Search Results (102)

Photopolymer-based additive manufacturing processes such as stereolithography (SLA) offer high precision and surface quality but generate cured thermoset waste that is typically non-recyclable. In microgravity environments, conventional recycling approaches—based on gravitational settling, open solvent handling, and buoyancy-driven degassing—are ineffective, motivating the development of fully contained, gravity-independent material recovery systems for on-orbit manufacturing. This work presents a conceptual, design-stage closed-loop system architecture for recycling photopolymer resins in microgravity. The system integrates eight subassemblies enabling mechanical fragmentation, solvent-assisted dissolution, filtration, low-pressure degassing, pressurized storage, injection molding, and ultraviolet curing. A hermetically sealed dual-screw shredder produces resin fragments of 1–3 mm, suitable for dissolution. Gas removal is achieved through low-vacuum degassing at approximately 0.1–0.3 bar, with characteristic residence times of 5–10 min, ensuring stable processing prior to injection. Material transport is governed by mechanical conveyance and controlled pressure, eliminating reliance on gravity. The architecture maintains full containment of solids, liquids, and vapors throughout the process. Supported by engineering design considerations, the system establishes a microgravity-compatible pathway for closed-loop recycling of SLA materials. Experimental validation is planned in future work. Full article

Firefighters must locate victims reliably to carry out rescue operations within burning structures during urban firefighting events. Low visibility, reduced oxygen levels, weakened structural rigidity, and dense smoke make it difficult to locate victims. In addition to these challenges, victims may be unconscious and unable to report their locations to firefighters. This research work explores the Double Deep Q-Network (Double DQN), Dueling Deep Q-Network (Dueling DQN), and Dueling Double Deep Q-Network (D3QN) agents for an unmanned aerial vehicle (UAV) to navigate around a structure and locate trapped victims within it. The UAV’s position, Light Detection and Ranging (LiDAR), and infrared camera data are utilized as inputs for the Deep Q-Networks. The PER is used to store transitions and sample them according to priority for training. Python’s Pygame library is used in this research to create a simulated environment in which infrared camera and LiDAR data are simulated. The performance of the UAV agent is evaluated using cumulative maximum reward, reward distribution histogram, Temporal Difference (TD) error over time, and number of successful episodes. Among the three DQN UAV agents, the Dueling DQN and Double DQN have potential for real-world applications in firefighting. Full article

Additive manufacturing (AM) has emerged as a key enabling technology in contemporary dental manufacturing, driven by its capacity for customization, geometric complexity, and seamless integration with digital design workflows. This article presents a technology-oriented narrative review of additive manufacturing in dental implant production, focusing on dominant processing routes, material systems, and emerging research trends rather than a systematic or critical appraisal of the literature. An indicative descriptive analysis of publications indexed in the Web of Science and Scopus databases between 2014 and 2024 was used to contextualize the technological development of the field and identify major research directions. Emphasis was placed on metal powder bed fusion technologies, specifically Selective Laser Melting (SLM) and Direct Metal Laser Sintering (DMLS), which enable the fabrication of titanium implants with controlled porosity and enhanced osseointegration. Ceramic AM approaches, including SLA, DLP, and PBF, are discussed in relation to their potential for aesthetic dental restorations and customized prosthetic components. The publication trend overview indicates a growing interest in ceramic AM after 2020, an increasing focus on hybrid and functionally graded materials, and persistent challenges related to standardization and the availability of long-term clinical evidence. Key technological limitations—including manufacturing accuracy, material stability, validated metrology, and process reproducibility—are highlighted alongside emerging directions such as artificial intelligence-assisted workflows, nanostructured surface modifications, and concepts enabling accelerated or immediate clinical use of additively manufactured dental restorations. Full article

