Current Additive Manufacturing Technologies Research Articles

Improvements in Injection Moulds Cooling and Manufacturing Efficiency Achieved by Wire Arc Additive Manufacturing Using Conformal Cooling Concept.

The plastic injection moulding industry is a constantly developing industrial field. This industrial process requires the manufacturing of metal moulds using complex heating and cooling systems. The purpose of this research is to optimize both the plastic injection moulding process and the mould manufacturing process itself by combining practices in this industry with current additive manufacturing technologies, specifically Wire Arc Additive Manufacturing (WAAM) technology. A mould punch was manufactured by using both WAAM technology, whose internal cooling system has been designed under the concept of Conformal Cooling, and conventional cooling channel designs and manufacturing techniques in order to carry out a comparative analysis. Theoretical results obtained by CAE methods showed an improvement in heat extraction in the WAAM mould. In addition, the WAAM mould was able to achieve better temperature homogeneity in the final part, minimizing deformations in the final part after extraction. Finally, the WAAM manufacturing process was proven to be more efficient in terms of material consumption than the conventional mould, reducing the buy-to-fly ratio of the part by 5.11.

Comparative Study of Mechanical Properties and Microstructure Between Conventional and Infinite z-Axis Fused Deposition Modeling Printers

Additive Manufacturing (AM) has emerged as a critical technology in shaping manufacturing strategies, offering versatility and efficiency in designing complex structural components. Extensive literature exists on small- to mid-sized product production. However, a significant knowledge gap exists in manufacturing elongated products, such as wind turbine blades and constructional beams. Current AM technology faces limitations in this context, primarily due to the constraints imposed by the conventional 90-degree nozzle head and limited bed space. This study introduces an innovative AM approach called Infinite z-Axis Printing. This novel technique utilizes a belt-driven heated bed and a 45-degree nozzle head to 3D print objects of infinite length. The study compares this groundbreaking approach and the traditional 90-degree nozzle head Fused Deposition Modeling (FDM) method and the associated results. The findings of this research demonstrate that the Infinite z-Axis Printing methodology yields a significant improvement of up to 20% in tensile and compressive strength compared to the currently used FDM process. This advancement can potentially revolutionize on-site operations by enabling the efficient production of elongated structural components, thus contributing significantly to the construction and renewable energy sectors.

Design-encoded dual shape-morphing and shape-memory in 4D printed polymer parts toward cellularized vascular grafts.

Current additive manufacturing technologies wherein as-printed simple two-dimensional (2D) structures morph into complex tissue mimetic three-dimensional (3D) shapes are limited to multi-material hydrogel systems, which necessitates multiple fabrication steps and specific materials. This work utilizes a single shape memory thermoplastic polymer (SMP), PLMC (polylactide-co-trimethylene carbonate), to achieve programmable shape deformation through anisotropic design and infill angles encoded during 3D printing. The shape changes were first computationally predicted through finite element analysis (FEA) simulations and then experimentally validated through quantitative correlation. Rectangular 2D sheets could self-roll into complete hollow tubes of specific diameters (ranging from ≈6 mm to ≈10 mm) and lengths (as long as 40 mm), as quantitatively predicted from FEA simulations within one minute at relatively lower temperatures (≈80 °C). Furthermore, shape memory properties were demonstrated post-shape change to exhibit dual shape morphing at temperatures close to physiological levels. The tubes (retained as the permanent shape) were deformed into flat sheets (temporary shape), seeded with endothelial cells (at T < Tg), and thereafter triggered at ≈37 °C back into tubes (permanent shape), utilizing the shape memory properties to yield bioresorbable tubes with cellularized lumens for potential use as vascular grafts with improved long-term patency. Additionally, out-of-plane bending and twisting deformation were demonstrated in complex structures by careful control of infill angles that can unprecedently expand the scope of cellularized biomimetic 3D shapes. This work demonstrates the potential of the combination of shape morphing and SMP behaviors at physiological temperatures to yield next-generation smart implants with precise control over dimensions for tissue repair and regeneration.

