Additive manufacturing of silicone-thermoplastic elastomeric composite architectures

The terms Additive Manufacturing (AM) and 3D printing describe several very different methods for producing 3-dimensional forms. AM technologies present new opportunities for the yacht design and small boat manufacturing sectors, particularly the Fused Filament Fabrication (FFF) method. The design and construction of marine vessels present unique manufacturing challenges and opportunities for AM. While many AM methods are not well-suited for small boat manufacturing, some of these technologies are already being used by the marine industry. While AM technology is currently limited by the speed, scale, and material constraints of 3D printing materials and equipment, these technologies are being successfully scaled up for the marine industry by academic researchers and manufacturers. Additive Manufacturing technology will need to continue to advance in order to adapt itself to the complex material, structural, and mechanical requirements of the marine industry. The technical challenges that remain for large-scale AM to produce entire boats are the water-resistance of extruded materials, surface integrity (smoothness), the structural integrity of surface manifolds, and the integration of structural reinforcement systems.

Advancements in understanding the microstructure and properties of additive manufacturing Ti-6Al-4V alloy: A comprehensive review

Recent advances in additive manufacturing (AM) have attracted significant industrial interest. Initially, AM was mainly associated with the fabrication of prototypes, but the AM advances together with the broadening range of available materials, especially for producing metallic parts, have broaden the application areas and now the technology can be used for manufacturing functional parts, too. Especially, the AM technologies enable the creation of complex and topologically optimised geometries with internal cavities that were impossible to produce with traditional manufacturing processes. However, the tight geometrical tolerances along with the strict surface integrity requirements in aerospace, biomedical and automotive industries are not achievable in most cases with standalone AM technologies. Therefore, AM parts need extensive post-processing to ensure that their surface and dimensional requirements together with their respective mechanical properties are met. In this context, it is not surprising that the integration of AM with post-processing technologies into single and multi set-up processing solutions, commonly referred to as hybrid AM, has emerged as a very attractive proposition for industry while attracting a significant R&D interest. This paper reviews the current research and technology advances associated with the hybrid AM solutions. The special focus is on hybrid AM solutions that combine the capabilities of laser-based AM for processing powders with the necessary post-process technologies for producing metal parts with required accuracy, surface integrity and material properties. Commercially available hybrid AM systems that integrate laser-based AM with post-processing technologies are also reviewed together with their key application areas. Finally, the main challenges and open issues in broadening the industrial use of hybrid AM solutions are discussed.

Additive manufacturing of cementitious composites: Materials, methods, potentials, and challenges

Additive manufacturing (AM), also known as 3D printing, has been showing significant growth in recent years. Due to the several advantages, these processes provide, such as high process speed, the possibility for non-conventional geometries and a large range of materials; AM is quickly becoming an industry standard for both prototyping and end-user products. There are several 3D printing technologies available in the market, the most prevalent being fused deposition modeling (FDM), also known by fused filament fabrication (FFF). FDM is widely used as it is highly versatile and has the lowest entry level cost of any AM technology. Due to the layer-by-layer nature of the production procedure, 3D printed materials tend to behave with highly anisotropic properties. The main aspect that governs the anisotropy in FDM is the printing orientation. In order to study these effects, as well as select the optimal materials for future work, bulk specimens were produced from three different materials: polylactic acid (PLA), polycarbonate (PC), and thermoplastic polyurethane (TPU). These specimens were then submitted to tensile testing. In this work, the printing orientations used to manufacture the tested materials were 0°, 45°, and 90° for 100% line infill, with the bulk specimens being produced flat on the printing bed. Steps were taken to prevent layer adhesion failure as well as optimize the production of flexible materials, in this case TPU. The results were then compared with the specifications given by the supplier for FDM and with the raw material properties found in the literature. As expected, for all the specimens, infill orientation played a major role on both tensile strength and elongation. With the results presented in this work, it was possible to select TPU and PC as the most interesting materials to combine, given their broadly different properties. As for future work, a multi-material specimen will be produced, varying the percentage of each material as well as the placement and distribution on the testing bulk.

Aiming at the problems of a low material utilization rate and uneven stress distribution of cast-steel support joints in cable dome structures, topology optimization and additive manufacturing methods are used for optimization design and integrated manufacturing. First, the basic principle and calculation process of topology optimization are briefly introduced. Then, the initial model of the support joint is calculated and analyzed by using the universal software ANSYS Workbench 2020R2 and Altair OptiStruct, and the optimized joint is imported into Discovery Live to smooth the surface. The static behaviors of three types of joints (topology-optimized joints, joints after the smoothing treatment, and joints from practical engineering) are compared and analyzed. Finally, the joints are printed by using fused deposition modeling (FDM) technology and laser-based powder bed fusion (LBPBF) technology in additive manufacturing. The results show that the new support joint in the cable dome structure obtained by the topology optimization method has the advantages of a novel shape, a high material utilization rate, and a uniform stress distribution. Additive manufacturing technology can allow the manufacture of complex shape components with high precision and high speed. The combination of topology optimization and additive manufacturing effectively realizes the advanced design and integrated manufacturing of support joints for cable dome structures.

