Search Results (118)

Large-format additive manufacturing (LFAM) is a manufacturing process in which high volumes of material are extruded in a layer-by-layer fashion to create large structures with often complex geometries. The Loci-One system, operated and developed by Loci Robotics Inc., is an LFAM-type system that was used to print single-bead walls of 20% by weight carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) using various print parameter inputs. This study observed the influence of bead width and layer time on thermomechanical performance via material characterization techniques that accounted for the complex microstructure of LFAM parts to develop a better understanding of parameter–structure–property relationships. Printed parts were characterized by measuring the coefficient of thermal expansion (CTE) and interlayer strength. Near the edges of the printed beads, microscopy revealed a “thinning effect” experienced by a shell composed primarily of highly oriented fiber as the bead width was increased; however, this effect was diminished with a higher shear rate. The CTE results demonstrated the influence of mesostructure on the thermomechanical response. Increased shear rates were expected to lower CTE in the x-direction due to a higher ratio of fiber oriented in the print direction, but this relationship was not always observed. For the larger bead widths printed at higher shear rates, the randomly oriented fiber at the core dominated the thermomechanical response and increased CTE overall in the x-direction. A heat transfer model was developed for this work to determine how much time was required for the deposited bead to cool to the glass transition temperature. Interlayer strength results revealed a rapid decrease once the printed layer time exceeded the time required for the extrudate to cool below the glass transition temperature. Full article

The fabrication of thin-walled plastic parts has potential in the automotive industry in terms of sustainability and circular economy targets to decrease any harmful effects on the ecosystems, cost and performance. Injection molding of thin-walled automotive parts is more complex in terms of processing defects compared to traditional plastic parts. Optimization of processing parameters is of critical importance to solving problems and defects in the production of thin-walled parts. In this study, the flow length and weight of thin-walled spiral parts (with wall thicknesses of 0.50, 1.50, 2.70 and 3.00 mm) were investigated with theoretical and experimental studies. The theoretical flow length and weight of the thin-walled spiral parts were determined by Moldflow analysis according to the pressure and wall thickness. The correlation graph between theoretical results and experimental measurements was obtained. When the wall thickness of the thin-walled spiral parts increased, the flow length of the thin-walled spiral parts increased. As a result, it was found that the thin-walled spiral part mold could not be filled for wall thicknesses of 0.50 and 1.50 mm at maximum pressure due to decreasing temperature at the flow front. In addition, the thin-walled spiral part mold can be filled for a wall thickness of 2.70 and 3.00 mm. In the correlation study conducted for these values, an agreement of approximately 90% was achieved. However, it was also observed that as the pressure increases, the deviation between the experimental and theoretical results becomes more pronounced. Full article

Laser powder bed fusion (LPBF) is the best suited technology to manufacture temperature-resistant Ti-6Al-2Sn-4Zr-6Mo parts with complex geometrical features for high-end applications. Improving printing accuracy by reducing the layer thickness (t) generally requires repeating a tedious and time-consuming process optimization routine. To simplify this endeavour, the present work proposes three process equivalence criteria allowing to transfer optimized process conditions from one printing parameter set to another. This approach recommends keeping the volumetric laser energy density (VED) and hatching space-to-layer thickness ratio (h/t) constant, while adjusting the scanning speed (v) and hatching space (h) accordingly. To validate this approach, Ti6246 parts were printed with 50 µm and 25 µm layer thicknesses, while keeping VED = 100 J/mm³ and h/t = 3 constant for both cases. The printed samples were analyzed in terms of their density, microstructure and mechanical properties, as well as the geometric compliance of wall-, gap- and channel-containing artefacts. Highly dense samples exhibiting comparable microstructures and mechanical properties were obtained with both parameters sets investigated. However, they induced markedly differing geometric characteristics. Notably, using 25 µm layers allowed printing walls as thin as 0.2 mm as compared to 1.0 mm for 50 µm layers. Full article

