Search Results (719)

Outdoor access, often referred to as pop holes, is widely used to improve the production and welfare of hens. Such cage-free environments present an opportunity for precision flock management via best environmental control practices. However, outdoor access disrupts the integrity of the indoor environment, including properly planned ventilation. Moreover, complaints exist that hens do not use the holes to access the outdoor environment due to the strong incoming airflow through the outdoor access, as they behave as uncontrolled air inlets in a negative pressure ventilation system. As the egg industry transitions to cage-free systems, there is an urgent need for validated computational fluid dynamics (CFD) models to optimize ventilation strategies that balance animal welfare, environmental control, and production efficiency. We developed and validated CFD models of a cage-free hen house with outdoor access by specifying real-world conditions, including two exhaust fans, sidewall ventilation inlets, wire-meshed pens, outdoor access, and plenum inlets. The simulations of four ventilation scenarios predict the measured air flow velocity with an error of less than 50% for three of the scenarios, and the simulations predict temperature with an error of less than 6% for all scenarios. Plenum-based systems outperformed sidewall systems by up to 136.3 air changes per hour, while positive pressure ventilation effectively mitigated disruptions to outdoor access. We expect that knowledge of improved ventilation strategy will help the egg industry improve the welfare of hens cost-effectively. Full article

To address the issues of hydrogen embrittlement, creep, and fatigue that commonly occur in the welds of hydrogen production reactor operating under hydrogen exposure, high temperature and high pressure, this study proposes adding Si and Mo as reinforcing elements to the welding materials to enhance weld performance. Given the varying performance requirements of different weld layers in the stacked weld, a gradient performance optimization method for the stacked weld of hydrogen production reactors based on the response surface methodology (RSM)–genetic algorithm (GA) is proposed. Using tensile strength, the hydrogen embrittlement sensitivity index, fatigue strain strength, creep rate and weld performance evaluation indices, a high-precision regression model for Si and Mo contents and weld performance indices was established through RSM and analysis of variance (ANOVA). A multi-objective optimization mathematical model for gradient improvement of the stacked weld was also established. This model was solved using a GA to obtain the optimal element content combination added to the welding wire and the optimal weld thickness for each weld layer. Finally, submerged arc welding experiments of the stacked weld were conducted according to the optimization results. The results show that the tensile strength of the base layer, filling layer and cover layer of the stacked weld increased by 5.60%, 6.16% and 4.53%, respectively. Hydrogen embrittlement resistance increased by 70.56%, 52.40% and 45.16%, respectively. The fatigue and creep resistance were also improved. The experimental results validate the feasibility and accuracy of the proposed optimization method. Full article

Digital Twins (DTs) are transforming manufacturing by bridging the physical and digital worlds, enabling real-time insights, predictive analytics, and enhanced decision making. In Industry 4.0, DTs facilitate automation and data integration, while Industry 5.0 emphasizes human-centric, resilient, and sustainable production. However, implementing DTs in robotic metal additive manufacturing (AM) remains challenging because of the complexity of the wire-based laser metal deposition (LMD) process, the need for real-time monitoring, and the demand for advanced defect detection to ensure high-quality prints. This work proposes a structured DT architecture for a robotic wire-based LMD cell, following a standard framework. Three DT implementations were developed. First, a real-time 3D simulation in RoboDK, integrated with a 2D Node-RED dashboard, enabled motion validation and live process monitoring via MQTT (message queuing telemetry transport) telemetry, minimizing toolpath errors and collisions. Second, an Industrial IoT-based system using KUKA iiQoT (Industrial Internet of Things Quality of Things) facilitated predictive maintenance by analyzing motor loads, joint temperatures, and energy consumption, allowing early anomaly detection and reducing unplanned downtime. Third, the Meltio dashboard provided real-time insights into the laser temperature, wire tension, and deposition accuracy, ensuring adaptive control based on live telemetry. Additionally, a prescriptive analytics layer leveraging historical data in FireStore was integrated to optimize the process performance, enabling data-driven decision making. Full article