Biobased composite powders from PHA, waxes and lignocellulosic biomasses for powder-based additive manufacturing processes

Reducing our impact on the environment requires the use of biobased materials and their composites, which can be sourced from biomass feedstocks. However, due to technological limitations, these materials are not easily integrated into current Additive Manufacturing technologies like Selective Laser Sintering.The focus of the present study is to develop a new, environmentally friendly process that can prepare composite biobased powders for SLS. These powders are made from polyhydroxyalkanoate, waxes, and lignocellulosic fillers. The process is based on emulsification and dissolution/precipitation in eutectic solvents and has the potential to be utilized with a wide range of biobased materials.

Online monitoring for error detection in vat photopolymerization

ABSTRACT Sensor implementation together with data processing in manufacturing provides continuous measurements enabling process monitoring, optimization, and automation. Additive manufacturing (AM) technologies are shifting from one-off and prototyping production to batch, mass, and continuous production. Current AM technologies are mostly focused on small production devices, without monitoring systems. This study aims to bring AM closer to automation by proposing an online monitor system for bottom-up photopolymerization AM (VPP) systems. The sensor-generated data is used to capture the detachment error of built parts from the build platform that otherwise cannot be observed physically by the machine operator. The detachment itself will not stop the build job, which results in lost material and operating time. The online monitoring procedure consists of two phases, an offline and an online one, respectively. The offline phase is used for training a prediction model to be used in connection with a control chart for online monitoring. The monitoring control chart is advantageous as only the detachment predictions need to be recorded. The research carried out in this article brings novelty in both the vat photopolymerization set-up, as well as in an online monitoring procedure that can be easily extended to similar technologies.

Carbon-Based Piezoresistive Polymer Nanocomposites by Extrusion Additive Manufacturing: Process, Material Design, and Current Progress.

Advancement in additive manufacturing (AM) allows the production of nanocomposites with complex and custom geometries not typically allowable with conventional manufacturing techniques. The benefits of AM have led to recent interest in producing multifunctional materials capable of being printed with current AM technologies. In this article, piezoresistive composites realized by AM and the matrices and fillers utilized to make such devices are introduced and discussed. Carbon-based nanoparticles (Carbon Nanotubes, Graphene/Graphite, and Carbon Black) are often the filler choice of most researchers and are heavily discussed throughout this review in combination with extrusion AM methods. Piezoresistive applications such as physiological and wearable sensors, structural health monitoring, and soft robotics are presented with an emphasis on material and AM selection to meet the demands of such applications.

A crack-free and high-strength Al-Cu-Mg-Mn-Zr alloy fabricated by laser powder bed fusion

Laser Powder Bed Fusion (LPBF) is considered as one of the most current additive manufacturing technologies that could prepare customized and complex parts. There have been challenges for LPBF-fabricating 2xxx (Al–Cu) alloy because that own alloy elements cause large solidification ranges and hot cracking is susceptible to generate during solidification. In this study, a crack-free and high-strength Al–Cu–Mg–Mn–Zr alloy was designed and manufactured by LPBF. The results showed that the laser energy density has an important effect on microstructure and density, and it was sufficient to melt the alloy powder and deliver high-quality builds at 333 J/mm3. The microhardness, tensile strength, and yield strength of the LPBF-fabricated Al–Cu–Mg–Mn–Zr alloy increased with increasing laser energy density. In addition, the tensile fracture surfaces exhibited mixed brittle and ductile fracture features at low energy density values (231–358J/mm3). The ductile fracture was observed at higher energy density values (>463J/mm3). When the laser density was set at 500 J/mm3, the LPBF-fabricated alloy exhibited high relative density (99.88%) and the most optimal mechanical properties, with microhardness of 141.5 Hv, tensile strength of 343.9 MPa, yield strength of 311.0 MPa, and elongation of 6.1%. After solution treatment at 560 °C for 2 h and water quenching, the Al–Cu–Mg–Mn–Zr alloy exhibits the excellent mechanical properties with ultimate tensile strength of 483.6 MPa, yield strength of 365.5 MPa, and elongation of 13.4%.

Direct sound printing

Photo- and thermo-activated reactions are dominant in Additive Manufacturing (AM) processes for polymerization or melting/deposition of polymers. However, ultrasound activated sonochemical reactions present a unique way to generate hotspots in cavitation bubbles with extraordinary high temperature and pressure along with high heating and cooling rates which are out of reach for the current AM technologies. Here, we demonstrate 3D printing of structures using acoustic cavitation produced directly by focused ultrasound which creates sonochemical reactions in highly localized cavitation regions. Complex geometries with zero to varying porosities and 280 μm feature size are printed by our method, Direct Sound Printing (DSP), in a heat curing thermoset, Poly(dimethylsiloxane) that cannot be printed directly so far by any method. Sonochemiluminescnce, high speed imaging and process characterization experiments of DSP and potential applications such as remote distance printing are presented. Our method establishes an alternative route in AM using ultrasound as the energy source.