Additive manufacturing (AM) enables the consolidation of components and the integration of new functionalities in metallic parts, but layered fabrication often results in poor surface quality and geometric deviations. Among various surface treatment techniques, machining is often favoured for its capability to enhance not only surface finish but also critical geometric tolerances such as flatness and circularity, in addition to dimensional accuracy. However, machining AM components, particularly thin-walled structures, poses challenges related to unconventional material properties, complex fixturing, and heightened susceptibility to chatter. This study investigates the vibrational behaviour of thin-walled Ti6Al4V components produced via laser powder bed fusion, using a jet-engine compressor blade demonstrator. Four stock envelope designs were evaluated: constant, tapered, and two topologically optimised variants. After fabrication by Laser Powder Bed Fusion, the blades underwent tap testing and subsequent machining to assess changes in modal characteristics. The results show that optimised geometries can enhance modal performance without increasing the volume of the stock material. However, these designs exhibit more pronounced in situ modal changes during machining, due to greater variability in material removal and chip load, which amplifies vibration sensitivity compared to constant or tapered stock designs. Full article

This study investigates the effect of Interlayer Dwell Time (IDT) on the thermal behavior of the Wire-Laser Directed Energy Deposition (WLDED) process. A two-dimensional transient thermal model was developed in MATLAB, incorporating temperature-dependent material properties, a moving Gaussian heat source, and melting–solidification phase change to simulate sequential layer deposition. The model was calibrated for thin-walled geometries, numerically validated using ANSYS, and experimentally validated with literature data. Using the validated model, twenty-seven cases were simulated to examine the combined influence of IDT, part length, and layer thickness on melt-pool dimensions and layer-wise temperature distribution. The results show that increasing IDT reduces melt-pool depth and length by limiting heat accumulation, with the magnitude of this effect depending strongly on part length and layer thickness. Shorter parts and thicker layers exhibit the highest sensitivity to IDT variations. Additionally, the Thermal Stability Factor (TSF) is introduced, a dimensionless index that effectively identifies heat-accumulation phenomena and indicates thermal instabilities. Overall, the findings enhance the understanding of the impact of IDT in the thermal profile of WLDED and demonstrate that optimized IDT selection can stabilize melt-pool geometry and reduce thermal buildup, supporting future adaptive IDT strategies in wire-based metal additive manufacturing. Full article

This work presents a fused-filament fabrication (FFF) hot end that combines an unrestricted-rotation C-axis with a rectangular-slot nozzle and an induction-heated melt sleeve. The architecture replaces the popular resistive cartridge and heater block design with an external coil that induces eddy-current heating in a thin-walled sleeve, threaded to the heat break and nozzle, reducing thermal mass and eliminating wired sensors across the rotating interface. A contactless infrared thermometer targets the nozzle tip; the temperature is regulated by frequency-modulating the inverter around resonance, yielding stable control. The hot end incorporates an LPBF-manufactured nozzle, which transitions from a circular inlet to a rectangular outlet to deposit broad, low-profile strands at constant layer height while preserving lateral resolution. The concept is validated on a desktop Cartesian platform retrofitted to coordinate yaw with XY motion. A twin-printer testbed compares the proposed hot end against a stock cartridge-heated system under matched materials and environments. With PLA, the induction-heated, rotating hot end enables printing at 170 °C with defect-free flow and delivers substantial reductions in job time (22–49%) and energy per part (9–39%). These results indicate that the proposed approach is a viable route to higher-throughput, lower-specific-energy material extrusion. Full article

Thin-walled cellular structures of continuous fiber-reinforced thermoplastic composites (CFRTPCs) have received much attention from both academics and industry due to their superior properties. Additive manufacturing provides an efficient solution for fabricating these thin-walled cellular structures of CFRTPCs. However, the process often requires cutting fiber filaments at jumping points during printing. Furthermore, the filament may twist, fold, and break due to sharp turns in the printing path. These issues adversely affect the mechanical properties of the additive manufactured part. In this paper, a Euler graph-based path planning method for additive manufacturing of CFRTPCs is proposed to avoid jumping and sharp turns. Euler graphs are constructed from non-Eulerian graphs using the method of doubled edges. An optimized Hierholzer’s algorithm with pseudo-intersections is proposed to generate printing paths that satisfy the continuity, non-crossing, and avoid most of the sharp turns. The average turning angle was reduced by up to $20.88\%$ and the number of turning angles less than or equal to $120°$ increased by up to $26.67\%$ using optimized Hierholzer’s algorithm. In addition, the generated paths were verified by house-made robot-assisted additive manufacturing equipment. Full article

