Search Results (322)

Inspection, maintenance, and repair (IMR) operations on underwater infrastructure remain costly and time-intensive because fully teleoperated remote operated vehicle s(ROVs) lack the range and dexterity necessary for precise cooperative underwater manipulation, and the alternative of using professional divers is ruled out due to the risk involved. This work presents and experimentally validates an autonomous, dual-I-AUV (Intervention–Autonomous Underwater Vehicle) system capable of assembling rigid pipeline segments through coordinated actions in a confined underwater workspace. The first I-AUV is a Girona 500 (4-DoF vehicle motion, pitch and roll stable) fitted with multiple payload cameras and a 6-DoF Reach Bravo 7 arm, giving the vehicle 10 total DoF. The second I-AUV is a BlueROV2 Heavy equipped with a Reach Alpha 5 arm, likewise yielding 10 DoF. The workflow comprises (i) detection and grasping of a coupler pipe section, (ii) synchronized teleoperation to an assembly start pose, and (iii) assembly using a kinematic controller that exploits the Girona 500’s full 10 DoF, while the BlueROV2 holds position and orientation to stabilize the workspace. Validation took place in a 12 m × 8 m × 5 m water tank. Results show that the paired I-AUVs can autonomously perform precision pipeline assembly in real water conditions, representing a significant step toward fully automated subsea construction and maintenance. Full article

Repairing veneer defects is the key to ensuring the quality of plywood. In order to improve the maintenance quality and material utilization efficiency during the maintenance process, this paper proposes a bidirectional maintenance method based on gear rack transmission and its related equipment. Based on the working principle, a geometric relationship model was established, which combines the structural parameters of the mold, punch, and gear system. Simultaneously, it solves the problem of motion attitude analysis of conjugate tooth profiles under non-standard meshing conditions, aiming to establish a constraint relationship between stamping motion and structural design parameters. On this basis, a constrained optimization model was developed by integrating multi-objective optimization theory to maximize maintenance efficiency. The NSGA-III algorithm is used to solve the model and obtain the Pareto front solution set. Subsequently, three optimal parameter configurations were selected for simulation analysis and experimental platform construction. The simulation and experimental results indicate that the veneer repair time ranges from 0.6 to 1.8 seconds, depending on the stamping speed. A reduction of 28 mm in die height decreases the repair time by approximately 0.1 seconds, resulting in an efficiency improvement of about 14%. The experimental results confirm the effectiveness of the proposed method in repairing veneer defects. Vibration measurements further verify the system’s stable operation under parametric modeling and optimization design. The main vibration response occurs during the meshing and disengagement phases between the gear and rack. Full article

Educational buildings, including schools, nurseries and universities, face stricter regulation and design control on indoor air quality (IAQ) and thermal conditions than other built environments, as these may affect children’s health and wellbeing. In this scoping review, wide-ranging health, performance, and absenteeism consequences of poor—and benefits of good—IAQ and thermal conditions are evaluated, focusing on source control, ventilation and air purification interventions. Economic impacts of interventions in educational buildings have been evaluated to enable the assessment of tangible building-related costs and savings, alongside less easily quantifiable improvements in educational attainment and reduced healthcare. Key recommendations are provided to assist decision makers in pathways to provide clean air, at an optimal temperature for students’ learning and health outcomes. Although the role of educational buildings can be challenging to isolate from other socio-economic confounders, secondary short- and long-term impacts on attainment and absenteeism have been demonstrated from the health effects associated with various pollutants. Sometimes overlooked, source control and repairing existing damage can be important cost-effective methods in minimising generation and preventing ingress of pollutants. Existing ventilation standards are often not met, even when mechanical and hybrid ventilation systems are already in place, but can often be achieved with a fraction of a typical school budget through operational and maintenance improvements, and small-scale air-cleaning and ventilation technologies, where necessary. Full article

This paper presents a stochastic analysis of a two-unit cold standby system incorporating imperfect switching mechanisms. Each unit operates in one of three states: normal, partial failure, or total failure. Employing Markov processes, the study evaluates system reliability by examining the mean time to failure (MTTF) and steady-state availability metrics. Failure and repair times are assumed to follow exponential distributions, while the switching mechanism is modeled as either perfect or imperfect. The results highlight the significant influence of switching reliability on both MTTF and system availability. This analysis is crucial for optimizing the performance of complex systems, such as thermal power plants, where continuous and reliable operation is imperative. The study also aligns with recent research trends emphasizing the integration of preventive maintenance and advanced reliability modeling approaches to enhance overall system resilience. Full article

