing an innovative coupling strategy between extrusion-based and aspiration-assisted bioprinting, a breast tumor model that included a central channel mimicking a blood vessel, with tumor spheroids bioprinted in proximity is developed. Validation using a clinically-available chemotherapeutic drug illustrated its efficacy in reducing the tumor volume via perfusion over time. This method opens a new way of bioprinting enabling the creation of complex-shaped organs with internal anatomical features.

3D simulation of image-defined complex internal features using the numerical manifold method

3D simulation of image-defined complex internal features using the numerical manifold method

Novel Approach to Grain Boundary Modification in Stainless and Duplex Steel L-PBF Components through In Situ Heat Treatment

Additive manufacturing (AM) has provided new possibilities for improving the grain boundary properties of metallic components. However, effectively modifying the microstructure, particularly the grain boundary properties, of laser powder bed fusion (L-PBF) components remains a challenge. Post-processing methods have shown some success in adjusting grain boundary angles, but they have limitations when it comes to complex geometries and internal features. In this study, we propose an innovative in situ heat treatment to control the grain boundary properties of L-PBF components. A model is proposed to predict the thermal cycle at a single point, and it is validated through experiments on 2507 super duplex steel and 316L austenitic steel samples. The results demonstrate that, by applying controlled in situ heat treatment, the dynamic recovery processes can be influenced, and thereby the grain boundary properties of the manufactured parts can be controlled. This proposed method improves our understanding of the impact of in situ heat treatment on grain boundary properties and offers potential for designing and fabricating high-performance L-PBF components. The findings from this study lay the groundwork for the further exploration of grain boundary engineering in metallic components using L-PBF. By leveraging in situ heat treatment, future research can open up new avenues in additive manufacturing, facilitating the production of advanced and high-quality metallic components.

(Invited) An Overview of Electrochemistry Application to Additive Manufacturing

Additive manufacturing (AM) is the process of creating three-dimensional (3D) objects from digital models through the sequential deposition of material in layers. This talk will highlight how researchers have used electrochemical research in additive manufacturing and will provide insights into how technology can be exploited to formulate novel microstructures and optimize the manufacturing process. Electrochemical 3D printing is a relatively new form of AM that creates metallic structures through the electrochemical reduction of metal ions from solutions onto conductive substrates. It involves localized electrochemical deposition of metals combined with additive manufacturing principles to achieve Electrochemical Additive Manufacturing (ECAM). The talk will also focus on the formulation of metal precursor inks to produce novel metallic microstructures and nanoalloys containing multiple metals. These inks are used with AM techniques to fabricate 2D and 3D printed conductive structures directly onto a substrate. Examples include aligned nickel nanowires over large areas, which provide opportunities to produce structures with enhanced anisotropic electrical and magnetic properties. Nanoalloy films printed using metal precursor inks have a variety of important applications involving local control of alloy composition in AM part. Examples include the facile formation of layered nanostructures and electrical conductivity with oxidative stability. The talk will conclude with current research on electropolishing of AM parts. AM while capable of producing complex-shaped metal parts with intricate internal geometries and lattice structures struggles to make parts with the smooth surface finish required for many applications. Polishing interior surfaces inaccessible to traditional surface polishing methods is a challenge. Electropolishing is increasingly being used as a post-treatment option for metal AM parts due to its non-contact nature and ability to finish complex internal features.

Ultrasonic testing of thick and thin Inconel 625 alloys manufactured by laser powder bed fusion

Additive manufacturing of alloys enables low-volume production of functional metallic components with complex geometries. Ultrasonic testing can ensure the quality of these components and detect typical defects generated during laser powder bed fusion (LPBF). However, it is difficult to find a single ultrasonic inspection technique that can detect defects in the large variety of geometries generated using LPBF. In this work, phased array ultrasonic testing (PAUT) is suggested to inspect thick LPBF components, while guided waves are explored for thin curved ones. PAUT is used to detect cylindrical lack of fusion defects in thick LPBF rectangular parts. Practical defects are generated by reducing the laser power at prespecified locations in the samples. The defects’ shape and density are verified using optical microscopy and X-ray computed tomography. Partially fused defects down to 0.25 mm in diameter are experimentally detected using a 10 MHz PAUT probe with the total focusing method post-processing. The experimental results are compared to defect images predicted by finite element simulations. For thin components with curved geometry, guided waves are used to detect powder-filled cylindrical defects. The waves are generated using piezoelectric transducers, and the spatiotemporal wavefield is measured using a scanning laser Doppler vibrometer. Using root-mean-square imaging of the wavefield, defects down to 1 mm are clearly detected despite the complex internal features in the samples.

