Search Results (341)

Plunge shaving is a widely used finishing process for high-precision gears due to its high productivity and cost-effectiveness. However, manufacturing the plunge-shaving cutter itself remains challenging, particularly for modified tooth profiles. Because the theoretical cutter flank exhibits a hyperboloid-like geometry in the lead direction, conventional disk-wheel grinding tends to introduce systematic twist-like topographic bias. To overcome this limitation, a comprehensive mathematical framework is developed for the generative grinding of plunge-shaving cutters using an involute-helicoid grinding worm. Based on envelope theory and homogeneous coordinate transformations, the theoretical cutter surface is first derived, followed by the establishment of a complete kinematic grinding model. A linear least-squares optimization algorithm is then formulated to determine the optimal center-distance compensation parameter for minimizing the normal deviation between the generated and theoretical surfaces. Numerical simulations demonstrate that the proposed method significantly suppresses twist-related topographic errors. In a benchmark moderate-helix case, the maximum residual deviation is controlled to approximately 2 µm. For a more demanding large-helix configuration, a two-level optimization strategy—combining machine-setting compensation and grinding-worm helix-angle adjustment—reduces the peak deviation from about 5.5 µm to 4.7 µm, corresponding to an improvement of approximately 15%. This confirms that worm-geometry tuning provides an additional, effective degree of freedom for high-helix cutter applications. Full article

Coastal seas around Aotearoa, New Zealand, are among the least observed parts of the global ocean, limiting our ability to monitor and forecast marine conditions. The Moana Project addresses this gap with a new observing system that includes temperature sensors mounted on commercial fishing gear—the Mangōpare fishing vessel network. This study presents the first evaluation of New Zealand’s operational ocean 4D-Var data assimilation system that incorporates these fishing vessel (FV) observations into a regional ROMS model. Using just over one year of operational forecasts, we show that FV temperature profiles significantly improve subsurface temperature representation, especially in coastal regions where satellite products have warm biases or miss key features such as upwelling and mesoscale variability. Assimilation of FV data reduces background temperature biases throughout the upper ocean and enhances forecast skill in areas influenced by major currents and dynamic coastal processes. We also identify sensitivity to periods of missing satellite sea surface temperature, which can lead to overfitting of the available observations. Overall, the results demonstrate that FV observations provide essential subsurface information and can substantially strengthen operational coastal ocean forecasting systems. Full article

Long-wavelength flank waviness plays a critical role in the excitation behavior of geared transmissions. While coordinate measuring machine (CMM) exports provide detailed geometric information, conventional evaluations typically focus on individual tooth curves and do not quantify circumferential inhomogeneity across teeth. This study introduces a tooth-to-tooth long-wavelength waviness inhomogeneity indicator (ΔW1) derived directly from Klingelnberg-style MKA plot files and demonstrates its behavior on a large industrial dataset comprising 3375 measured gear parts. Each flank curve was detrended using a second-order polynomial fit, and lobe-based waviness amplitudes (W1–W3) were extracted via sine–cosine projection. The proposed ΔW1 metric was defined as the difference between the maximum and minimum W1 values across measured teeth within the same part. To eliminate measurement edge effects, a mid-section evaluation (10–90% of the face width) was additionally performed. Population-level analysis revealed consistent separation between geometrically homogeneous and inhomogeneous parts, with ΔW1 values in the most critical components exceeding 7–9 µm after mid-section filtering. Unsupervised clustering based on ΔW1 and maximum W1 further distinguished a high-variability subset of parts exhibiting systematic long-wavelength modulation patterns. The results demonstrate that circumferential waviness variability can be quantified using standard CMM outputs without additional hardware or specialized measurement procedures. The proposed indicator provides a practical geometric screening tool for large production batches and establishes a reproducible framework for linking detailed flank geometry to manufacturing consistency assessment. Although acoustic validation is outside the scope of the present work, the metric is intended as an NVH-relevant geometric risk indicator for future vibroacoustic correlation studies. Full article