The invention concerns a screw-driven shredder for solid photopolymer resin, designed for both terrestrial use and prospective deployment in microgravity environments. The system addresses the need for efficient recycling of cured photopolymer waste generated by stereolithography (SLA) 3D printing—a process not yet implemented in orbit, but envisioned as part of future closed-loop additive manufacturing systems aboard space stations or lunar habitats. The proposed device is a compact, hermetically sealed mechanical unit composed of ten subassemblies, featuring two counter-rotating screw shafts equipped with carbide milling inserts arranged helically to achieve uniform and controlled fragmentation of solid SLA residues. The shredding process is supported by a pressurized inert fluid circuit, utilizing carbon dioxide (CO₂) as a cryogenic working medium to enhance cutting efficiency, reduce heat accumulation, and ensure particle evacuation under microgravity conditions. Studies indicate that CO₂-assisted cooling can reduce tool-tip temperature by 10–30 °C, cutting forces by 5–15%, and electrical power consumption by 5–12% while extending tool life by up to 50%. This invention thus provides a key component for a future in situ photopolymer recycling loop in space while also offering a high-efficiency shredding solution for Earth-based photopolymer waste management in additive manufacturing. Full article

Current traditional tea processing production lines suffer from issues such as fragmented data and low levels of intelligence. This paper proposes a three-dimensional visualization system for tea processing production lines based on digital twins. Firstly, the system’s overall framework and functional architecture were established. Secondly, multi-source heterogeneous data from the production line was collected and managed through a driver architecture, enabling the construction and mapping of the digital twin information model. Thirdly, referencing the actual environment of a green tea processing line, scene-specific lighting models and rendering techniques were employed to recreate a virtual green tea processing environment. During this process, lighting optimization enhanced the realism of the system’s scenes. Finally, employing data-driven methodologies, the system dynamically simulates the operational states of various production line equipment and the morphological changes in tea leaves. This achieves comprehensive three-dimensional visualization and all-round monitoring of the tea processing production line. Experimental validation confirms the feasibility of this visualized 3D system, injecting fresh impetus into advancing intelligent tea production. Full article

The demand for organ transplantation continues to rise worldwide, intensifying the gap between supply and demand and driving research in tissue engineering (TE). Bioprinting, particularly light-based vat photopolymerization (VP) methods such as digital light processing (DLP), has emerged as a promising strategy to fabricate complex, cell-compatible tissue constructs with high precision. In this study, we developed an open-source, bottom-up DLP bioprinter designed to provide a cost-effective and modular alternative to commercial systems. The device was built from commercially available components and custom-fabricated parts, with tolerance allocation and deviation analyses applied to ensure structural reliability. Mechanical and optical subsystems were modeled and validated, and the control architecture was implemented on the Arduino platform with a custom Python-based graphical interface. The system achieved a theoretical Z-axis resolution of 1 $\mathsf{\mu }$m and a vertical travel range of 50 mm, with accuracy and repeatability comparable to research-grade bioprinters. Initial printing trials using polyethylene glycol diacrylate (PEGDA) hydrogels demonstrated high-fidelity microfluidic constructs with adequate dimensional precision. Collectively, these results validate the functionality of the proposed system and highlight its potential as a flexible, precise, and cost-effective platform that is also easy to customize to advance the democratization of biofabrication in TE. Full article

This research details the development and evaluation of a Modern Ultrasonic Cleaning Tank (MUCT) designed to enhance cleaning efficiency in jewelry manufacturing, particularly for silver jewelry, replacing the traditional method, which was less efficient and had higher operating costs. The MUCT offers capabilities of single- or dual-frequency ultrasonic operation (28 kHz and 40 kHz) and adjustable transducer positioning. An advanced method involving computer simulations, utilizing harmonic response analysis and transient dynamic analysis, was employed to determine the acoustic pressure inside the MUCT, thereby indicating the cavitation intensity required to achieve high cleaning efficiency. Simulation results confirm that this design can distribute acoustic pressure throughout the MUCT, as intended. A prototype MUCT was assembled, and its operation was validated through foil corrosion tests, ultrasonic power concentration (UPC) measurements, and jewelry cleaning tests. The results revealed that the MUCT’s center provided the maximum UPC of 28 W/L and an acoustic pressure of 30.43 MPa, effectively operating at single and dual frequencies, and achieving superior dirt removal. The highest cleaning efficiency of 100% was achieved using dual frequency with a 97% water and 3% dishwashing liquid mixture at 60 °C, exceeding the 23.52% obtained with water at 27 °C without ultrasonic treatment. The MUCT, successfully integrated into the manufacturing process, offers customizable features to meet various cleaning needs, providing flexibility, improved performance, and cost savings. Full article

