Search Results (236)

The hydrostatic guideway has been widely used in ultra-precision machine tools. The flow stability of the hydrostatic guideway has a significant impact on its bearing characteristics, and the flow controller is critical to safeguard the flow stability of the hydrostatic guideway. Currently, most engineering applications use fixed, fluid-resistance flow controllers, which have a simple structure, low cost, and high reliability. However, when facing complex working conditions, the fixed, fluid-resistance flow controller cannot maintain the flow stability of the hydrostatic guide. In this study, a membrane-type flow controller with variable fluid resistance is designed, and a theoretical model of the flow controller’s bearing characteristics is established, which is verified by fluid–solid coupling simulation and flow rate experiments. Analyzing the influence of the design parameters of the membrane-type flow controller on the performance according to the theoretical model, the design guidelines of the membrane-type flow controller are established, the key structure of the flow controller is clarified, and the design range of the key structure dimensions is given. The results show that the gasket thickness of the membrane-type flow controller has the greatest impact on the performance of the hydrostatic guideways, which should be ensured to have a machining error of less than 0.005 mm. This study is a guide for the design and manufacture of flow controllers, as well as for engineering applications. Full article

Nanotechnology is revolutionizing medicine by enabling highly precise diagnostics, targeted therapies, and personalized healthcare solutions. This review explores the multifaceted applications of nanotechnology across medical fields such as oncology and infectious disease control. Engineered nanoparticles (NPs), such as liposomes, polymeric carriers, and carbon-based nanomaterials, enhance drug solubility, protect therapeutic agents from degradation, and enable site-specific delivery, thereby reducing toxicity to healthy tissues. In diagnostics, nanosensors and contrast agents provide ultra-sensitive detection of biomarkers, supporting early diagnosis and real-time monitoring. Nanotechnology also contributes to regenerative medicine, antimicrobial therapies, wearable devices, and theranostics, which integrate treatment and diagnosis into unified systems. Advanced innovations such as nanobots and smart nanosystems further extend these capabilities, enabling responsive drug delivery and minimally invasive interventions. Despite its immense potential, nanomedicine faces challenges, including biocompatibility, environmental safety, manufacturing scalability, and regulatory oversight. Addressing these issues is essential for clinical translation and public acceptance. In summary, nanotechnology offers transformative tools that are reshaping medical diagnostics, therapeutics, and disease prevention. Through continued research and interdisciplinary collaboration, it holds the potential to significantly enhance treatment outcomes, reduce healthcare costs, and usher in a new era of precise and personalized medicine. Full article

As the core component of ultra-precision machine tools, the manufacturing errors of aerostatic spindles are inevitable due to the limitations of machining and assembly processes, and these errors significantly affect the spindle’s static and dynamic performance. To address this issue, a force model of the unbalanced air film, considering the straightness errors of the rotor’s radial and thrust surfaces, was constructed. Unlike conventional studies that rely solely on idealized error assumptions, this research integrates actual straightness measurement data into the simulation process, enabling a more realistic and precise prediction of bearing performance. Rotors with different tolerance specifications were fabricated, and static performance simulations were carried out based on the measured geometry data. An experimental setup was built to evaluate the performance of the aerostatic spindle assembled with these rotors. The experimental results were compared with the simulation outcomes, confirming the validity of the proposed model. To further quantify the influence of straightness errors on the static characteristics of aerostatic spindles, ideal functions were used to define representative manufacturing error profiles. The results show that a barrel-shaped error on the radial bearing surface can cause a load capacity variation of up to 46.6%, and its positive effect on air film load capacity is more significant than that of taper or drum shapes. For the thrust bearing surface, a concave-shaped error can lead to a load capacity variation of up to 13.4%, and its enhancement effect is superior to those of the two taper and convex-shaped errors. The results demonstrate that the straightness errors on the radial and thrust bearing surfaces are key factors affecting the radial and axial load capacities of the spindle. Full article