Kombucha is a beverage obtained through the fermentation of tea leaves by a symbiotic culture of bacteria and yeast called SCOBY. This beverage is popularly known for the potential health benefits associated with its consumption, which is the main reason for its commercial expansion over the last century. These potential benefits are linked to the presence of a wide variety of bioactive compounds, notably phenolic compounds and organic acids. This composition varies significantly depending on the fermentation conditions, which in turn modifies the beverage’s bioactive properties (i.e., antioxidant capacity or antimicrobial properties, among others). For this reason, the most recent advances in kombucha production are geared towards achieving standardized production, including strategies for enhancing bioactive content and fortification with functional ingredients. All these advances should satisfy quality control and regulatory compliance. However, despite the growing scientific and commercial interest in kombucha, current knowledge remains fragmented across different disciplines, highlighting the need for an updated and integrative overview of its composition, bioactivity, production variables, and safety aspects. In this review, nutritional, microbiological, and technological perspectives are integrated to provide an updated framework for understanding kombucha as a functional beverage, while also outlining key directions for future research and industrial application. Full article

Firefighters are exposed to complex combustion products and to contaminants carried on personal protective equipment (PPE). Occupational exposure as a firefighter is classified as carcinogenic. This review summarizes the current evidence on exposure environments, routes of uptake, contamination and secondary exposure from PPE, and the effectiveness and limits of decontamination approaches. Across incident types, smoke composition varies with the fuels and combustion conditions, but fine and ultrafine particles and semi-volatile organic chemicals are common. Biomonitoring confirms uptake after incidents. Self-contained breathing apparatus reduces inhalation exposure during active suppression, yet exposures persist through dermal absorption at ensemble interfaces and post-incident tasks. Protective ensembles can retain soot-bound polycyclic aromatic hydrocarbons, additive chemicals, and metals; volatiles and particles resuspension in vehicles and stations can extend exposure. Studies show that on-scene preliminary exposure reduction and laundering can lower contaminant burdens on PPE; however, removal remains incomplete and decreases when cleaning is delayed or when gear is aged. Emerging evidence raises additional concern for per- and polyfluoroalkyl substances from foams and coating materials, with limited data on exposure metrics and removability. The field lacks standardized, realistic contamination platforms and a dose-based definition of clean PPE. Integrated intervention studies linking exposure, secondary exposure pathways, biomarkers, and decontamination methods are needed to set performance-based targets and evaluate emerging hazards. Full article

This paper presents a numerical case study on the application of generative design to the shape optimisation of a spur gear body with consideration of manufacturing constraints and material properties. The presented results are obtained using numerical simulation and finite element analysis. A finite element-based generative design workflow was employed to evaluate weight reduction and stiffness performance under different manufacturing routes, including additive manufacturing, machining, and casting. The results show that the application of generative design enabled a gear-body mass reduction of up to 37.46–45.68% compared to the reference geometry while maintaining acceptable deformation levels. Designs constrained for additive manufacturing achieved the highest weight savings, whereas machining-constrained variants exhibited lower deformation values, indicating higher structural stiffness. Casting-oriented constraints resulted in more conservative geometries with locally reinforced regions. The study confirms that manufacturing constraints significantly influence the generated geometry and mechanical response, demonstrating that the manufacturing route acts as an independent design variable within the generative design process. The presented methodology provides practical guidance for the early-stage numerical optimisation of gear bodies and supports informed decision-making with respect to manufacturing technology selection. Full article

Gears, as critical power-transmission components in most power equipment, have a particularly urgent need for in situ inspection systems. Traditional gear inspection methods rely on contact inspection instruments, which are not only time-consuming, but also potentially damage the gear surface due to contact. This study delves into the detection requirements in the gear manufacturing process and establishes a rapid, non-contact detection mechanism and model using a CHCS. This model employs a CHCS to achieve high-speed, non-contact measurement on various surfaces with extremely high accuracy, enabling real-time monitoring of production process details, thereby improving production efficiency and ensuring product quality. Through actual inspection and comparison with a standard involute spur gear tooth profile model, this study implements a complete inspection system in a prototype. The results of gear inspection using a CHCS with an accuracy of 1 μm showed that the interquartile range of qualified gears under test (GUTs) was within 2.5 μm, and the beard line value was within 10 μm. The experiment demonstrated a layout equipped with a CHCS where the rotating axis represents the hobbing machine spindle. This method can be completed without moving the gear, enabling subsequent finishing processes. Full article

This paper presents a mathematical approach for analyzing the thermal behavior of a dual-permanent-magnet consequent-pole magnetically geared machine. The analytical method, referred to as harmonic modeling, employs a complex Fourier series and the Cauchy product to obtain solutions to the partial differential equations governing the temperature distribution in electrical machines. Unlike lumped-parameter thermal networks that provide only average quantities, the proposed approach enables the prediction of spatial temperature distributions. The machine is further investigated under various operating conditions, including different convection coefficients and loss levels. An 11-pole, 18-slot prototype was evaluated by comparison with finite element method (FEM) simulations. The results demonstrate that the proposed method agreed well with the FEM results, with errors below 10%, while requiring less than 2 s per calculation compared with approximately 20 s for FEM simulations. Full article