The electrodynamics of current provide much of our technology, from telegraphs to the wired infrastructure powering the circuits of our electronic technology. Current flow is analyzed by its own rules that involve the Maxwell Ampere law and magnetism. Electrostatics does not involve magnetism, and so current flow and electrodynamics cannot be derived from electrostatics. Practical considerations also prevent current flow from being analyzed one charge at a time. There are too many charges, and far too many interactions to allow computation. Current flow is essential in biology. Currents are carried by electrons in mitochondria in an electron transport chain. Currents are carried by ions in nerve and muscle cells. Currents everywhere follow the rules of current flow: Kirchhoff’s current law and its generalizations. The importance of electron and proton flows in generating ATP was discovered long ago but they were not analyzed as electrical currents. The flow of protons and transport of electrons form circuits that must be analyzed by Kirchhoff’s law. A chemiosmotic theory that ignores the laws of current flow is incorrect physics. Circuit analysis is easily applied to short systems like mitochondria that have just one internal electrical potential in the form of the Hodgkin Huxley Katz (HHK) equation. The HHK equation combined with classical descriptions of chemical reactions forms a computable model of cytochrome c oxidase, part of the electron transport chain. The proton motive force is included as just one of the components of the total electrochemical potential. Circuit analysis includes its role just as it includes the role of any other ionic current. Current laws are now needed to analyze the flow of electrons and protons, as they generate ATP in mitochondria and chloroplasts. Chemiosmotic theory must be replaced by an electro-osmotic theory of ATP production that conforms to the Maxwell Ampere equation of electrodynamics while including proton movement and the proton motive force. Full article

In the process of high-speed wire rod production, flying steel accidents may occur due to various reasons. Current detection methods relying on sensors like hardware make debugging complex as well as limit real-time and accuracy. These methods are complicated to debug, and the real-time and accuracy of detection are poor. Therefore, this paper proposes a flying steel detection method based on improved You Only Look Once v8 (YOLOv8), which can realize high-precision flying steel detection based on machine vision through the monitoring video of the production site. Firstly, the Omni-dimensional Dynamic Convolution (ODConv) is added to the backbone network to improve the feature extraction ability of the input image. Then, a lightweight C2f-PCCA_RVB module is proposed to be integrated into the neck network, so as to carry out the lightweight design of the neck network. Finally, the Efficient Multi-Scale Attention (EMA) module is added to the neck network to fuse the context information of different scales and improve the feature extraction ability. The experimental results show that the average accuracy (mAP@0.5) of the flying steel detection method based on the improved YOLOv8 is 99.1%, and the latency is reduced to 2.5 ms, which can realize the real-time accurate detection of the flying steel. Full article

The objective of this paper is to evaluate the capability of various steel rope manufacturers to maintain the desired variability within the strength class of wires used in the production of steel ropes. From a service life perspective, it is optimal to achieve the narrowest possible strength class interval for wires integrated into steel ropes. However, the applicable EN 12385 standards permit a relatively wide interval of allowable strength class dispersion. The analysis encompasses 112 steel ropes tested over the period from 2000 to 2025. For the purpose of evaluating rope quality in terms of wire strength variability, the ropes were categorized into four quality classes. The assessment of wire strength was conducted using statistical quality control methods, specifically through the application of control charts. Based on these methods, the stability and capability of wire strength within each rope were verified. The results highlight the differences in wire strength performance across the evaluated quality classes. Full article

Greenhouse horticulture plays an important role globally by producing nutritious fruits and vegetables with high resource use efficiency. Modern greenhouses are large-scale high-tech production factories that are increasingly data-driven, and where climate and irrigation control are gradually becoming more autonomous. This is enabled by technological developments and driven by shortages in skilled labor and the demand for improved resource use efficiency. In the Autonomous Greenhouse Challenge, it has been shown that controlling greenhouse cultivation can be done efficiently with intelligent algorithms. For an optimal strategy, however, it is essential that control algorithms properly account for crop responses, which requires appropriate sensors, reliable data, and accurate models. This paper presents the results of the 4th Autonomous Greenhouse Challenge, in which international teams developed six intelligent algorithms that fully controlled a dwarf tomato cultivation, a crop that is well-suited for robotic harvesting, but for which little prior cultivation data exists. Nevertheless, the analysis of the experiment showed that all teams managed to obtain a profitable strategy, and the best algorithm resulted a production equivalent to 45 kg/m²/year, higher than in the commercial practice of high-wire cherry tomato growing. The predominant factor was found to be the much higher plant density that can be achieved in the applied growing system. More difficult challenges were found to be related to measuring crop status to determine the harvest moment. Finally, this experiment shows the potential for novel greenhouse cultivation systems that are inherently well-suited for autonomous control, and results in a unique and rich dataset to support future research. Full article