Manufacturing processes are inherently complex, multi-objective in nature, and highly sensitive to process parameter settings. This paper presents two simple and efficient optimization algorithms—Best–Worst–Random (BWR) and Best–Mean–Random (BMR)—developed to solve both constrained and unconstrained optimization problems of manufacturing processes involving single, multi-, and many-objectives. These algorithms are free from metaphorical inspirations and require no algorithm-specific control parameters, which often complicate other metaheuristics. Extensive testing reveals that BWR and BMR consistently deliver competitive, and often superior, performance compared to established methods. Their multi- and many-objective extensions, named MO-BWR and MO-BMR, respectively, have been successfully applied to tackle 2-, 3-, and 9-objective optimization problems in advanced manufacturing processes such as friction stir processing (FSP), ultra-precision turning (UPT), laser powder bed fusion (LPBF), and wire arc additive manufacturing (WAAM). To aid in decision-making, the proposed BHARAT can be integrated with MO-BWR and MO-BMR to identify the most suitable compromise solution from among a set of Pareto-optimal alternatives. The results demonstrate the strong potential of the proposed algorithms as practical tools for intelligent decision-making in real-world manufacturing applications. Full article

With the rapid advancement of high-precision optical systems, increasingly stringent demands are imposed on the surface figure accuracy of optical components. The magnitude of residual stress in multilayer films directly influences the post-coating surface figure stability of these components, making the control of multilayer film stress a critical factor in enhancing optical surface figure accuracy. In this study, which addresses the process constraints and substrate damage risks associated with conventional annealing-based stress compensation for large-aperture optical components, we introduce an active stress engineering strategy rooted in in situ deposition process optimization. By systematically tailoring film deposition parameters and adjusting the thickness modulation ratio of TiO₂ and SiO₂, we achieve dynamic compensation of residual stress in multilayer structures. This approach demonstrates broad applicability across diverse optical coatings, where it effectively mitigates stress-induced surface distortions. Unlike annealing methods, this intrinsic stress polarity manipulation strategy obviates the need for high-temperature post-processing, eliminating risks of material decomposition or substrate degradation. By enabling precise nanoscale stress regulation in large-aperture films through controlled process parameters, it provides essential technical support for manufacturing ultra-precision optical devices, such as next-generation laser systems and space-based stress wave detection instruments, where minimal stress-induced deformation is paramount to functional performance. Full article

To obtain a flat top shaped passband in a conventional thin-film-based optical bandpass filter (OBF), it needs a large number of constitutional layers of thin films, which makes the film deposition systems more complicated and accumulates errors in film growth. A flat top and polarization-independent optical bandpass filter structure is proposed based on experimentally verified polarization independency in the form of a prism-pair coupled planar optical waveguide (POW). The POW is composed of two waveguide stacks, which consists of nine planar thin-film layers. Theoretical simulations show that the flat band top spans about 5 nm with transmittance over 97.8%. The passband is designed to be centered at 632.8 nm, the He-Ne laser wavelength, and the FWHM (full width at half maximum) bandwidth is about 35 nm. Within 0.5° tuning for the incident angle of the light, the passband could be shifted within 50 nm, while its transmittance fluctuates only less than 1% and the passband shape distorts only slightly. This type of OBF is potentially applicable in various fields of optical and laser spectroscopies. Full article

The enduring manufacturing goals are increasingly shifting toward ultra-precision manufacturing and micro-nano fabrication, driven by the demand for sophisticated products. Unconventional machining processes such as electrochemical jet machining (ECJM), electrical discharge machining (EDM), electrochemical machining (ECM), abrasive water jet machining (AWJM), and laser beam machining (LBM) have been widely adopted as feasible alternatives to traditional methods, enabling the production of high-quality engineering components with specific characteristics. ECJM, a non-contact machining technology, employs electrodes on the nozzle and workpiece to establish an electrical circuit via the jet. As a prominent special machining technology, ECJM has demonstrated significant advantages, such as rapid, non-thermal, and stress-free machining capabilities, in past research. This review is dedicated to outline the research progress of ECJM, focusing on its fundamental concepts, material processing capabilities, technological advancements, and its variants (e.g., ultrasonic-, laser-, abrasive-, and magnetism-assisted ECJM) along with their applications. Special attention is given to the application of ECJM in the semiconductor and biomedical fields, where the demand for ultra-precision components is most pronounced. Furthermore, this review explores recent innovations in process optimization, significantly boosting machining efficiency and quality. This review not only provides a snapshot of the current status of ECJM technology, but also discusses the current challenges and possible future improvements of the technology. Full article

