Search Results (7)

The primary focus of enhancing the efficiency of operations in the Industry 4.0 setting is Predictive and Preventive Maintenance (PPM). The paper introduces a predictive-maintenance system based on the Unified Namespace (UNS), which involves real-time sensor measurements, photogrammetry, and modelling of a digital twin to improve fault prediction and responsiveness to maintenance. This experiment was conducted over six months in a medium-sized discrete electromechanical production plant equipped with motors, Variable Speed Drives (VSDs), robot/cobots, precision grip systems, pipework systems, Magnemotion/linear motor drives, and a CNC machine. The continuous data, such as high-frequency vibration, temperature, current, and pressure, were monitored and analysed with machine-learning models, including support-vector machines, Gradient Boosting, long-short-term memory, and Random Forest, through which temporal degradation can be predicted. UNS architecture integrated all sensor and imaging data into a vendor-neutral data model through OPC UA to help ensure that all experiments could be integrated consistently and be updated in real time to real digital twins. The suggested system correctly identified mechanical and electrical failures and predicted failures before they really took place. Consequently, machine downtime was reduced by 42.25%, and Mean Time to Repair (MTTR) by 36%, compared to the prior six-month baseline period. These improvements were associated with earlier anomaly detection and digital-twin-supported pre-inspection. Overall, the findings indicate that the integration of UNS with multi-modal sensing and digital-twin technologies may enhance predictive maintenance performance in comparable industrial settings. The framework provides a data-driven, scalable solution to organisations that aim to modernise their maintenance processes, attain greater reliability and better equipment utilisation, as well as enhanced Industry 4.0 preparedness. Full article

Background: Grip control is a critical determinant of fencing performance, requiring both stability and precision. Traditional measures of hand strength, such as dynamometry, provide only a global estimate and cannot capture finger-specific load distribution. Yet, upper-extremity overuse syndromes, tendinopathies of the wrist and digital flexors are common in fencers, underscoring the need for more granular assessments that may inform clinical practice, especially in prehension contexts. Methods: This pilot study included eight elite épée fencers from the Polish National Team (age: 23.9 ± 4.9 years; training experience: >10 years) tested using a novel épée handle instrumented with five force-sensitive resistors (FSRs) embedded beneath each finger. Participants performed two 5-s maximal voluntary contractions (MVCs) for each of the three conditions—Pinch (thumb + index), Trio (middle + ring + small), and Whole (all digits). Standard handheld dynamometry was also performed to provide a global reference measure. Results: Maximal grip strength measured with a dynamometer (65.3 ± 11.7 kgf) was substantially higher than finger-specific forces captured with the FSR handle (14.4 ± 4.4 kgf). Isolated Pinch contractions (83.0 ± 29.2 N) were significantly stronger than their integrated contribution within the Whole-hand condition (54.7 ± 16.3 N; Z = 2.52, p = 0.012), whereas Trio forces did not differ significantly (p = 0.263). On average, radial digits (thumb + index) contributed ~39% and ulnar digits (middle, ring, small) ~61% of Whole output, with the thumb and middle finger producing the largest forces. Conclusions: This pilot study demonstrates the feasibility of using an FSR-instrumented épée handle to capture finger-specific grip contributions in elite fencers. Despite limited statistical power (n = 8), the observed effects provide initial quantitative evidence for sport-specific, digit-level assessment, showing potential clinical utility in detecting maladaptive load-transfer mechanisms and informing rehabilitation and injury-prevention programs. Full article

As a key piece of equipment in badminton, the surface treatment technology of rackets has garnered significant attention in the fields of material science and sports engineering. This study is the first to systematically review research on racket coatings, integrating interdisciplinary knowledge on the classification of functional coatings, their performance-enhancing principles, and their relationship with competitive levels, thereby addressing a gap in theoretical research in this field. This study focuses on four major functional coating systems: superhydrophobic coatings (to improve environmental adaptability and reduce air resistance), anti-scratch coatings (to prolong the life of the equipment), vibration-damping coatings (to optimise vibration damping performance), and strength-enhancing coatings (to safeguard structural stability). In badminton, differences in player skill levels and usage scenarios lead to variations in racket materials, which, in turn, result in different preparation processes and performance effects. The use of vibration-damping materials alleviates the impact force on the wrist, effectively preventing sports injuries caused by prolonged training; leveraging the aerodynamic properties of superhydrophobic technology enhances racket swing speed, thereby improving hitting power and accuracy. From the perspective of performance optimization, coating technology improves athletic performance in three ways: nanocomposite coatings enhance the fatigue resistance of the racket frame; customized damping layers reduce muscle activation delays; and surface energy regulation technology improves grip stability. Challenges remain in the industrial application of environmentally friendly water-based coatings and the evaluation system for coating lifespan under multi-field coupling conditions. Future research should integrate intelligent algorithms to construct a tripartite optimization system of “racket-coating-user” and utilize digital sports platforms to analyze its mechanism of influence on professional athletes’ tactical choices, providing a theoretical paradigm and technical roadmap for the targeted development of next-generation smart badminton rackets. Full article