Since lightweight design and construction safety is a crucial element in different sectors of industry, the use of SMA wires in composites could improve the monitoring and adjustment of mechanical properties starting from the product development process through to field use. This work shows how embedded SMA wires can lead to a better understanding of applied forces to a composite structure made of GFRP laminates. To achieve this, different methods will be addressed. Besides mechanical testing of the GFRP-samples with embedded SMA wires, NDT-methods like active thermography, high-frequency ultrasonic testing, and computer tomography are used to detect the SMA wires, whereby thermography and computer tomography are best suited. In this study, the location and the amount of the applied force on GFRP composites with embedded SMA wires could be characterized with relative resistance changes. It is shown that SMA wires with a diameter of 250 µm are preferred to wires with a diameter of 100 µm due to production process and better performance under load (4N force plateau for 100 µm in contrast to 25N force plateau for 250 µm wires). Furthermore, Young’s modulus of the GFRP composites with embedded SMA wires was measured and is similar for various samples with 30.8 GPa on average. Full article

Industries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and intrinsic defects. This information is necessary for establishing the operating process window and for the quality characterization of the part. Therefore, this work presents a methodology that combines information captured from a vision-based monitoring system with the output of Computed Tomography (CT) towards the knowledge generation and process optimization of wire DED-LB. The design of experiments as well as the interpretation of the results are achieved by employing Nested ANOVA where the dependency of cross-sectional stability on the laser power parameter is demonstrated, enabling, at the same time, the understanding of unstructured datasets where multiple parameters vary at different levels. Finally, this work can be the pillar for adopting new production and part requirements while also giving directions about the effect of control strategies on the part quality. Full article

5G private mobile networks are becoming a platform for ‘wire-free’ networking for professional applications in smart industry sectors, such as automated warehousing, logistics, autonomous vehicle deployments in campus environments, mining, material processing, and more. It is expected that most of these Machine-to-Machine (M2M) and Industrial Internet of Things (IIoT) communication paths will be realized wirelessly, as the advantages of providing flexibility are obvious compared to hard-wired network installations. Unfortunately, the deployment of private 5G networks in smart industries has faced delays due to a combination of high costs, technical challenges, and uncertain returns on investment, which is reflected in troublesome access to fully operational private networks. To obtain insight into occupational exposure to radiofrequency electromagnetic fields (RF EMF) emitted by 5G private mobile networks, an analysis of RF EMF due to different types of 5G equipment was carried out on a real case scenario in the production and logistic (warehouse) industrial sector. A private standalone (SA) 5G network operating at 3.7 GHz in a real industrial environment was numerically modeled and compared with in situ RF EMF measurements. The results show that RF EMF exposure of the workers was far below the existing exposure limits due to the relatively low power (1 W) of indoor 5G base stations in private networks, and thus similar exposure scenarios could also be expected in other deployed 5G networks. In the analyzed RF EMF exposure scenarios, the radio transmitter—so-called ‘radio head’—installation heights were relatively low, and thus the obtained results represent the worst-case scenarios of the workers’ exposure that are to be expected due to private 5G networks in smart industries. Full article

As an indispensable piece of production equipment in the industrial field, wire rope is directly related to personnel safety and the normal operation of equipment. Therefore, it is necessary to perform broken wire detection. Deep learning has powerful feature-learning capabilities and is characterized by high accuracy and efficiency, and the YOLOv8 object detection model has been adopted to detect wire breaks in electromagnetic signal images of wire rope, achieving better results. Nevertheless, the black box problem of the model brings a new trust challenge, and it is difficult to determine the correctness of the model’s decision and whether it has any potential problems, so an interpretability study needed to be carried out. In this work, a perturbation-based interpretability method—ESTC (Eliminating Splicing and Truncation Compensation)—is proposed, which distinguishes itself from other methods of the same type by targeting the signaling object instead of the ordinary object. ESTC is compared with other model-agnostic interpretable methods, LIME, RISE, and D-RISE, using the same model on the same test set. The results indicate that our proposed method is objectively superior to the others, and the interpretability analysis shows that the model predicts in a way that is consistent with the priori knowledge of the manual rope inspection. This not only increases the credibility of using the object detection model for broken wire detection but also has important implications for the practical application of using object detection model to detect wire breaks. Full article