Within the field of remote sensing, Unmanned Aerial Vehicle (UAV) infrared object detection plays a pivotal role, especially in complex environments. However, existing methods face challenges such as insufficient accuracy or low computational efficiency, particularly in the detection of small objects. This paper proposes a lightweight and accurate UAV infrared object detection model, YOLO-UIR, for small object detection from a UAV perspective. The model is based on the YOLO architecture and mainly includes the Efficient C2f module, lightweight spatial perception (LSP) module, and bidirectional feature interaction fusion (BFIF) module. The Efficient C2f module significantly enhances feature extraction capabilities by combining local and global features through an Adaptive Dual-Stream Attention Mechanism. Compared with the existing C2f module, the introduction of Partial Convolution reduces the model’s parameter count while maintaining high detection accuracy. The BFIF module further enhances feature fusion effects through cross-level semantic interaction, thereby improving the model’s ability to fuse contextual features. Moreover, the LSP module efficiently combines features from different distances using Large Receptive Field Convolution Layers, significantly enhancing the model’s long-range information capture capability. Additionally, the use of Reparameterized Convolution and Depthwise Separable Convolution ensures the model’s lightweight nature, making it highly suitable for real-time applications. On the DroneVehicle and HIT-UAV datasets, YOLO-UIR achieves superior detection performance compared to existing methods, with an mAP of 71.1% and 90.7%, respectively. The model also demonstrates significant advantages in terms of computational efficiency and parameter count. Ablation experiments verify the effectiveness of each optimization module. Full article

To improve the surface morphology quality of ultra-precision optical components, particularly in the suppression of mid-spatial frequency (MSF) errors, this paper proposes a morphology gradient-aware spatiotemporal coupled smoothing model based on convolutional material removal. By introducing the Laplacian curvature into the surface evolution framework, a curvature-sensitive “peak-priority” mechanism is established to dynamically guide the local dwell time. A nonlinear spatiotemporal coupling equation is constructed, in which the dwell time is adaptively modulated by surface gradient magnitude, local curvature, and periodic fluctuation terms. The material removal process is modeled as the convolution of a spatially invariant removal function with a locally varying dwell time distribution. Moreover, analytical evolution expressions of PV, RMS, and PSD metrics are derived, enabling a quantitative assessment of smoothing performance. Simulation results and experimental validations demonstrate that the proposed model can significantly improve smoothing performance and enhance MSF error suppression. Full article

This study presents the optimization of a laser ablation process designed to achieve the precise removal of polyamide coatings from ultra-thin platinum wires. Removing polymer coatings is a critical challenge in high-reliability manufacturing processes such as aerospace thermocouple fabrication. The ablation process must not only ensure the complete removal of the polyamide insulation but also maintain the tensile strength of the wire to withstand mechanical handling in subsequent manufacturing stages. Additionally, the exposed platinum surface must exhibit low surface roughness to enable effective soldering and be free of thermal damage or residual debris to pass strict visual inspections. The wires have a total diameter of 65 µm, consisting of a 50 µm platinum core encased in a 15 µm polyamide coating. By utilizing a UV laser with a wavelength of 355 nm, average power of 3 W, a repetition rate range of 20 to 200 kHz, and a high-speed marking system, the process parameters were systematically refined. Initial attempts to perform the ablation in an air medium were unsuccessful due to inadequate thermal control and incomplete removal of the polyamide coating. Hence, a water-assisted ablation technique was explored to address these limitations. Experimental results demonstrated that a scanning speed of 1200 mm/s, coupled with a line spacing of 1 µm and a single ablation pass, resulted in complete coating removal while ensuring the integrity of the platinum substrate. The incorporation of a water layer above the ablation region was considered crucial for effective heat dissipation, preventing substrate overheating and ensuring uniform ablation. The laser’s spot diameter of 20 µm in air and a focal length of 130 mm introduced challenges related to overlap control between successive passes, requiring precise calibration to maintain consistency in coating removal. This research demonstrates the feasibility and reliability of water-assisted laser ablation as a method for a high-precision, non-contact coating material. Full article