Design for Inspectability: A Framework to Increase Inspectability of Additive Manufacturing Parts for Pulse-Echo Ultrasonic Inspection Methods

Abstract Additive manufacturing (AM) is used to produce load-bearing, safety-critical components in industries like aerospace, automotive, and medical devices. Designers can create AM components with complex internal features, organic topologies, and lattice structures to reduce part mass or part count. However, such complex features can make designs difficult or impossible to inspect using mature nondestructive testing (NDT) methods. Professional organizations suggest designers keep quality assurance and quality control (QA/QC) in mind early in the design process. The Design for Inspectability (DfI) framework is suggested as a way of meeting the need for early-stage QA/QC considerations. This work presents a case study, where a group of designers considered one type of NDT, known as Pulse-Echo Ultrasonic (PEU) testing. Using heuristics derived from relevant literature, designers were able to create designs with increased inspectability. This improved inspectability came at the cost of other design objectives, however, such as strength and mass. This implies that certain design objectives may be inversely related to increased inspectability, raising significant concerns for the field. This work marks the first step toward mapping out the trade-offs between inspection and performance objectives.

Machine learning-enabled feature classification of evaporation-driven multi-scale 3D printing

The freeform generation of active electronics can impart advanced optical, computational, or sensing capabilities to an otherwise passive construct by overcoming the geometrical and mechanical dichotomies between conventional electronics manufacturing technologies and a broad range of three-dimensional (3D) systems. Previous work has demonstrated the capability to entirely 3D print active electronics such as photodetectors and light-emitting diodes by leveraging an evaporation-driven multi-scale 3D printing approach. However, the evaporative patterning process is highly sensitive to print parameters such as concentration and ink composition. The assembly process is governed by the multiphase interactions between solutes, solvents, and the microenvironment. The process is susceptible to environmental perturbations and instability, which can cause unexpected deviation from targeted print patterns. The ability to print consistently is particularly important for the printing of active electronics, which require the integration of multiple functional layers. Here we demonstrate a synergistic integration of a microfluidics-driven multi-scale 3D printer with a machine learning algorithm that can precisely tune colloidal ink composition and classify complex internal features. Specifically, the microfluidic-driven 3D printer can rapidly modulate ink composition, such as concentration and solvent-to-cosolvent ratio, to explore multi-dimensional parameter space. The integration of the printer with an image-processing algorithm and a support vector machine-guided classification model enables automated, in situ pattern classification. We envision that such integration will provide valuable insights in understanding the complex evaporative-driven assembly process and ultimately enable an autonomous optimisation of printing parameters that can robustly adapt to unexpected perturbations.

Effect of Build Parameters on the Mechanical Behavior of Polymeric Materials Produced by Multijet Fusion

Multijet fusion (MJF) is a novel additive manufacturing (AM) process for the powder bed fusion of thermoplastic polymers. In recent years, MJF has been established as a promising manufacturing technique for the rapid prototyping and production of fully functional, large‐scale components at high resolution. Like other powder bed fusion techniques, MJF permits the printing of parts without support material, and does not require chemical postprocessing steps, making it especially suitable for fabricating parts with complex and intricate internal features. However, the effects of common build volume parameters (such as part orientation, location, and interpart spacing) on mechanical properties are currently not well understood. This study aims to provide a thorough and comprehensive description of the trends in mechanical properties observed in polyamide (PA)‐11 and PA‐12 samples printed using the MJF process. Tensile, flexural, and impact specimens are printed using varying build volume packing parameters and tested according to the corresponding ASTM standards. The fracture surfaces of tested specimens are studied and characterized to further understand the method of failure propagation through MJF‐printed PA‐11 and PA‐12. As this work demonstrates, determining an optimal bed packing algorithm will be instrumental for optimizing desired mechanical properties of printed parts.

X-Ray Computed Tomography Instrument Performance Evaluation, Part III: Sensitivity to Detector Geometry and Rotation Stage Errors at Different Magnifications.

