Browse Topic: Manufacturing
Aircraft assembly systems, as a critical phase in aerospace manufacturing, face significant challenges in maintaining production efficiency and ensuring product quality. This complex manufacturing system exhibits two distinct characteristics: (1) tightly coupled interactions among manufacturing elements involving process sequences, material flows, and equipment utilization; and (2) dynamic resource allocation and material distribution plans. The inherent variability in production element configurations often leads to operational instability and schedule deviations, which may result in abnormal production states. To address these challenges, this study proposes a data-driven predictive framework that integrates Long Short-Term Memory (LSTM) neural networks with multi-criteria evaluation. The developed LSTM-based model effectively forecasts two critical production indicators of cycle time and balance rate, achieving temporal prediction through historical operational data analysis. The proposed methodology facilitates timely anomaly detection and early warning, allowing proactive risk mitigation and ensuring sustained production system stability. This research contributes to advancing intelligent monitoring and control strategies for aircraft assembly operations within data-driven manufacturing environments.
With the increasing demand for material microimaging analysis, there is a growing need for advanced precision grinding and polishing equipment, especially for metals, ceramics, and composites. Existing automated systems struggle with handling complex material challenges. This paper presents a fully automated adaptive grinding and polishing machine based on an STM32 microcontroller that handles multi-material samples. The system includes modules for sample access, cleaning, pad replacement, human-computer interaction, and equipment communication. The STM32 microcontroller executes grinding and polishing tasks based on instructions from the host computer while dynamically adjusting PID control parameters using an improved weighted average optimization algorithm. This approach enhances control accuracy, stability, and overall surface treatment quality compared to traditional PID control methods.
This research demonstrates a facile method for fabricating an anti-icing coating through spray deposition on a metallic substrate. A dual-layer structure was designed to enhance icephobic properties: a primer layer incorporating fluorocarbon resin, butyl acetate, and rod-shaped micrometer-sized metal oxides to establish a secondary roughness morphology, followed by a topcoat composed of butyl acetate and nano-scaled superhydrophobic particles. Evaluation of the coating performance revealed a maximum water contact angle of 171.9°, indicating exceptional hydrophobicity. Furthermore, the coating exhibited notable abrasion resistance and anti-icing capabilities against overlaying ice.
Additive manufacturing (AM) processes facilitate the production of components with high geometrical complexity, presenting substantial opportunities for innovation in demanding sectors such as aerospace and biomedical engineering. A significant challenge impeding their broader application is the characteristic surface roughness of as-fabricated parts, which results from the layer-wise construction and the presence of partially melted powder particles. While electrochemical polishing (EP) represents a viable post-processing technique for achieving a smooth surface finish, a comprehensive understanding of how the non-equilibrium microstructures characteristic of AM materials interact with the EP process remains incomplete. This investigation centers on the electrochemical polishing behavior of Ti-6Al-4V alloy fabricated by direct energy deposition (DED), utilizing a sodium chloride-ethylene glycol electrolyte. The findings reveal that the material's distinct engenders anisotropic anodic dissolution. This behavior is attributed to the differential electrochemical potentials among the constituent phases and their crystallographic orientations, which consequently narrows the operational process window for effective, uniform polishing. This preferential dissolution of certain phases results in the formation of a subtle, micro-scale topographical variation that mirrors the orientation of the original columnar grain structure. Notwithstanding this microstructural influence, the EP treatment proved highly successful in refining the surface finish, substantially decreasing the average surface roughness from 0.350 μm to 0.042 μm. Concurrently, the treatment led to a significant enhancement in the alloy's corrosion resistance, attributed to an oxide layer. These findings underscore the critical necessity of accounting for microstructural characteristics when developing optimized electrochemical polishing protocols for additively manufactured components.
With the development of controlled nuclear fusion technology, the tokamak device, as the most promising magnetic confinement fusion reactor for advanced engineering applications, requires remote maintenance of its internal components, which has become a key factor affecting both operational efficiency and safety. As a critical component directly exposed to high-temperature plasma, the divertor target plate needs to be periodically replaced and carefully maintained to ensure stable and reliable reactor operation. However, this region is subject to extreme conditions, including high temperature, high vacuum, and intense radiation, making conventional manual maintenance infeasible. This necessitates the development of intelligent and automated teleoperation systems. To address the automated assembly and disassembly requirements of divertor target plates, this study designs an integrated target plate actuator comprising key functional units: a positioning module, a screwing module, a quick-change module, and a passive compliance structure. The actuator achieves rapid and precise alignment with target plate holes, accommodates bolts of different specifications, and exhibits excellent impact resistance. Furthermore, stiffness and mechanical analyses, supported by finite element simulations, verify the actuator’s safety and reliability under high loads and impact forces. To further enhance operational performance, a segmented disassembly and assembly control strategy based on reinforcement learning is proposed, enabling the actuator to adaptively handle torque variations and ensure precise and stable bolt operations. The results demonstrate that the proposed actuator and control strategy significantly improve the accuracy, stability, and efficiency of target plate operations under complex working conditions, providing a reliable solution for automated divertor maintenance in tokamak devices.