The paper aims to bridge the gap between the theoretical potential of Additive Manufacturing (AM) and its practical implementation for spare parts management, offering a potential contribution to practitioners in emerging countries. The paper proposes a structured framework for adopting Additive Manufacturing (AM) in spare parts supply chains by first evaluating suitable production methods and then proposing three distinct integration strategies at the enterprise, supplier, and corporate levels.The research adopts a Systematic Literature Review (SLR) using the databases Google Scholar, ScienceDirect, and Scopus. The literature relates to AM, spare parts production, and Supply Chain Management (SCM) challenges. Based on the reviewed papers, suitable AM technologies for spare parts production were identified and analysed to outline their potential across multiple characteristics. After that, papers on SCM were reviewed to develop a simplified framework for implementing spare parts using AM across three distinct integration strategies. The framework is tailored to respond to the needs of practitioners in emerging economies.The results demonstrate that suitable AM technologies should be selected for spare parts production, based on several criteria, including mechanical characteristics, materials, and cost. The paper confirms that implementing spare parts production using AM is feasible in emerging countries by adapting one of the three practical frameworks to each company's situation. Additional recommendations are provided to enable the combination of AM technologies with a conventional manufacturing system.The study is primarily limited by its reliance on theoretical literature rather than empirical studies, which may limit the direct applicability of the findings in industry. Nonetheless, it focused approach provides a foundational framework that researchers and practitioners can adapt and test in industrial contexts, especially in emerging economies.The research provides researchers and practitioners in emerging economies with a direct, actionable tool for selecting the AM technology to produce spare parts. It offers a clear roadmap to strategically integrate AM into their production within a conventional manufacturing system.The paper compares AM methods for the production of spare parts and presents preliminary insight into their SCM. The finding aims to enhance research on AM and its integration with conventional manufacturing systems in emerging countries.

TPU/CNTs flexible strain sensor with auxetic structure via a novel hybrid manufacturing process of fused deposition modeling 3D printing and ultrasonic cavitation-enabled treatment

Additive manufacturing (AM) has significant advantages, including design freedom, mass customization, and complex-structure manufacturing capabilities. As reducing the manufacturing energy is challenging in terms of the industrial sustainability, the AM energy consumption must be further explored. Existing energy consumption quantitation methods for AM require complex models that considering the energy characteristics of equipment. Therefore, we propose a feature-based energy consumption quantitation method for complex AM parts using simple models and suitable for different AM technologies. First, a feature segmentation method is proposed to divide complex AM parts into typical AM features. Then, the energy consumption model for each AMF is developed for energy consumption quantification during part fabrication. Finally, the energy consumption of a typical mechanical part manufactured via three different AM processes is investigated using the proposed method and measured experimentally. The results show that the proposed method can effectively and rapidly predict the energy consumption of AM processes with an accuracy of more than 95 %. Furthermore, the efficiency of the three AM processes is compared and discussed to address suitable efficiency improvement methods. In general, the proposed method can be integrated into three-dimensional AM models, providing a reference for the structural optimization of AM parts and sustainable manufacturing.

Plateau-Rayleigh instabilities in pore networks of additively manufactured polymers: A modeling perspective

Rapid vacuum casting has been proven to be a successful method in producing high-quality parts in small series. However, a challenge lies in the selection of proper Additive Manufacturing (AM) technologies for the development of a master pattern for the vacuum casting process. Each AM technologies differ from one another in terms of dimensional accuracy, surface finish, cost and lead times. The aim of this study is to investigate the performance of casting mating parts based on different additive manufacturing patterns for small batch. Three types of AM-based patterns: Fused Deposition Modeling (FDM), Stereolithography (SLA) and Multi-Jet Fusion (MJF) were compared. The Taguchi method, Signal to Noise ratio (S/N), Analysis of Variance (ANOVA) and T-test were conducted in determining the optimized parameters. From the findings, curing time is shown to be a significant parameter for dimensional accuracy and surface finish. Dimensional deviation varies in different directions of parts. For surface finish, there was only a slight change from the master pattern whereas the surface roughness of casting parts decreased within the range 0.23% to 2.85%. Tolerance grades for the selected dimensions of the parts were in the permissible range, based on ISO286-1:2010. When using distinct kinds of AM patterns to create replacement components, design tolerance is needed. It was suggested to select AM technology similar to that had been used for the original components. Battery cover was selected as a case study to represent the mating application parts.