Laser wire additive manufacturing (LWAM) offers high deposition efficiency and excellent material utilization. However, manufacturing thin-walled structures with large inclination angles and no support remains a challenge. In this study, the influence of laser tilt angle on the formability of multi-layer inclined parts was systematically investigated. Results reveal that tilting the laser redistributes energy input along the inclination direction, stabilizing the melt pool and reducing angular deviation. Under a 20° tilt condition, thin-walled structures with inclination up to 70° were successfully fabricated, overcoming the limitation of conventional vertical deposition. Furthermore, a multi-inclination arch bridge structure was fabricated under optimized conditions, demonstrating good morphological appearance, dimensional accuracy (deviation within ±0.3 mm), and surface waviness (W < 0.12 mm). The findings provide new insights into the mechanism of energy redistribution in tilted LWAM and establish a promising strategy for manufacturing complex overhanging structures in aerospace and automotive industries. Full article

Laser-directed energy deposition (DED) offers significant potential for the additive manufacturing of thin-walled Inconel 718 aerospace components. However, the structural defects readily formed during deposition, along with the extensive precipitation of long-chain Laves phases between coarse dendrites, can severely compromise the mechanical properties of as-fabricated Inconel 718 parts. To address this, an ultrasonic-assisted DED (UDED) method was employed to reduce the deposited structural defects and refine crystalline structures, and the influences of ultrasonic energy fields on the microstructure and mechanical properties of thin-walled Inconel 718 samples were systematically investigated. The results demonstrated that ultrasonic vibration significantly enhances the microstructural quality by reducing porosity and pore size, weakening texture intensity, fragmenting long-chain Laves phases, mitigating severe elemental segregation, and refining matrix grains. Consequently, the UDED thin-walled Inconel 718 sample exhibited an approximately 15% increase in microhardness compared to the conventional DED counterpart, alongside satisfactory strength and ductility. This study highlights the superiority of UDED for microstructure tailoring and its potential for mechanical property regulations in thin-walled Inconel 718 aerospace components. Full article

AI-integrated robotics in Industry 5.0 demands advanced manufacturing systems capable of autonomously interpreting complex geometries and dynamically adjusting machining strategies in real time—particularly when dealing with aerospace components featuring large-curvature surfaces. Large-curvature aerospace components present significant challenges for precision drilling due to surface-normal deviations caused by curvature, roughness, and thin-wall deformation. This study presents a robotic drilling system that integrates adaptive PCA-based surface normal estimation with in-process pre-drilling correction and post-drilling verification. This system integrates a 660 nm wavelength linear laser projector and a 1.3-megapixel industrial camera arranged at a fixed 30° angle, which project and capture structured-light fringes. Based on triangulation, high-resolution point clouds are reconstructed for precise surface analysis. By adaptively selecting localized point-cloud regions during machining, the proposed algorithm converts raw measurements into precise normal vectors, thereby achieving an accurate solution of the normal direction of the surface of large curvature parts. Experimental validation on a 400 mm-diameter cylinder shows that using point clouds within a 100 mm radius yields deviations within an acceptable range of theoretical normals, demonstrating both high precision and reliability. Moreover, experiments on cylindrical aerospace-grade specimens demonstrate normal direction accuracy ≤ 0.2° and hole position error ≤ 0.25 mm, maintained across varying curvature radii and roughness levels. The research will make up for the shortcomings of existing manual drilling methods, improve the accuracy of hole-making positions, and meet the high fatigue service needs of aerospace and other industries. This system is significant in promoting the development of industrial automation and improving the productivity of enterprises by improving drilling precision and repeatability, enabling reliable assembly of high-curvature aerospace structures within stringent tolerance requirements. Full article

The use of aluminum honeycomb structures is fast expanding in advanced sectors such as the aeronautics, aerospace, marine, and automotive industries. However, processing these structures represents a major challenge for producing parts that meet the strict standards. To address this issue, an innovative manufacturing method using longitudinal ultrasonic vibration-assisted cutting, combined with a CDZ10 hybrid cutting tool, was developed to optimize the efficiency of traditional machining processes. To this end, a 3D numerical model was developed using the finite element method and Abaqus/Explicit 2017 software to simulate the complex interactions among the cutting tool and the thin walls of the structures. This model was validated by experimental tests, allowing the study of the influence of milling conditions such as feed rate, cutting angle, and vibration amplitude. The numerical results revealed that the hybrid technology significantly reduces the cutting force components, with a decrease ranging from 10% to 42%. In addition, it improves cutting quality by reducing plastic deformation and cell wall tearing, which prevents the formation of chips clumps on the tool edges, thus avoiding early wear of the tool. These outcomes offer new insights into optimizing industrial processes, particularly in fields with stringent precision and performance demands, like the aerospace sector. Full article