The improvement of environmental conditions has become a priority for governments and legislators. New electrified mobility systems are increasingly present in our environment, as they enable the reduction of polluting emissions. Electric vehicles (EVs) are one of the fastest-growing alternatives to date, with exponential growth expected over the next few years. In this article, the various charging modes for EVs are explored, and the risks associated with charging technologies are analysed, particularly for charging systems in high-power DC with Lithium battery energy storage, given their long market deployment and characteristic behaviour. In particular, the Arc Flash (AF) risk present in high-power DC chargers will be studied, involving numerous simulations of the charging process. Subsequently, the Incident Energy (IE) analysis is carried out at different specific points of a commercial high-power ‘Mode 4’ charger. For this purpose, different analysis methods of recognised prestige, such as Doan, Paukert, or Stokes and Oppenlander, are applied, using the latest version of the ETAP^® simulation tool version 22.5.0. This study focuses on quantifying the potential severity (consequences) of an AF event, assuming its occurrence, rather than performing a probabilistic risk assessment according to standard methodologies. The primary objective of this research is to comprehensively quantify the potential consequences for workers involved in the operation, maintenance, repair, and execution of tasks related to EV charging systems. This analysis makes it possible to provide safe working conditions and to choose the appropriate and necessary personal protective equipment (PPE) for each type of operation. It is essential to develop this novel process to quantify the consequences of AF and to protect the end users of EV charging systems. Full article

A particularly important activity carried out by railway infrastructure managers to maintain railway devices in full working order is the diagnostic process. It increases the level of railway safety. The diagnostic process involves collecting information about the equipment through inspections, tests, functional trials, parameter measurements, and analysis of the working environment, followed by comparing the obtained information with the required parameters or permissible conditions. This activity also enables the formulation of a technical diagnosis regarding the current ability of the devices to perform its intended functions, taking into account the impact of its technical condition on railway traffic safety. This is especially important in the case of railway traffic control devices, as these devices are largely responsible for ensuring railway traffic safety. The collection of data on the condition of railway traffic control devices in the form of Big Data sets and diagnostic inference is an effective factor in making operational decisions for such devices. It enables the acquisition of complete information about the actual course of the exploitation process and allows for obtaining reliable information necessary to manage this process, particularly in the areas of diagnostics forecasting of devices conditions, renewal, and organization of maintenance and repair facilities. To support this, a service data acquisition and analysis system for railway traffic control devices (SADEK) was developed. This system can serve as a software platform for maintenance needs in the railway sector. Full article

The efficient and reliable maintenance and repair of industrial machinery depend critically on circuit diagrams, which serve as essential references for troubleshooting and must be updated when machinery is modified. However, many circuit diagrams are not available in structured, machine-readable format; instead, they often exist as unstructured PDF files, rendered images, or even photographs. Existing digitization methods often address isolated tasks, such as symbol detection, but fail to provide a comprehensive solution. This paper presents a novel pipeline for extracting the underlying graph structures of circuit diagrams, integrating image preprocessing, pattern matching, and graph extraction. A U-net model is employed for noise removal, followed by gray-box pattern matching for device classification, line detection by morphological operations, and a final graph extraction step to reconstruct circuit connectivity. A detailed error analysis highlights the strengths and limitations of each pipeline component. On a skewed test diagram from a scan with slight rotation, the proposed pipeline achieved a device detection accuracy of 88.46% with no false positives and a line detection accuracy of 94.7%. Full article

A branch of the nucleotide excision repair (NER) pathway, transcription-coupled repair (TCR or TC-NER) specifically operates on the template DNA strand of actively transcribed genes. Initiated by stalling of elongating RNA polymerase complexes at damaged sites, TC-NER has historically been viewed as “accelerated repair”, arguably necessary for the maintenance of vital transcription function. Conversely, the conventional “global genome” (GG-NER) mechanism, operating throughout the genome, is usually regarded as a much slower process, even though it has long been found that differences in repair kinetics between transcribed DNA and the rest of the genome are not manifested for all structural types of DNA damage. Considering that damage detection is the rate-limiting step of overall repair reactions in most cases and that the mechanisms of the initial recognition of modified DNA structure are fundamentally different between TC-NER and GG-NER, it is suggestive to attribute the observed kinetic differences to different damage spectra recognized by the two pathways. This review summarizes current knowledge on the differential requirements of TC-NER and GG-NER towards specific damage types, based on their structural rather than spatial characteristics, and highlights some common features of DNA modifications repaired preferentially or exclusively by TC-NER, while evading other repair mechanisms. Full article