Excessive recoil in firearms reduces shooting accuracy, causes user discomfort, and increases mechanical wear over time. This creates a need for effective solutions that can improve recoil management. This study investigates the use of advanced lattice structures made from thermoplastic polyurethane (TPU) and resin to enhance vibration damping and impact absorption in firearm components. Four lattice geometries were used, including Voronoi, Weaire Phelan, Gyroid, and Kelvin Cell. These structures were fabricated using two additive manufacturing methods. Material extrusion was applied for TPU parts to provide flexibility and strength, while Stereolithography (SLA), a light-based resin curing technique, was used to produce intricate resin structures. These approaches highlight the adaptability of additive manufacturing in producing functional parts that offer both vibration control and impact resistance. The performance of each structure was evaluated through vibration damping in two modes, rapid impact testing, and compression strength assessments. TPU samples consistently outperformed resin in both damping and energy absorption. Voronoi TPU exhibited the highest damping ratio, improving by 331 percent in the first mode with a value of 1.25 and by 300 percent in the second mode with a value of 0.20 compared to the original solid part. Weaire Phelan TPU reached the highest impact energy absorption at 6.45 joules, which is an improvement of 18.14 percent. Gyroid TPU absorbed energy the fastest, reaching a peak of 5.4 joules in only 14 milliseconds. This study introduces a new design approach by applying lattice structures to recoil pads, enabling enhanced performance and a high degree of customization.

<div class="section abstract"><div class="htmlview paragraph">Additive Manufacturing (AM) techniques, particularly Fusion Deposition Modeling (FDM), have received considerable interest due to their capacity to create complex structures using a diverse array of materials. The objective of this study is to improve the process control and efficiency of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material by creating a predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The study investigates the impact of FDM process parameters, including layer height, nozzle temperature, and printing speed, on key printing attributes such as tensile strength, flexibility, and surface quality. Several experimental trials are performed to gather data on these parameters and their corresponding printing attributes. The ANFIS predictive model is built using the collected dataset to forecast printing characteristics by analyzing input process parameters. The ANFIS model utilizes the learning capabilities of neural networks and fuzzy logic systems to analyze the intricate relationships within the FDM process. This model allows for precise predictions of printing outcomes. The model shows its ability to precisely forecast printing attributes, enabling the determination of ideal process parameter configurations for enhanced FDM performance with TPU material. The proposed Adaptive Neuro-Fuzzy Inference System (ANFIS) predictive model presents a methodical strategy for optimizing Fused Deposition Modeling (FDM) parameters. This model serves as a valuable tool for manufacturers to improve productivity and product quality in additive manufacturing operations using Thermoplastic Polyurethane (TPU) material. This research enhances the comprehension of FDM processes and provides practical recommendations for optimizing AM operations in diverse industrial applications.</div></div>

3D printing, also known as Additive manufacturing (AM), has emerged as a transformative technology with applications across various industries, including the medical sector. This review paper provides an overview of the current status of AM technology, its challenges, and its application in the medical industry. The paper covers the different types of AM technologies, such as fused deposition modeling, stereolithography, selective laser sintering, digital light processing, binder jetting, and electron beam melting, and their suitability for medical applications. The most commonly used biomedical materials in AM, such as plastic, metal, ceramic, composite, and bio-inks, are also viewed. The challenges of AM technology, such as material selection, accuracy, precision, regulatory compliance, cost and quality control, and standardization, are also discussed. The review also highlights the various applications of AM in the medical sector, including the production of patient-specific surgical guides, prosthetics, orthotics, and implants. Finally, the review highlights the Internet of Medical Things (IoMT) and artificial intelligence (AI) for regulatory frameworks and safety standards for 3D-printed biomedical devices. The review concludes that AM technology can transform the healthcare industry by enabling patients to access more personalized and reasonably priced treatment alternatives. Despite the challenges, integrating AI and IoMT with 3D printing technology is expected to play a vital role in the future of biomedical device applications, leading to further advancements and improvements in patient care. More research is needed to address the challenges and optimize its use for medical applications to utilize AM's potential in the medical industry fully.

Enhancement in the capabilities of additive manufacturing (AM) methods has led to development of many high-value components for aerospace, automotive and medical fields. Security concerns, such as (a) a predominantly cloud based process chain of AM may be breached and stolen files can be used for unauthorized reproduction of parts and (b) legitimately acquired parts can be reverse engineered, need to be addressed for this field to protect intellectual property and deter counterfeiting or unauthorized production. In the present work, a method of embedding an identification code inside the parts manufactured by AM methods is presented, which takes advantage of the layer-by-layer manufacturing process. The code is obfuscated by segmenting it into a specific number of parts, which are distributed throughout a large number of printed layers. In this case, viewing the code only from a specific direction is provides the correct visualization. A further obfuscation scheme is demonstrated that embeds multiple identification codes in the interpenetrating format. Only a specific set of processing conditions can lead to printing of the authentic code inside the part correctly. Numerous other conditions lead to printing of wrong code inside the part, which will lead to positive identification of counterfeit or unauthorized parts. Securing the AM process chain can help in accelerating the industrial applications of this versatile method.