With steadily increasing use in dimensional metrology applications, especially for delicate parts and those with complex internal features, X-ray computed tomography (XCT) has transitioned from a medical imaging tool to an inspection tool in industrial metrology. This has resulted in the demand for standardized test procedures and performance evaluation standards to enable reliable comparison of different instruments and support claims of metrological traceability. To meet these emerging needs, the American Society of Mechanical Engineers (ASME) recently released the B89.4.23 standard for performance evaluation of XCT systems. There are also ongoing efforts within the International Organization for Standardization (ISO) to develop performance evaluation documentary standards that would allow users to compare measurement performance across instruments and verify manufacturer's performance specifications. Designing these documentary standards involves identifying test procedures that are sensitive to known error sources. This paper, which is the third in a series, focuses on geometric errors associated with the detector and rotation stage of XCT instruments. Part I recommended positions of spheres in the measurement volume such that the sphere center-to-center distance error and sphere form errors are sensitive to the detector geometry errors. Part II reported similar studies on the errors associated with the rotation stage. The studies in Parts I and II only considered one position of the rotation stage and detector; i.e., the studies were conducted for a fixed measurement volume. Here, we extend these studies to include varying positions of the detector and rotation stage to study the effect of magnification. We report on the optimal placement of the stage and detector that can bring about the highest sensitivity to each error.

Study on properties of SLM-NiTi shape memory alloy under the same energy density

Abstract In recent years, selective laser melting (SLM)-NiTi had developed rapidly due to the ability to achieve the complex shape and internal features, as well as high dimensional accuracy. The choice of parameters was particularly critical to the forming and performance of SLM-NiTi. In this work, we had designed and prepared five sets of SLM-NiTi shape memory alloys with the same energy density (range of 40–90 J/mm3). The microstructure, phase transition characteristic, mechanical properties and shape memory effect of SLM-NiTi shape memory alloys were investigated through various characterization methods of X-ray diffraction, scanning electron microscopy, differential scanning calorimetry and stress-controlled cyclic tensile tests, etc. The results showed that the surface forming quality of SLM-NiTi was not only related to the energy density, but also related to the value of P/V, which higher than 0.3 or lower than 0.1 would lead to the formation of surface pores. Interestingly, the SLM-NiTi showed ultrahigh failure strength of 735 MPa and elongation of 10.88% under room temperature tensile conditions. In addition, stress-controlled cyclic tensile tests under 400 MPa indicated that the SLM-NiTi had excellent shape memory effect of 76.1% recovery ratio and 3.95% recoverable strain after ten times loading–unloading cycles. The design of multi-parameter variables can not only optimize the surface quality, but also provide a basis for the prediction of SLM-NiTi phase transition temperature.

A case study on use of 3D scanning for reverse engineering and quality control

Reverse engineering is needed to acquire knowledge of design that is lost, obsolete or withheld. Techniques have evolved from manual measurements, to utilizing the possibilities that lie within 3D scanning technologies. This paper surveys literature to map the possibilities and challenges connected to methodologies and technologies using 3D scanning for reverse engineering and production control. A case study on reverse engineering using a handheld 3D laser scanner is conducted to compare with the findings in literature. In the case study, a 3D printed component with complex internal features is 3D scanned and the point cloud is optimized before two different surface modelling techniques are tested. The dimensional errors of the output CAD design are mapped before the process and results are compared with the findings in literature. The findings of this paper show that using 3D scanning technologies for RE and PC is possible but significant challenges exists in developing accurate surface reconstruction algorithms that deals with point cloud imperfections like i.e., noise and holes. Using 3D scanning for RE purposes is found to be most suitable for components with complex geometry like free-form surfaces that are hard to measure manually.

Process behavior charts used to check the consistency of CT instruments

Digital manufacturing is one of the enabling methodologies associated with the concept of flexible mass customization, which has been boosted by the recent advances in Additive Manufacturing (AM) technologies, from which complex freeform geometries, internal and reentrant features can be reproduced based on the CAD model. From the standpoint of coordinate metrology, AM calls for a measurement technology capable of acquiring high data density of these complex structures. Computed Tomography (CT) is the technology of choice to holistically measure them and respond to the needs of mass customization. However, due to the complexity of the CT measurement chain, the numerous influence factors, and their difficult quantification, the measurement uncertainty evaluation remains an issue yet to be resolved. In this regard, one topic that has received attention is the determination of the geometric errors of the CT instrument, which cause errors to dimensional measurements. Using an imaging method to quantify the geometric errors, process behavior charts are detailed and used to check the consistency of the CT measurement process with regard to the geometric errors. The utilization of process behavior charts is the major contribution of this work since they allow us to operate the measurement process up to its full potential, and to evaluate the actual effectiveness of the imaging method to quantify the errors.