High-precision angular positioning mechanisms are essential across diverse scientific and industrial applications, from optical instrumentation to automated mechanical systems. Conventional bronze–steel gear reduction units, while reliable, are often heavy, costly, and unsuitable for chemically aggressive or vacuum environments, limiting their use in advanced research setups. This work introduces a novel 1:360 gear reduction system manufactured by resin-based additive manufacturing, designed to overcome these limitations. The compact worm–gear assembly translates a single crank rotation into a precise one-degree indicator displacement, enabling fine and repeatable angular control. A primary application is the alignment of parabolic mirrors in schlieren systems, where accurate tilt adjustment is critical to correct optical alignment; however, the design is broadly adaptable to other precision positioning tasks in laboratory and industrial contexts. Compared with conventional assemblies, the resin-based reducer offers reduced weight, chemical and vacuum compatibility, and lower production cost. Its three-stage reduction design further enhances load-bearing capacity, achieving approximately double the theoretical torque transfer of equivalent commercial systems. These features establish the device as a robust, scalable, and automation-ready solution for high-accuracy angular adjustment, contributing both to specialized optical research and general-purpose precision engineering. Full article

This study presents the development and validation of an automated oyster classification system designed to classify oysters by size and place them into trays for freezing. Addressing limitations in conventional manual processing, the proposed system integrates a vision-based recognition algorithm and a delta robot (parallel robot) equipped with a soft gripper. The vision system identifies oyster size and optimal grasp points using image moment calculations, enhancing the accuracy of classification for irregularly shaped oysters. Experimental tests demonstrated classification and grasping success rates of 99%. A process simulation based on real industrial conditions revealed that seven units of the automated system are required to match the daily output of 7 tons achieved by 60 workers. When compared with a theoretical 100% success rate, the system showed a marginal production loss of 715 oysters and 15 trays. These results confirm the potential of the proposed system to improve consistency, reduce labor dependency, and increase productivity in oyster processing. Future work will focus on gripper design optimization and parameter tuning to further improve system stability and efficiency. Full article

In recent years, the deterioration of social infrastructure such as bridges has become a serious issue in many countries around the world. To maintain the functionality of aging bridges over the long term, it is necessary to conduct regular inspections, detect damage at an early stage, and perform timely repairs. However, inspections require significant cost and time, and ensuring the safety of inspectors remains a major challenge. As a result, inspection using robots has attracted increasing attention. This study focuses on a wire-driven bridge inspection robot designed to inspect the underside of bridge girders. To use this robot, wires must be installed in the space beneath the girders. However, it is difficult to install wires over areas such as rivers. To address this problem, we developed a robotic arm capable of throwing a spear attached to a string. In order to throw the spear accurately to the target location, a three-dimensional dynamic model of the spear in flight was constructed, considering the tension of the string. Using this model, we accurately estimated the required throwing conditions and confirmed that the robotic arm could successfully throw the spear to the target location. Full article

This study introduces a MATrix LABoratory (MATLAB, version R2024b, update 1 (24.2.0.2740171))-based automated system for the detection and measurement of indication areas in coated surfaces, enhancing the accuracy and efficiency of quality control processes in metal, polymeric and thermoplastic coatings. The developed code identifies various indication characteristics in the image and provides numerical results, assesses the size and quantity of indications and evaluates conformity to ISO standards. A comprehensive testing method, involving non-destructive penetrant testing (PT) and radiographic testing (RT), allowed for an in-depth analysis of surface and internal porosity across different coating methods, including aluminum-, copper-, polytetrafluoroethylene (PTFE)- and polyether ether ketone (PEEK)-based materials. Initial findings had a major impact on indicating a non-homogeneous surface of obtained coatings, manufactured using different technologies and materials. Whereas researchers using non-destructive testing (NDT) methods typically rely on visual inspection and manual counting, the system under study automates this process. Each sample image is loaded into MATLAB and analyzed using the Image Processing Tool, Computer Vision Toolbox, Statistics and Machine Learning Toolbox. The custom code performs essential tasks such as image conversion, filtering, boundary detection, layering operations and calculations. These processes are integral to rendering images with developed indications according to NDT method requirements, providing a detailed visual and numerical representation of the analysis. RT also validated the observations made through surface indication detection, revealing either the absence of hidden defects or, conversely, internal porosity correlating with surface conditions. Matrix and graphical representations were used to facilitate the comparison of test results, highlighting more advanced methods and materials as the superior choice for achieving optimal mechanical and structural integrity. This research contributes to addressing challenges in surface quality assurance, advancing digital transformation in inspection processes and exploring more advanced alternatives to traditional coating technologies and materials. Full article