Safety on construction sites is an essential yet challenging issue due to the inherently hazardous nature of these sites. Workers are expected to wear Personal Protective Equipment (PPE), such as helmets, vests, and safety glasses, to prevent or minimize their exposure to injuries. However, ensuring compliance remains difficult, particularly in large or complex sites, which require a time-consuming and usually error-prone manual inspection process. The research proposes an automated PPE detection system utilizing the deep learning model YOLO11, which is trained on the CHVG dataset, to identify in real-time whether workers are adequately equipped with the necessary gear. The proposed PPE-EYE method, using YOLO11x, achieved a mAP50 of 96.9% and an inference time of 7.3 ms, which is sufficient for real-time PPE detection systems, in contrast to previous approaches involving the same dataset, which required 170 ms. The model achieved these results by employing data augmentation and fine-tuning. The proposed solution provides continuous monitoring with reduced human oversight and ensures timely alerts if non-compliance is detected, allowing the site manager to act promptly. It further enhances the effectiveness and reliability of safety inspections, overall site safety, and reduces accidents, ensuring consistency in follow-through of safety procedures to create a safer and more productive working environment for all involved in construction activities. Full article

In response to mounting resource and environmental pressures in the textile industry, this study investigates the feasibility of fiber-to-fiber closed-loop recycling for used firefighting protective clothing—a waste stream characterized by material homogeneity and large-scale disposal. Employing a mixed-methods approach combining stakeholder questionnaires, field investigations (n = 3650), and performance testing of retired aramid fabrics, this research systematically evaluates the technical, market, and systemic potential for circular regeneration. Results demonstrate strong multi-stakeholder support (over 89%) and significant consumer willingness to purchase recycled products (81.01–84% across categories), while material tests confirm the retained flame resistance and mechanical properties of the fabrics, enabling high-value applications. By constructing an integrated framework spanning technical, policy, market, and cultural dimensions, and proposing strategies of “targeted recycling” and “value reconstruction,” this work confirms the commercial viability and environmental benefit of recycling firefighting gear. It further offers a transferable model for advancing the circularity of other safety and protective textiles, with key innovations lying in its comprehensive full-chain assessment and the concurrent validation of stakeholder dynamics and material performance. Full article

Quiet drivetrains have become a central requirement in modern electric vehicles, where the absence of engine masking makes even subtle gear tones clearly audible. As a result, manufacturers are looking for more reliable ways to understand how design choices, manufacturing variability, and operating conditions shape gear noise and vibration. Digital Twin (DT) approaches—linking high-fidelity models with measured data throughout the product lifecycle—offer a potential route to achieve this, but their use in gear NVH is still emerging. This review examines recent work from the past decade on DT concepts applied to gears and drivetrain NVH, drawing together advances in simulation, metrology, sensing, and data exchange standards. The survey shows that several building blocks of an NVH-oriented twin already exist, yet they are rarely combined into an end-to-end workflow. Clear gaps remain. Current models still struggle with high-frequency behavior. Real-time operation is also limited. Manufacturing and test data are often disconnected from simulations. Validation practices lack consistent NVH metrics. Hybrid and surrogate modeling methods are used only to a limited extent. The sustainability benefits of reducing prototypes are rarely quantified. These gaps define the research directions needed to make DTs a practical tool for future gear NVH development. A research Gap Map is presented, categorizing these gaps and their impact. For each gap, we propose actionable future directions—from multiscale “hybrid twins” that merge test data with simulations, to benchmark datasets and standards for DT NVH validation. Closing these gaps will enable more reliable gear DTs that reduce development costs, improve acoustic quality, and support sustainable, data-driven NVH optimization. Full article