Generative Design of Structured Materials for Controlled Frequency Responses.

Spatially varying material properties allow the dynamic response of structural systems to be almost arbitrarily tailored, far beyond the first or fundamental natural frequency. Continuing advances in manufacturing technology are making it possible to achieve the necessary range of stiffness and density variations, but the design of these property distributions is a challenging task because of the complex multidimensional nature of the problem. Generative design methods based on evolutionary optimization algorithms have been successfully used to obtain solutions based on multi-material distributions. However, the applicability of these solutions is limited by their reliance on multi-material additive manufacturing (AM), which currently only offers digitally mixed acrylic polymer options that are generally unsuitable to produce functional parts. A novel structured material solution is proposed here, in which the problem domain is divided into several volume elements (voxels), each of which contains a structure whose geometrical form is altered to adjust its effective properties to desired values. The single material structural solution will be amenable for ready fabrication by the powder-based selective laser sintering and melting processes with real engineering polymer and metal systems, thereby allowing for the realization of the benefits in real-world applications. The resulting continuous design spaces are searched using a modern evolutionary algorithm, the covariance matrix adaptation evolution strategy (CMA-ES). A MATLAB implementation of this evolutionary design method, in conjunction with finite element simulations for fitness evaluation, showed good convergence for several different cantilever beam test cases when tested against several different sets of target natural frequencies. Correlations with the multi-material solutions show that the single structured material approach is on par or even better in some cases, even though the test domain was discretized into 80% fewer voxels than for the multi-material case. Furthermore, the voxel structures can be realized using current AM technologies.

A GEOMETRIC DESIGN METHOD OF RADIAL INFLOW TURBINE FROM 0D TO 3D FOR ORGANIC RANKINE CYCLE MICRO POWER GENERATION

Radial turbine is an essential component of Organic Rankine Cycle system and requires a medium to high specific speed turbine. Radial turbine has a compact structure that can easily be made with current additive manufacturing technology if the 3D geometry of turbine components is known. Current researches only conduct 2D geometry design then import it into third-party software to construct the 3D geometry. This paper will explain design methodology to design radial inflow turbines from 0D until 3D using simple tools. The methods used to determine the geometry were based on Aungier, with modification in determining value of a, b, and c in nozzle design and A1 in Volute design to simplify the design process. The tools used in design were MS Excel and Autodesk Inventor. Rotor design starts with determining the two-dimensional parameters. All parameters are calculated based on the angle and velocities occurring in the velocity triangle at the inlet and outlet of the rotor using equations proposed by Aungier. Then, the straight, radial and quasi-normal lines of the blades are drawn based on governing equations. The transformation from 2D to 3D blade coordinates is done by using vector equations. The nozzle is designed by drawing the camber line profile and calculating the nozzle thickness to get the profile based on the governing equations given by Aungier. The volute dimensions are obtained by calculating the area of volute inlet passage and mean radius from mass and momentum conservation equations. A case study is shown in this paper with R134a as working fluid with the following range inlet conditions: mass flow rate at 1-2 kg/s, inlet pressure at 1.5 to 5 bar, inlet temperature at 80 to 130 °C, and power output target between 20 to 25 kW. The CFD results show that the designed turbine performs well with slight wake flow at the pressure side on the rotor inlet. A further study needs to be done in order to check the validity of this method by conducting analysis through experimental.

Enhancement in fine powder availability for Powder Bed Fusion applying high gravity

In recent years, additive manufacturing (AM) technology that can directly shape objects from three-dimensional data has attractedattention.AM technology is promising as a manufacturing method in space because of its resource and space-saving properties. Some studies have shown that gravity change is viewed as a problem to overcome. On the other hand, there has been no progress in the discussion of attempts to effectively utilize gravity changes for AM technology. In this study, we focus on powder bed fusion (PBF) among AM technologies, using gravity as a control factor. The high gravity PBF (HG-PBF) is expected to be able to solve the problems of the current AM technology such as improvement of shape accuracy and process stability. In this study, we used fine powders and experimentally discuss the effect of the high gravity field on improvement of PBF process.