With the large-scale application and high-quality development demands of optical fiber cables, higher requirements have been placed on the corresponding measurement technologies. In recent years, optical fiber testing has played a crucial role in evaluating cable performance, as well as in the deployment, operation, maintenance, fault repair, and upgrade of optical networks. The Optical Time-Domain Reflectometer (OTDR) is a fiber fault diagnostic tool recommended by standards such as the International Telecommunication Union and the International Electrotechnical Commission. It is used to certify the performance of new fiber links and monitor the status of existing ones, detecting and locating fault events with advantages including simple operation, rapid response, and cost-effectiveness. First, this paper introduces the working principle and system architecture of OTDR, along with a brief discussion of its performance evaluation metrics. Next, a comprehensive review of improved OTDR technologies and systems is provided, categorizing different performance enhancement methods, including the enhanced measurement distance with simple structure and low cost in 2024, and the high spatial resolution measurement of optical fiber reflection events and non-reflection events in 2025. Finally, the development trends and future research directions of OTDR are outlined, aiming to achieve the development of low-cost, high-performance OTDR systems. Full article

The paper focuses on the experimental investigation of the impact of filtration and tribological parameters on the reliability, service life, and functional characteristics of gear mechanisms used in robotics. The primary objective was to analyze the importance of lubricant cleanliness in robotic transmission modules and to assess the effectiveness of filtration as a preventive and protective measure. As part of the research, a dedicated test rig was designed and developed. Based on the measurements and analyses performed, a significant correlation was confirmed between lubricant contamination levels and degradation phenomena in transmission modules. The study also highlights a sharp increase in contamination during the initial hours of operation, emphasizing the need for early intervention and continuous monitoring. The findings have strong practical potential and are highly relevant for manufacturers of robotic systems, maintenance service providers, and operators of automated production lines. The results contribute to increased system reliability and extended service life, reduced maintenance and repair costs, and improved environmental aspects of robotic system maintenance. Full article

In recent years, numerous regions worldwide have experienced devastating natural disasters, leading to significant structural damage to buildings and loss of human lives. The reconstruction process highlights the need for a reliable method to document and track the maintenance history of buildings. This paper introduces a novel approach for managing and monitoring restoring interventions using a secure and transparent digital framework. We will also present an application aimed at improving building structures with respect to earthquake resistance. The proposed system, referred as the “Building Ledger Dossier”, leverages a Digital Twin approach applied to blockchain to establish an immutable record of all structural interventions. The framework models buildings using OpenSees, while all maintenance, repair activities, and documents are registered as Non-Fungible Tokens on a blockchain network, ensuring timestamping, transparency, and accountability. A Decentralized Autonomous Organization oversees identity management and work validation, enhancing security and efficiency in building restoration efforts. This approach provides a scalable and globally applicable solution for improving both ante-disaster monitoring and post-disaster reconstruction, ensuring a comprehensive, verifiable history of structural interventions and fostering trust among stakeholders. The proposed method is also applicable to other types of processes that require the aforementioned properties for document monitoring, such as the life-cycle management of tax credits and operations in the financial or banking sectors. Full article

In the Karaganda coal basin, deteriorating geomechanical conditions have been observed, including seam disturbances, diminished strength of argillite–aleurolite strata, water ingress, and pronounced floor heave, all of which markedly increase the labor intensity of maintaining developmental headings. The maintenance and operation of these entries for a reference coal yield of 1000 t necessitate 72–75 man-shifts, of which 90–95% are expended on mitigating ground pressure effects and restoring support integrity. Conventional heave control measures—such as relief drifts, slotting, drainage, secondary blasting, and the application of concrete or rock–bolt systems—deliver either transient efficacy or incur prohibitive labor and material expenditures while lacking unified methodologies for predictive forecasting and support parameter design. This study therefore advocates for an integrated framework that synergizes geomechanical characterization, deformation prognosis, and the tailored selection of reinforcement schemes (incorporating both sidewall and floor-anchoring systems with directed preloading), calibrated to seam depth, geometry, and lithological properties. Employing deformation state assessments to optimize reinforcement layouts for floor stabilization in coal mine workings is projected to curtail repair volumes by 30–40% whilst significantly enhancing operational safety, efficiency, and the punctuality of face preparation. Full article