This device belongs to the field of aviation materials technology and discloses a high-efficiency drilling equipment for manufacturing aviation materials, which includes a bottom plate. The top of the bottom plate is provided with a clamping structure and a positioning structure. The clamping structure includes a second moving plate, a third sliding groove, a second bi-directional screw, a fourth screw block, a clamping plate, and a rubber block. This device can hold materials through a clamping structure and effectively and quickly locate and drill holes through a positioning structure. By rotating the first threaded rod, it can drive the first screw block to move the U-shaped column. During the movement of the U-shaped column, it will drive the second threaded rod to move together. By rotating the second threaded rod, it will drive the second screw block to adjust the height of the connecting plate for drilling holes. By rotating the third threaded rod, it will drive the first moving plate to move, which will facilitate the multi-directional movement of the drill bit, improve the efficiency of drilling, avoid multiple position changes, and be beneficial for practical applications and operations.
Blended metal powders offer a compelling alternative to pre-alloyed powders in metal additive manufacturing by providing access to a wider range of alloy compositions and avoiding the high costs in producing pre-alloyed powders. In this work, a new and crack-free Ti-5AlMnScZrMgSiFe alloy (in wt.%) was manufactured by laser powder bed fusion (L-PBF) from mixed powders to investigate the microstructures, mechanical performance of printed parts. Ti-5 AlMnScZrMgSiFe alloy contains both alpha (α) and alpha prime (α′) phases. Further microstructural characterizations show that the L-PBF Ti-5 AlMnScZrMgSiFe contain dense dislocations and twins formed in additive manufacturing process. The as-printed Ti-5 AlMnScZrMgSiFe alloy exhibits a tensile fracture strength of ~950 MPa with a fracture elongation of ~12.5%. The eye-catching properties are attributed to the dense dislocations, nano-twins and solid-solution strengthening.
Topology optimization (TO), while powerful for generating high-performance structural layouts, often yields designs with enclosed voids that hinder manufacturability in powder-based additive manufacturing (AM). To address this, this paper proposes an Adaptive Virtual Temperature Field (AVTF) method that enforces the connectivity constraint. The approach integrates a projection-based density filtering and flood fill algorithm to detect enclosed voids, combined with an adaptive penalty scheme that autonomously adjusts the virtual temperature penalty factor to eliminate disconnected regions. AVTF operates via a low-cost geometric feedback mechanism. Numerical examples demonstrate that the method effectively eliminates enclosed voids with only a marginal increase in compliance while significantly reducing the maximum virtual temperature. The resulting designs exhibit fully connected material layouts, ensuring powder removability. The method provides a practical and robust pathway toward AM-ready topology optimization, bridging the gap between structural performance and manufacturability.
This paper examines the temperature distribution during pipe cutting and the impact of the heat-affected zone on the mechanical microstructure and properties of steel pipes. Utilizing testing equipment such as K-type thermocouples, a MESTL-WELD thermocouple spot welding machine, and a DC5516H 16-channel temperature data logger, temperature tests were conducted on Φ 1016 × 17.5 mm X70M spiral seam submerged arc welded steel pipes and Φ 1016 × 21 mm X70M straight-seam submerged arc welded steel pipes. The results indicate that the maximum test temperatures during cutting were 953.8 °C and 1216.6 °C, respectively, with the duration of temperatures exceeding 400 °C at each test point not exceeding 30 seconds. By fitting the relationship curve between the peak temperatures of each test point and the cutting distance using the ExpDec3 model, it was found that the cutting distance corresponding to a temperature of 580 °C was 12 mm. Furthermore, mechanical microstructure and property tests were performed on the pipe body at different positions of the HAZ. Except for an anomaly in the yield strength of the rod-shaped tensile specimens of the Φ 1016 × 21 mm X70M welded pipe body, no other abnormalities were detected. Macroscopic metallographic examination revealed that the axial length of the HAZ at the end of the cut pipe did not exceed 7 mm. Microhardness testing showed significant fluctuations in the microhardness of the pipe body at the end of the cut pipe, while the microhardness of the pipe body beyond 10 mm from the end gradually returned to normal.
This paper investigated the small deformation control of a large vertical vacuum vessel, a critical component in aerospace testing with stringent deformation limits under specific test conditions. Building on engineering experience and economic considerations, we designed oversized and multi-array external reinforcement rings tailored to the vessel’s spatial geometry to enhance its stiffness and stability. A novel integrated structural design was proposed, which mechanically couples the vacuum vessel with the concrete foundation via embedded components, specifically, by configuring optimized embedded parts at the vessel’s base and external reinforcement ring bottom, and then welding and binding these parts to the foundation’s embedded elements. This design significantly boosted the vertical vessel’s overall structural strength, rigidity, and stability. Ansys Workbench was used to simulate and analyze the vacuum vessel under different experimental conditions, and finite element simulations of the vessel under diverse experimental conditions validated that the integrated design achieves low stress and minimal deformation, compliant with test requirements. Post-installation deformation measurements further confirmed good agreement between experimental data and simulation results, verifying the model’s accuracy. The proposed fixed support structure addresses the limitations of traditional support systems for small-deformation applications and offers a new design paradigm for vertical vessel supports in high-precision engineering scenarios.
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