This study considered the molding process of a thin-walled composite structure, imported from a CAD model, with the requirements of the uniformity of the mechanical properties and wall thickness. The developed numerical process model, which includes both the vacuum infusion and post-infusion stages, takes into account the entire complex of processes evolving in a spreading liquid resin, as well as in a porous preform. The controlled process parameters are the temperature and the magnitudes and times of pressure applied to the open surface of the preform and in the vacuum line. The low thickness of the preform walls and the fixation of its inner surface on an open composite mold allow the mechanical part of the problem to be simplified, thus considering only the preform deformation normal to the opened surface, which provides a significant reduction in the simulation time and the ability to effectively optimize the process. The examples associated with the three control modes considered here show that the presented model’s description of the process, with the toolkit for selecting the controlled parameters, eliminates critical situations such as the formation of dry spots, the premature blocking of the vacuum port, or the uneven distribution and insufficient amount of the reinforcing component in the preform. This is due to the appropriately described process dynamics up to the moment of a sharp increase in viscosity and the hardening of the resin. This approach additionally provides access to process parameters that would be inaccessible in a full-scale experiment. Full article

Machining deformation is a key bottleneck that restricts the improvement of manufacturing accuracy of aviation thin-walled structural components, such as frames, beams, and wall panels. The initial residual stress of the workblank and the cutting load are the direct factors leading to machining deformation. Based on the initial residual stress measurement and the milling force test, a finite element prediction model for milling deformation of frame-type thin-walled parts with integrated consideration of initial residual stress and the milling force was established and experimentally verified in this study. Then, the influence of milling process factors, such as the frame processing sequence (FPS), the cutting path, and the single frame one-time removal depth (SFORD), on the milling deformation of frame-type parts was studied. The results showed that the established prediction model had high reliability and the prediction accuracy was improved by 6.7% compared with that when only considering the initial residual stress. A smaller machining deformation can be achieved through the use of the FPS to prioritize the width, direction, and symmetrical milling, as well as the inner loop cutting path, and the smaller SFORD. This study can provide a technical reference for the prediction and control of milling deformation of aviation thin-walled structural parts, especially frame-type thin-walled parts. Full article

A well-designed clamping layout significantly enhances the dynamic stiffness of a manufacturing system, improving its stability and suppressing cutting chatter in workpieces. This paper focuses on the machining of thin-walled beams, which are prone to vibration and have low stiffness, especially under hydraulic floating clamping conditions. By analyzing the system stability domain, we propose a method to improve system stiffness through strategic design of support module layouts. Finite element dynamic simulations and modal hammer experiments were conducted to validate this approach. The results show that the proposed layout design method increases the relative central frequency by 13.49% and the relative fundamental frequency by 8.51%. These findings demonstrate a substantial improvement in the dynamic stiffness of the part-clamping system, confirming that the auxiliary support module layout design method effectively enhances system dynamic stiffness and suppresses cutting chatter. Full article

Precise thermal management remains a critical challenge in Wire Arc-Direct Energy Deposition (W-DED) processes due to significant temperature fluctuations that can adversely impact part quality, dimensional accuracy, and process reliability. To address these issues, this study introduces a novel Hybrid Interlayer Hysteresis Controller (HIHC) designed specifically for W-DED, which integrates real-time thermal feedback and adaptive dwell time control. The system implements a dual-mode cooling strategy based on a temperature threshold, utilizing optical character recognition-based temperature monitoring and a rolling buffer system for stability. Experimental validation demonstrated improvements in thermal management, with the dynamic control system maintaining an average temperature undershoot of 1.38% while achieving 96.29% optimal temperature window compliance. Surface quality analysis revealed an 8.67% improvement in front face smoothness and a 5.15% enhancement in top surface quality. The dynamic control system also exhibited superior dimensional accuracy, producing thin walls with widths of 61.98 mm versus 66.43 mm in fixed dwell time samples, relative to the intended 60 mm specification. This study advances the field of additive manufacturing by establishing a robust framework for precise thermal management in W-DED processes, contributing to enhanced part quality, reduced post-processing requirements, and improved process reliability. Despite these advances, limitations include the system’s dependence on external optical monitoring hardware, potential scalability constraints for complex geometries, and limited testing across diverse material systems. Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling. Full article