Originally introduced in the 1960s by DISA Elektronik as a calibration tunnel for hot-wire anemometers, the Type 55D41 has now been reengineered into a versatile and modern aerodynamic test platform. While retaining key legacy components, such as the converging nozzle and the 55D42 power unit, the upgraded system features a redesigned modular test section with optical-grade quartz windows. This enhancement enables compatibility with advanced flow diagnostics and visualization methods, including PTV, DIC, and schlieren imaging. The modernized facility maintains the precision and flow stability that made the original design widely respected, while expanding its functionality to meet the demands of contemporary experimental research. Its architecture supports the aerodynamic characterization of micro-scale static pressure probes used in aerospace, propulsion, and micro gas turbine applications. Special attention is given to assessing the influence of probe tip geometry (e.g., conical, ogive), port positioning, and stem interference on measurement accuracy. Full article

The paper presents the CNC manufacturing technology of the ”Double fixing fork” part as a module with educational purpose, being designed as a training support for students and other parties, facilitating the practical learning of CNC processing technology. Its technological manufacturing process involved a careful analysis of the geometry, material, tolerances, as well as functional requirements to ensure precision and reliability in operation. The material from which the part was made is a polymer material (PEHD 1000) selected both for its mechanical characteristics and for its compatibility with processing technologies. The results demonstrated high precision and adaptability, reduced execution times and the possibility of achieving complex geometries in a relatively short time. The developed module supports skill development in CNC programming and operation and is suitable for replication in other academic environments. Programming allowed for more precise control of the cutting tool trajectory and processing parameters. The paper represents an important contribution to the training of future specialists, paying special attention to the growing interdisciplinarity in manufacturing technology and the development of technical skills necessary for future engineers in the numerically controlled machinery sector. Full article

This paper introduces an automated calibration system for color filters used in quantitative schlieren imaging, developed in response to prior findings highlighting the need for automation to reduce calibration time, minimize human error, and improve data accuracy and repeatability. Drawing from the authors’ experimental experience and practical application, the system demonstrates a significant enhancement in calibration efficiency—reducing the process from 2–5 h manually to just 15–30 min, representing time savings of up to 90%. Positioning accuracy improves from ±50–100 μm in manual setups to ±1–10 μm through precision-controlled automation, substantially lowering variability and increasing the reliability of pixel calibration curves. While calibration accuracy remains dependent on flow characteristics and post-processing capabilities, the system’s use of larger color filters—validated analytically and experimentally—further increases contrast sensitivity by 10–20%, enhancing the extraction of physical parameters such as velocity, temperature, and pressure fields. The setup features a modular, scalable architecture with a user-friendly interface, making it adaptable to diverse experimental environments and suitable for users at varying levels of expertise. Its iterative optimization and high-throughput capabilities position this system as a robust, flexible solution for advancing schlieren imaging techniques and enabling next-generation optical diagnostics in fluid dynamics research. Full article

This article presents a series of innovative systems developed through student laboratory projects, comprising two autonomous vehicles, a quadrupedal walking robot, an active ankle-foot orthosis, a ball-on-beam balancing mechanism, a ball-on-plate system, and a manipulator arm, all actuated by pneumatic artificial muscles (PAMs). Due to their flexibility, low weight, and compliance, fluidic muscles demonstrate substantial potential for integration into various mechatronic systems, robotic platforms, and manipulators. Their capacity to generate smooth and adaptive motion is particularly advantageous in applications requiring natural and human-like movements, such as rehabilitation technologies and assistive devices. Despite the inherent challenges associated with nonlinear behavior in PAM-actuated control systems, their biologically inspired design remains promising for a wide range of future applications. Potential domains include industrial automation, the automotive and aerospace sectors, as well as sports equipment, medical assistive devices, entertainment systems, and animatronics. The integration of self-constructed laboratory systems powered by PAMs into control systems education provides a comprehensive pedagogical framework that merges theoretical instruction with practical implementation. This methodology enhances the skillset of future engineers by deepening their understanding of core technical principles and equipping them to address emerging challenges in engineering practice. Full article