Microwave Characterization of Conductive PLA and Its Application to a 12 to 18 GHz 3-D Printed Rotary Vane Attenuator

This paper demonstrates an ultra-light weight microwave rotary vane attenuator (RVA) manufactured using polymer-based 3-D printing. In addition, for the first time, conductive polylactic acid (PLA) is rigorously characterized across both X- and Ku-bands (8 to 18 GHz); while acrylonitrile butadiene-styrene (ABS) has similarly been characterized across Ku-band (12 to 18 GHz). Using the results from the conductive PLA characterization process, an electromagnetic model was created for predicting the performance of the RVA. It is shown that, even with its complex internal geometrical features, a mix of both dielectric and conductive PLA building materials, an assembly of multiple parts and a mechanically rotating central section, our experimental proof-of-concept prototype RVA exhibits excellent measured performance across Ku-band. This tunable microwave control device represents a higher-level of functionality for additive manufacturing, when compared to a fixed (i.e., non-movable) 3-D printed structure, opening the way for other groups to routinely 3-D print custom microwave components and subsystems in the not too distant future.

The setup and relaxation of spring upwelling in a deep, rotationally influenced lake

AbstractStrong and sustained winds can drive dramatic hydrodynamic responses in density‐stratified lakes, with the associated transport and mixing impacting water quality, ecosystem function, and the stratification itself. Analytical expressions offer insight into the dynamics of stratified lakes during severe wind events. However, it can be difficult to predict the aggregate response of a natural system to the superposition of hydrodynamic phenomena in the presence of complex bathymetry and when forced by variable wind patterns. Using an array of current, temperature, and water quality measurements at the upwind shore, we detail the hydrodynamic response of deep, rotationally influenced Lake Tahoe to three strong wind events during late spring. Sustained southwesterly winds in excess of 10 m s−1 drove upwelling at the upwind shore (characteristic of non‐rotational upwelling setup), with upward excursions of deep water exceeding 70 m for the strongest event. Hypolimnetic water, with elevated concentrations of chlorophyll a and nitrate, was advected toward the nearshore, but this water rapidly returned to depth with the relaxation of upwelling after the winds subsided. The relaxation of upwelling exhibited rotational influence, highlighted by an along‐shore, cyclonic front characteristic of a Kelvin wave‐driven coastal jet, with velocities exceeding 25 cm s−1. The rotational front also produced downwelling to 100 m, transporting dissolved oxygen to depth. More complex internal wave features followed the passage of these powerful internal waves. Results emphasize the complexity of these superimposed hydrodynamic phenomena in natural systems, providing a conceptual reference for the role upwelling events may play in lake ecosystems.

Assessment of trapped powder removal and inspection strategies for powder bed fusion techniques

The issue of trapped powder within a part made using powder bed fusion additive manufacturing (AM) is one of the ‘dirty secrets’ of AM, yet it has not received significant attention by the research community. Trapped powders limit the application of AM for complex geometries, including heat exchangers and dies with conformal cooling channels. Being able to detect and remove trapped powder from the build is a necessary step to avoid downstream processing and performance challenges. In this work, ‘powder challenge geometries’ with complex internal features were fabricated via laser powder bed fusion (L-PBF) and electron beam selective melting (EBSM) and were used to assess the effectiveness of several powder removal and inspection methods. Hand-held ultrasonic polishing was explored as a powder removal technique and was shown to effectively clear extremely elongated channels that grit-blasting (the current industry standard) cannot clear. X-ray computed tomography (XCT) and weighing were used to inspect and quantitatively assess the effectiveness of powder removal techniques on the challenge geometries. Using the lesser known ‘vacuum boiling’ powder removal process and the more common ultrasonic bathing process, trapped L-PBF powder was easily removed from the deep channels. Conversely, trapped EBSM powder was difficult to remove using ultrasonic polishing as the powder was sintered inside the channels. It was shown that the powder recovered by the ultrasonic polishing process had size distributions, surface chemistry, morphology and porosity similar to the virgin powder. It is suggested, on these bases, that the recovered powder could likely be recycled without detrimental effects on the process operation.