Accurate vibration measurement is crucial for maintaining the performance, reliability, and safety of automated manufacturing environments. Abnormal vibrations caused by faults in gears or bearings can degrade positional accuracy, reduce productivity, and, over time, significantly impair production efficiency and product quality. Such vibrations may also disrupt supply chains, cause financial losses, and pose safety risks to workers through collisions, falling objects, or other operational hazards. Conventional vibration measurement techniques, such as wired accelerometers and strain gauges, are typically limited to a few discrete measurement points. Achieving multi-point measurements requires numerous sensors, which increases installation complexity, wiring constraints, and setup time, making the process both time-consuming and costly. The integration of high-frame-rate (HFR) cameras with Digital Image Correlation (DIC) enables non-contact, multi-point, full-field vibration measurement of robot manipulators, effectively addressing these limitations. In this study, HFR cameras were employed to perform non-contact, full-field vibration measurements of industrial robots. The HFR camera recorded the robot’s vibrations at 1000 frames per second (fps), and the resulting video was decomposed into individual frames according to the frame rate. Each frame, with a resolution of 1920 × 1080 pixels, was divided into 128 × 128 pixel blocks with a 64-pixel stride, yielding 435 sub-images. This setup effectively simulates the operation of 435 virtual vibration sensors. By applying mask processing to these sub-images, eight key points representing critical robot components were selected for multi-point DIC displacement measurements, enabling effective assessment of vibration distribution and real-time vibration visualization across the entire manipulator. This approach allows simultaneous capture of displacements across all robot components without the need for physical sensors. The transfer function is defined in the frequency domain as the ratio between the output displacement of each robot component and the input excitation applied by the shaker mounted on the end-effector. The frequency–domain transfer functions were computed for multiple robot components, enabling accurate and full-field vibration analysis during operation. Full article

Alpha-gal syndrome (AGS) is an emerging, relatively newly recognized allergic disorder with clinical manifestations that occur as a result of hypersensitivity reactions to oligosaccharide galactose-α-1,3-galactose (α-gal), a carbohydrate present in lower-mammalian meat, dairy products, and some biopharmaceutical products. These reactions are delayed with oral ingestion of the antigen but can be immediate with intravascular or other parenteral antigenic exposure. Over the past 15 years, many revelations have occurred in the realm of AGS. However, there is still a huge unmet need related to its pathophysiology, diagnostics, timely recognition, and management. This article is geared towards providing a review of AGS for healthcare providers (HCPs) from all realms of medicine. It is a universal challenge, with cases being recognized from various parts of the world. Hence, it is critically important for HCPs planet-wide to pay heed to the prompt recognition of AGS and educate their patients. This can prevent morbidity as well as potentially fatal complications like severe anaphylaxis. It is a narrative clinical review. The PubMed database was searched from 2009 to 2025. Alpha-gal syndrome and related topics were included in the search engine. Full article

The trajectory accuracy of equipment with complex motion paths presents a critical engineering challenge. Targeting the precision issues in the operating trajectory of a carbon-free car, this paper proposes an optimization method for complex mechanical trajectories. Firstly, this study investigates gear backlash-induced return error on the steering precision of a carbon-free cam mechanism of cars. Secondly, considering the cumulative return error of gear transmission between gear groups, a comprehensive mathematical model was established to guide the optimization of cam structure. Finally, the steering accuracy before and after optimization is quantitatively evaluated by trajectory calculation. In addition, the optimized structure was tested and compared with the numerical calculation. The experimental and numerical calculation results are highly consistent. The numerical calculation results show that by adjusting the transmission ratio of the gear set and optimizing the cam profile, the cam deflection angle error is reduced by 24.74% and 27.15%, respectively, and the comprehensive cumulative deflection error of the car is significantly reduced by 45.31%. More importantly, the research provides crucial technical support and guidance for achieving precise control and planning complex paths in automated production lines. Full article

The objective of this study was to investigate electron beam hardening (EBH) technology and compare its performance with laser beam hardening (LBH) in the context of manufacturing components such as gears, which increasingly employ submicron bainitic steels. Given the stringent demands for durability and fatigue resistance of gear teeth, identifying an optimal surface hardening method is essential for extending service life. Comprehensive analyses, including light and electron microscopy, hardness testing, tribocorrosion testing, and X-ray diffraction for phase composition, were conducted. The EBH-treated layer exhibited a slightly higher hardness (by 26 HV) compared to the LBH-treated layer (average 654 HV), while the base material measured 393 HV. The EBH process produced a uniform hardness distribution with a subsurface zone of reduced hardness. In contrast, LBH resulted in a surface oxide layer absent in EBH due to its vacuum environment. Both techniques reduced the residual austenite content in the surface layer from 22.5% to approximately 1.3%–1.4%. Notably, EBH achieved comparable hardening effects with nearly half the energy input of LBH, demonstrating superior energy efficiency and industrial feasibility. Application of the developed EBH process to an actual gear component confirmed its practical potential for modern gear manufacturing. Full article