This study develops a one-pot anodic templating electrodeposition strategy using dual-cation-crosslinking and interpenetrating networks, coupled with pulsed electrical signals, to fabricate a vessel-mimetic multilayered tubular hydrogel. Typically, the anodic electrodeposition is performed in a mixture of sodium alginate (SA) and carboxymethyl chitosan (CMC), with the ethylenediaminetetraacetic acid calcium disodium salt hydrate (EDTA·Na₂Ca) incorporated to provide a secondary ionic crosslinker (i.e., Ca²⁺) and modulate the cascade reaction diffusion process. The copper wire electrodes serve as templates for electrochemical oxidation and enable a copper ion (i.e., Cu²⁺)-induced tubular hydrogel coating formation, while pulsed electric fields regulate layer-by-layer deposition. The dual-cation-crosslinked interpenetrating hydrogels (CMC/SA-Cu/Ca) exhibit rapid growth rates and tailored mechanical strength, along with excellent antibacterial performance. By integrating the unique pulsed electro-fabrication with biomimetic self-assembly, this study addresses challenges in vessel-mimicking structural complexity and mechanical compatibility. The approach enables scalable production of customizable multilayered hydrogels for artificial vessel grafts, smart wound dressings, and bioengineered organ interfaces, demonstrating broad biomedical potential. Full article

In recent years, with the innovation and continuous development of additive manufacturing technology, research on wire arc additive manufacturing technology (WAAM) has become increasingly common and in-depth in the chemical industry, mold manufacturing, and other fields. Therefore, it has attracted the attention of many universities, research institutes, and aerospace industries, conducted in-depth research on WAAM technology, and achieved certain research results. This paper briefly summarizes the current research status of arc additive manufacturing technology and summarizes the application status of WAAM technology in product development, personalized customization, traditional process replacement, “material–structure–function” integration, mold repair, etc. WAAM technology has huge development potential and good application prospects. In the future, arc additive manufacturing will develop in the direction of intelligence and high precision. Full article

Reducing structural mass and volume is critical to improving efficiency and payload capacity in next-generation small satellites and CubeSats. Additive manufacturing, particularly material extrusion, offers design flexibility and enables the production of lightweight, functional metallic components. This study investigates the integration of nickel–titanium shape memory alloy wires into aluminum-based matrices using a sinter-based material extrusion process, aiming to develop compact actuator systems for aerospace applications. A customized AlSi7Mg aluminum alloy feedstock was extruded into filament form, printed, and embedded with shape memory alloy wires, allowing consolidation during sintering. X-ray micro-computed tomography was used to analyze internal defects and matrix–wire interfacial contact, before and after sintering. Tensile testing of the embedded actuator structures revealed effective mechanical bonding and actuation behavior. The results demonstrate that controlled shrinkage and interfacial bonding enable reliable embedding of shape memory elements without compromising structural integrity. This work provides a promising framework for developing multifunctional aerospace components, where active actuation and structural efficiency can be combined through advanced material extrusion-based manufacturing. Full article

The study aimed to establish effective tools and methodologies for optimizing the bending process of metal wires, particularly focusing on the performance of SUS304 stainless steel in manufacturing torsion springs. This includes addressing challenges like spring-back and ensuring product quality and lifespan. The research employed a combination of analytical approaches, computer simulations using the Finite Element Method (FEM), and mechanical tests to validate the bending process. The mathematical analysis provided a theoretical framework, while FEA simulations allowed for the assessment of stress distribution and strain during bending. The simulations indicated that strains were distributed over a larger fiber than initially assumed, allowing for smaller bending radii without compromising material integrity. Using analytical models and supported by FEM, the study identified an effective range of bending radius values based on mechanical properties and wire radius. Laboratory tests confirmed that the bending process can be executed effectively, with no defects observed in the wire bending. Experimental tests validated these findings, showing consistent improvement in the accuracy, structural integrity, and durability of the formed wires. These results provide practical guidance for manufacturers seeking enhanced product quality and performance. Full article