Additive manufacturing embraces big data

Additive manufacturing (AM) is a relatively novel method to fabricate 3D objects by adding layer-upon-layer materials. As one of the most anticipated techniques in recent years, AM already made advances in design, production, and supply chain process of the manufacturing industry. AM is a digital manufacturing technology in which a massive amount of data is generated during the process. Accordingly, obtaining useful information from these data to improve current AM technology becomes a challenge. Meanwhile, Big Data research provides an ideal solution for dealing with the massive data obtained from AM processes. Besides the contributions in the AM research and production, Big Data analysis methods can also be used to help designers and engineers by collecting valuable information from clients and customers. From a business perspective, the manufacturing sector will benefit from the established Big Data sharing platform to promote and popularize new products. On the other hand, customers will obtain desired commodities with the help of a new-type 3D printing service system. The goal of this article is to summarize the contributions from the existing literature in the AM and Big Data field and prospect how Big Data methods can offer a better future for AM technology. It also introduces recent developments in AM technology combined with the internet of things (IoT), cloud, and cybersecurity. Future directions in AM and Big Data, which include AM data unification, completed AM data-sharing platform, and smart AM production process is pointed out as well.

Advances in additive manufacturing of shape memory polymer composites

Purpose A review on additive manufacturing (AM) of shape memory polymer composites (SMPCs) is put forward to highlight the progress made up to date, conduct a critical review and show the limitations and possible improvements in the different research areas within the different AM techniques. The purpose of this study is to identify academic and industrial opportunities. Design/methodology/approach This paper introduces the reader to three-dimensional (3 D) and four-dimensional printing of shape memory polymers (SMPs). Specifically, this review centres on manufacturing technologies based on material extrusion, photopolymerization, powder-based and lamination manufacturing processes. AM of SMPC was classified according to the nature of the filler material: particle dispersed, i.e. carbon, metallic and ceramic and long fibre reinforced materials, i.e. carbon fibres. This paper makes a distinction for multi-material printing with SMPs, as multi-functionality and exciting applications can be proposed through this method. Manufacturing strategies and technologies for SMPC are addressed in this review and opportunities in the research are highlighted. Findings This paper denotes the existing limitations in the current AM technologies and proposes several directions that will contribute to better use and improvements in the production of additive manufactured SMPC. With advances in AM technologies, gradient changes in material properties can open diverse applications of SMPC. Because of multi-material printing, co-manufacturing sensors to 3D printed smart structures can bring this technology a step closer to obtain full control of the shape memory effect and its characteristics. This paper discusses the novel developments in device and functional part design using SMPC, which should be aided with simple first stage design models followed by complex simulations for iterative and optimized design. A change in paradigm for designing complex structures is still to be made from engineers to exploit the full potential of additive manufactured SMPC structures. Originality/value Advances in AM have opened the gateway to the potential design and fabrication of functional parts with SMPs and their composites. There have been many publications and reviews conducted in this area; yet, many mainly focus on SMPs and reserve a small section to SMPC. This paper presents a comprehensive review directed solely on the AM of SMPC while highlighting the research opportunities.

A review: additive manufacturing of flexure mechanism for nanopositioning system

A comprehensive review relevant to the design and fabrication of nanopositioning stages based on additive manufacturing (AM) technology has been for the first time introduced in the academic society. With the development of AM technology, AM has been applied in many engineering design areas such as aerospace, automotive, consumer electronics, and so on. Due to current limitations of AM tolerance (surface quality, form error), process obscurity (melting pool, layer adhesion), and cost (especially for metals or composites), there are only a small number of AM-applied devices that are currently available either in the market or in many industry sectors above. The flexure mechanisms that are typically employed in nanopositioning applications can provide a sub-nanometer resolution motion; however, their current manufacturing methods (milling, electric discharge machining, water jet machining) not only limit complicated flexure mechanisms in 3D geometries but also prevent designers from challenging novel topology optimizations. AM can overcome those limitations of fabrication and material distribution. Furthermore, it can allow new design approaches to topology optimizations. This review presents current and future AM-based precision motion device applications. Here, both design and fabrication of flexure mechanisms applied with current AM technology and the potential of further developments were discussed.