In response to the growing demand for automation in aerospace harness manufacturing, this study proposes a digital twin-based intelligent monitoring system for robotic wiring operations. The system integrates a seven-degree-of-freedom robotic platform with an adaptive servo gripper and employs a five-dimensional digital twin framework to synchronize physical and virtual entities. Key innovations include a coordinated motion model for minimizing joint displacement, a particle-swarm-optimized backpropagation neural network (PSO-BPNN) for adaptive gripping based on wire characteristics, and a virtual–physical closed-loop interaction strategy covering the entire wiring process. Methodologically, the system enables motion planning, quality prediction, and remote monitoring through Unity3D visualization, SQL-driven data processing, and real-time mapping. The experimental results demonstrate that the system can stably and efficiently complete complex wiring tasks with 1:1 trajectory reproduction. Moreover, the PSO-BPNN model significantly reduces prediction error compared to standard BPNN methods. The results confirm the system’s capability to ensure precise wire placement, enhance operational efficiency, and reduce error risks. This work offers a practical and intelligent solution for aerospace harness production and shows strong potential for extension to multi-robot collaboration and full production line scheduling. Full article

Hand prehension requires highly coordinated control of contact forces. The high-dimensional sensorimotor system of the human hand operates at ease, but poses several challenges when replicated in artificial hands. This paper investigates how the dynamical synergies, coordinated spatiotemporal patterns of contact forces, contribute to the hand grasp, and whether they could potentially capture the force primitives in a low-dimensional space. Ten right-handed subjects were recruited to grasp and hold mass-varied objects. The contact forces during this multidigit prehension were recorded using an instrumented grip glove. The dynamical synergies were derived using principal component analysis (PCA). The contact force patterns during the grasps were reconstructed using the first few synergies. The significance of the dynamical synergies, the influence of load forces and task configurations on the synergies were explained. This study also discussed the contribution of biomechanical constraints on the first few synergies and the current challenges and possible applications of the dynamical synergies in the design and control of exoskeletons. The integration of the dynamical synergies into exoskeletons will be realized in the near future. Full article

Grip force control during robotic in-hand manipulation is usually modeled as a monolithic task, where complex controllers consider the placement of all fingers and the contact states between each finger and the gripped object in order to compute the necessary forces to be applied by each finger. Such approaches normally rely on object and contact models and do not generalize well to novel manipulation tasks. Here, we propose a modular grip stabilization method based on a proposition that explains how humans achieve grasp stability. In this biomimetic approach, independent tactile grip stabilization controllers ensure that slip does not occur locally at the engaged robot fingers. Local slip is predicted from the tactile signals of each fingertip sensor i.e., BioTac and BioTac SP by Syntouch. We show that stable grasps emerge without any form of central communication when such independent controllers are engaged in the control of multi-digit robotic hands. The resulting grasps are resistant to external perturbations while ensuring stable grips on a wide variety of objects. Full article

This study describes a technique for measuring human grip forces exerted on a cylindrical object via a sensor array. Standardised resistor-based pressure sensor arrays for industrial and medical applications have been available for some time. We used a special 20 mm diameter grip rod that subjects could either move actively with their fingers in the horizontal direction or exert reactive forces against opposing forces generated in the rod by a linear motor. The sensor array film was attached to the rod by adhesive tape and covered approximately 45 cm² of the rod surface. The sensor density was 4/cm² with each sensor having a force resolution of 0.1 N. A scan across all sensors resulted in a corresponding frame containing force values at a frame repetition rate of 150/s. The force value of a given sensor was interpreted as a pixel value resulting in a false-colour image. Based on remote sensed image analysis an algorithm was developed to distinguish significant force-representing pixels from those affected by noise. This allowed tracking of the position of identified fingers in subsequent frames such that spatio-temporal grip force profiles for individual fingers could be derived. Moreover, the algorithm allowed simultaneous measurement of forces exerted without any constraints on the number of fingers or on the position of the fingers. The system is thus well suited for basic and clinical research in human physiology as well as for studies in psychophysics. Full article