Non-conformities—deviations from established standards or procedures—can significantly impact product quality and process performance. Although various tools and methodologies exist, current research lacks an integrated, deferred, and corrective approach to non-conformance management that bridges day-to-day operations with systematic quality control. The proposed tool aims to address this gap by providing a practical framework that combines batch data processing using the “Daily Challenge” tool with structured problem solving and corrective strategies. It serves as a comprehensive decision-making tool for systematically managing deviations. The methodology begins with identifying non-conformities through data collection and direct observation, followed by focused reporting and active discussion during departmental meetings. Issues are then categorized based on their frequency, operational impact, and resource requirements to determine the appropriate resolution path—whether through immediate correction or detailed analysis using structured tools such as the “Daily Challenge” sheet. It integrates well-established methodologies such as 5M and PDCA into a structured, daily workflow for resolving non-conformities. Implemented solutions are evaluated for effectiveness with ongoing monitoring to ensure continuous improvement. A key feature of this system is the use of the “Daily Challenge” form, which facilitates documentation, accountability, and knowledge retention—helping to reduce the recurrence of similar situations. The case studies illustrate the methodology through two examples: a labeling issue involving the omission of quantity information on product labels due to operator oversight and the management of production downtime caused by equipment and sensor failures. Although a standard existed, the errors revealed the need for reinforced procedures. Corrective actions included revising procedures, retraining personnel, repairing and recalibrating equipment, enhancing maintenance protocols, and using visual documentation to enhance process understanding. The “Daily Challenge” tool provides a replicable framework for managing non-conformities across various industries, aligning operational practices with quality assurance goals. By integrating structured analysis, clear documentation, and corrective strategies, it fosters a culture of continuous improvement and compliance. Full article

Machining centers are complex systems that consist of multiple subsystems. When maintaining these subsystems, considering opportunistic maintenance can prevent frequent shutdowns during the machining process and reduce costs. This paper proposes an opportunistic maintenance strategy for machining centers. Firstly, the reliability of the machining center subsystem was modeled, which serves as the basis for determining when to repair a subsystem. In this process, an improved average rank method was employed, which considers the time correlation of subsystem failures and can achieve better model-fitting results. In the opportunistic maintenance strategy, imperfect maintenance is considered. Additionally, the strategy includes direct maintenance costs, downtime costs, failure risk costs, and penalty costs for incomplete utilization of subsystems. The opportunistic maintenance threshold helps determine whether other subsystems need to be repaired during this maintenance opportunity. The optimization objective is to minimize the total cost within the specified operating time. By modeling the reliability of subsystems using the failure data collected from five machining centers, the opportunistic maintenance strategy can reduce downtime by 10 times, preventive downtime by 29%, and cost by 7%. The results indicate that for machining centers or other complex systems, the opportunistic maintenance strategy mentioned in this article can lead to good results. Full article

This study focused on the monitoring of a bridge using the global navigation satellite system real-time kinematic (GNSS-RTK) sensor. An improved hybrid denoising method was developed to enhance the GNSS-RTK’s accuracy. The improved hybrid denoising method consists of the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), the detrended fluctuation analysis (DFA), and an improved wavelet threshold denoising method. The stability experiment demonstrated the superiority of the improved wavelet threshold denoising method in reducing the noise of the GNSS-RTK. A noisy simulation signal was created to assess the performance of the proposed method. Compared to the ICEEMDAN method and the CEEMDAN-WT method, the proposed method achieves lower RMSE and higher SNR. The signal obtained by the proposed method is similar to the original signal. Then, GNSS-RTK was used to monitor a bridge in maintenance and rehabilitation construction. The bridge monitoring experiment lasted for four hours. (Considering the space limitation of the article, only representative 600 s data is displayed in the paper.) The bridge is located in Tianjin, China. The original displacement ranges are −14.9~19.3 in the north–south direction; −26.9~24.7 in the east–west direction; and −46.7~52.3 in the vertical direction. The displacement ranges processed by the proposed method are −12.3~17.2 in the north–south direction; −24.6~24.1 in the east–west direction; and −46.7~51.1 in the vertical direction. The proposed method processed fewer displacements than the initial monitoring displacements. It indicates the proposed method reduces noise significantly when monitoring the bridge based on the GNSS-RTK sensor. The average sixth-order frequency from PSD is 1.0043 Hz. The difference between the PSD and FEA is only 0.99%. The sixth-order frequency from the PSD is similar to that from the FEA. The lower modes’ natural frequencies from the PSD are smaller than those from the FEA. It illustrates the fact that, during the repair process, the missing load-bearing rods made the bridge less stiff and strong. The smaller natural frequencies of the bridge, the complex construction environment, the diversity of workers’ operations, and some unforeseen circumstances occurring in the construction all bring risks to the safety of the bridge. We should pay more attention to the dynamic monitoring of the bridge during construction in order to understand the structural status in time to prevent accidents. Full article