Platinum wires, known for their excellent electrical conductivity and durability, are widely used in high-precision industries, such as aerospace and automotive. These wires are typically coated with polyamide for protection; however, specific manufacturing processes require the coating to be selectively removed. Although traditional chemical stripping methods are effective, they are associated with high costs, safety concerns, and long processing times. As a result, laser ablation has emerged as a more efficient, precise, and cleaner alternative, especially at the microscale. In this study, ultraviolet nanosecond laser ablation was applied to remove polyamide coatings from ultra-thin platinum wires in a water-assisted environment. The presence of water enhances the process by promoting thermal management and minimizing debris. Key processing parameters, including the scanning speed, overlap percentage, and line distance, were evaluated. The optimal result was achieved at a scanning speed of 1200 mm/s, line distance of 1 µm, and single loop in water-ambient, where coating removal was complete, surface roughness remained low, and wire tensile strength was preserved. This performance is attributed to the effective energy distribution across the wire surface and reduced thermal damage due to the heat dissipation role of water, along with controlled overlap that ensured full coverage without overexposure. A thin, well-maintained water layer confined above the apex of the wire played a crucial role in regulating the thermal flow during ablation. This setup helped shield the delicate platinum substrate from overheating, thereby maintaining its mechanical integrity and preventing substrate damage throughout the process. This study primarily focused on analyzing the main effects and two-factor interactions of these parameters using Analysis of Variance (ANOVA). Interactions such as Speed × Overlap and Speed × Line Distance were statistically examined to identify the influence of combined factors on tensile strength and surface roughness. In the second phase of experimentation, the parameter space was further expanded by increasing the line distance and number of loops to reduce the overlap in the X-direction. This allowed for a more comprehensive process evaluation. Again, conditions around 1200 mm/s and 1500 mm/s with 2 µm line distance and two loops offered favorable outcomes, although 1200 mm/s was selected as the optimal speed due to better consistency. These findings contribute to the development of a robust, high-precision laser processing method for ultra-thin wire applications. The statistical insights gained through ANOVA offer a data-driven framework for optimizing future laser ablation processes. Full article

By integrating visual recognition technology and multi-object recognition into robotic arms, the flexibility and automation of the production process were improved in this study. By applying tiny machine learning (TinyML) and machine vision algorithms, we integrated edge computing devices to control the robotic arms and identified objects precisely on the production line, with ultra-low energy consumption. The developed system in this study included the SparkFun Edge development board and Raspberry Pi Camera Module 3, as edge devices for data processing, image recognition, and robotic arm control. By utilizing the Edge Impulse platform for data collection, model training, and optimization, edge devices and models for use in resource-limited environments were successfully generated. Using Edge Impulse’s automated toolchain, real-time image processing and object recognition were realized. The system achieved improved recognition accuracy and operational speed, demonstrating the potential of TinyML in enhancing the intelligence of robotic arms. MariaDB was chosen for data storage. Grafana was used to design a user-friendly web interface for real-time data monitoring and visualization and immediate data analysis and system monitoring. The developed system presented a success rate of 99% during actual operation. The feasibility of combining advanced image processing technology with robotic arms in intelligent manufacturing was verified in this study. The potential of integrating machine learning and automation technologies was also confirmed for the development of future manufacturing technologies. The model provides a technical reference and ideas for future factories that require high levels of automation and intelligence. Full article