Efficient contouring of functionally represented objects for additive manufacturing

Functionally (implicitly) defined 3D objects allow us to quite easily model parts with complex topology such as lattices and organic-like structures with a high level of flexibility. Previous works in this area are based on the direct generation of CNC programs for the 3D printing of these objects and are backed by the growing support for this input format from hardware manufacturers. Efficient contouring of functionally defined models, however, is not an easy task. In this paper, we develop an algorithm for contour extraction of implicitly defined objects for direct additive manufacturing (AM). By comparing various adaptive and exhaustive (non-adaptive) methods of the function representation contouring for AM (FRepCAM), we make a set of recommendations for its usage depending on the specific resolution of the printer. In particular, we use a novel criterion based on affine arithmetic to maintain efficiency while preserving the robustness of the contouring process. The techniques mentioned were evaluated for algebraic and non-algebraic solids and heterogeneous models under a resolution that is comparable with that of current AM technology. The results show that the chosen adaptation criteria allow us to efficiently obtain a contour for complex models and generally outperform those of traditional algorithms based on exhaustive enumeration, especially for high-resolution contouring. In addition, the results present proof of the printability of implicitly defined objects with different 3D printing techniques.

List of abstracts

. Results obtained in the analysis of single layer and multilayered carbon stacks produced by PLD at low temperature will be presented. The mechanical properties of carbon single layers deposited at various laser pulse fluences, like hardness and elasticity, were determined by means of nano indentation measurements. It will be shown that a wide variety of mechanical properties can easily be adjusted by adapting the process parameters.

Solution-Based 3D Printing of Polymers of Intrinsic Microporosity.

Current additive manufacturing methods have significant limitations in the classes of compatible polymers. Many polymers of significant technological interest cannot currently be 3D printed. Here, a generalizable method for 3D printing of viscous tenary polymer solutions (polymer/solvent/nonsolvent) is applied to both "intrinsically porous" (a polymer of intrinsic microporosity, PIM-1) and "intrinsically nonporous" (cellulose acetate) polymers. Successful ternary ink formulations require balancing of solution thermodynamics (phase separation), mass transfer (solvent evaporation), and rheology. As a demonstration, a microporous polymer (PIM-1) incompatible with current additive manufacturing technologies is 3D printed into a high-efficiency mass transfer contactor exhibiting hierarchical porosity ranging from sub-nanometer to millimeter pores. Short contactors (1.27 cm) can fully purify (<1 ppm) toluene vapor (1000 ppm) in N2 gas for 1.7 h, which is six times longer than PIM-1 in traditional structures, and more than 4000 times the residence time of gas in the contactor. This solution-based additive manufacturing approach greatly extends the range of 3D-printable materials.

Additive Manufacturing Techniques in Manufacturing -An Overview

Research projects have been taken up on additive manufacturing (AM) technology and has been getting developed for more than 25 years, but without removing or replacing materials, AM processes are useful to produce 3D parts directly from CAD models by joining materials layer by layer which offers beneficial ability to build parts with geometric and material complexities that could not be formed by subtractive manufacturing processes. Through intensive research over the past two decades, significant progress has been achieved in the development and commercialization of new and innovative AM processes, and the applications in automotive, energy sectors, aerospace, biomedical, and other fields as well. This paper reviews the main processes, materials and applications of the current AM technology.

Optimal lattice-structured materials

This work describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describing the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.

Study on Consistently Optimum Deposition Conditions of Typical Metal Material Using Additive/Subtractive Hybrid Machine Tool

Additive manufacturing (AM) is increasingly being pursued as a practical approach for component manufacturing. Current AM technologies present certain challenges that are solvable with novel additive/subtractive hybrid machine platforms. Production of work pieces with consistent and viable material properties remains elusive. This work reports on a primary study to define combinations of additive process parameters and nozzle selection that result in quality work pieces. Specifically, AM work pieces of X2CrNiMo17-12-2 and Inconel 625 where characterized principally by porosity followed by tensile strength, hardness, and microstructure to determine optimal process parameters. A Taguchi analysis suggested desired work piece quality is achievable on a hybrid machine platform by adjusting AM process parameters