Surface integrity of additive manufacturing parts: a comparison between optical topography measuring techniques

Abstract Additive Manufacturing (AM) presents significant industry-specific advantages allowing the creation of complex geometries and internal features that cannot be produced using conventional manufacturing processes. However, a current limitation of AM is the degraded dimensional control and surface integrity of specific surfaces. The parts are constructed through layer-by-layer approach, each layer presenting a characteristic ‘fingerprint’. The functional performance of the final part is influenced by the morphology of the outer surface as well as by the surface quality introduced at intermediate layers. Surface texture metrology therefore can play an enabling role in AM-related manufacture and research. The use of optical topography measurement instrumentation allows for a high level of detail in the acquisition of topographic information. Some of the most commonly used optical measuring instruments are Vertical Scanning Interferometry (CSI), Imaging Confocal Microscopy (CONF), and Focus Variation (FV), each one has benefits and drawbacks in terms of acquisition time and measurement resolution. AM surfaces overall present complex topographical features, requiring the acquisition of large surface areas and large z-scans which considerably increases the acquisition time. Speed is a key factor in industrial practice, and time optimization is required for quality control and surface analysis before down-stream processes. This paper reports on the measurement and characterisation of the surface texture of metal powder bed fusion AM parts. All measurements were performed in the same SENSOFAR S-NEOX instrument using the commonly used optical technologies (CSI, CONF, and FV) and the latest step in confocal measurement technology called Continuous Confocal (C-CONF). The resolution and acquisition time of each technique is analysed in order to check the suitability of each method to characterize and describe the AM surface microstructures in a time-efficient way.

Region-based online flaw detection of 3D printing via fringe projection

Additive manufacturing allows for the production of custom parts with complex internal features. However, a lack of online detection of the printing process is one of the challenges that has prevented further improvements in additive manufacturing. This paper proposes a novel online monitoring technique based on a fringe projector to keep the stability of the process under control on a layer-by-layer basis. To detect microdefects with a magnitude smaller than the noise, we propose a region-based defect detection method that takes each subregion, instead of each point, as a detection unit. Compared with a single point, a sub region contains hundreds of points, which represent a domain with greater stability. We combine voxel cloud connectivity segmentation (VCCS) and fast point feature histogram (FPFH) to divide the printing area into hundreds of subregions, smooth the surface to resist the noise based on moving least square (MLS) and evaluate each subregion using local point features. The projection model and normal deviation are developed to extract the sizes and locations of the flaws. The performances of the techniques are demonstrated with some experiments using different 3D printing objects, which indicate that the proposed method is able to detect various flaws and its detection accuracy is higher than the noise magnitude.

Assessment of 3D printed steels and composites intended for wear applications in abrasive, dry or slurry erosive conditions

The design of earth cutting and machining tools generally requires the application of several types of materials with different wear resistance: (1) base metal with low wear resistance, (2) extremely resistant cutting inserts made of ceramics (or even diamond), cemented carbides or cermets and (3) thick coatings with average wear resistance to protect base metal or thin (PVD or CVD) coatings to improve wear resistance of inserts. The production of such tools is complicated, tedious and not very efficient (tool life depends on the interface bonding, brazed inserts can be severely damaged after impact, base material wear, etc.). The novel approach is to exclude the steps of brazing or coating and to produce steels or composites with similar wear resistance as that of inserts or coatings using the promising approach of additive manufacturing (AM i.e. 3D printing). Moreover, benefits of AM like near net shape part building with complex internal features (internal cooling channels) are desired for cutting tools. The aim of the current research is to assess novel commercially available 3D printed steels and composites in several relevant tribological conditions where these materials could be applied. The comparison with conventional Hardox 400 wear resistant steel and AISI 316 stainless steel is provided. Results report significant improvement in the wear resistance of AM produced steels and composites against reference materials. The performance of 3D printed materials lie between WC- based bulk cemented carbides and hardfacings. The characteristic features of wear mechanisms are presented and discussion is supported by Scanning Electron Microscope images.