Background: Nanomaterial-based biosensors represent a transformative advancement in oral health diagnostics and therapeutics, offering superior sensitivity and selectivity for early disease detection compared to conventional methods. Their applications span prosthetic dentistry, where they enable the precise monitoring of dental implants, and theranostics for conditions such as dental caries, oral cancers, and periodontal diseases. These innovations promise to enhance proactive oral healthcare by integrating detection, treatment, and preventive strategies. Objectives: This review comprehensively examines the role of nanomaterial-based biosensors in dental theranostics, with a focus on prosthetic applications. It emphasizes their utility in dental implant surveillance, the early identification of prosthesis-related complications, and their broader implications for personalized treatment paradigms. Methods: A systematic literature search was conducted across PubMed, Scopus, and Web of Science for studies published between 2010 and early 2025. Keywords included combinations of “nanomaterials”, “biosensors”, “dentistry”, “oral health”, “diagnostics”, “therapeutics”, and “theranostics”. Articles were selected based on their relevance to nanomaterial applications in dental biosensors and their clinical translation. Results: The review identified diverse classes of nanomaterials—such as metallic nanoparticles, carbon-based structures, and quantum dots—whose unique physicochemical properties enhance biosensor performance. Key advancements include the ultra-sensitive detection of biomarkers in saliva and gingival crevicular fluid, the real-time monitoring of peri-implant inflammatory markers, and cost-effective diagnostic platforms. These systems demonstrate exceptional precision in detecting early-stage pathologies while improving operational efficiency in clinical settings. Conclusions: Nanomaterial-based biosensors hold significant promise for revolutionizing dental care through real-time implant monitoring and early complication detection. Despite challenges related to biocompatibility, scalable manufacturing, and rigorous clinical validation, these technologies may redefine oral healthcare by extending prosthetic device longevity, enabling personalized interventions, and reducing long-term treatment costs. Future research must address translational barriers to fully harness their potential in improving diagnostic accuracy and therapeutic outcomes. Full article

In this paper, the concept of symmetry is utilized to design the composite controller for the die attach machine’s motion platform—that is, the construction and the solution of the nominal model-based composite controller design approach are symmetrical. With escalating demands for ultra-high-speed operations and microscale positioning accuracy (<5 μm) in semiconductor manufacturing, motion platforms face critical challenges, including high-speed instability, positioning jitter, and insufficient disturbance rejection. To address these limitations, a composite control strategy integrating nominal model-based linear active disturbance rejection control (NMLADRC) with sliding mode control (SMC) is developed. The synergistic interaction ensures the concurrent realization of robust tracking accuracy and rapid transient convergence. Simulation results demonstrate significant improvements over conventional PI control, LADRC, and NMLADRC. The phase lag is reduced by 50.04%, 36.34%, and 23.07%, respectively, while positioning time within ±5 μm accuracy threshold is shortened by 44.00%, 56.31%, and 31.51% when tracking the executed motion profile. The composite controller substantially enhances motion control precision, strengthens disturbance rejection capability, and improves system stability during high-speed operations. These advancements highlight the method’s strong practical applicability in precision motion control systems requiring both rapid response and microscale positioning accuracy. Full article

Micro Light Emitting Diode (Micro-LED) technology, characterized by exceptional brightness, low power consumption, fast response, and long lifespan, holds significant potential for next-generation displays, yet its commercialization hinges on resolving challenges in high-density interconnect fabrication, particularly micrometer-scale bump formation. Traditional fabrication approaches such as evaporation enable precise bump control but face scalability and cost limitations, while electroplating offers lower costs and higher throughput but suffers from substrate conductivity requirements and uneven current density distributions that compromise bump-height uniformity. Emerging alternatives include electroless plating, which achieves uniform metal deposition on non-conductive substrates through autocatalytic reactions albeit with slower deposition rates; ball mounting and dip soldering, which streamline processes via automated solder jetting or alloy immersion but struggle with bump miniaturization and low yield; and photosensitive conductive polymers that simplify fabrication via photolithography-patterned composites but lack validated long-term stability. Persistent challenges in achieving micrometer-scale uniformity, thermomechanical stability, and environmental compatibility underscore the need for integrated hybrid processes, eco-friendly manufacturing protocols, and novel material innovations to enable ultra-high-resolution and flexible Micro-LED implementations. This review systematically compares conventional and emerging methodologies, identifies critical technological bottlenecks, and proposes strategic guidelines for industrial-scale production of high-density Micro-LED displays. Full article