Maintenance Interventions Research Articles

Digital twins-boosted intelligent maintenance of ageing bridge hangers exposed to coupled corrosion–fatigue deterioration

The corrosion–fatigue coupled deterioration of ageing steel bridge hangers presents significant structural challenges, demanding rigorous condition assessments and timely maintenance interventions. This paper introduces a framework of digital twins-boosted intelligent maintenance (DTIM) tailored for ageing hangers, integrating the prediction model, monitoring data and inspection results. The DTIM features a suite of algorithms adaptation and innovations, including dynamic Partially Observable Markov Decision Processes (POMDP), Asynchronous Advantage Actor Critic (A3C), and Bayesian Dynamic Linear Models (BDLM). The DTIM emphasises regular early-life repairs, strategic inspections, and timely replacements towards life-end, tailored to the condition of specific bridge hangers in the case study presented. By coordinating actions across hangers, the DTIM enables opportunistic maintenance to further optimise resource allocation. The output highlights digital twins in exploring the add-on value of monitoring and inspection for the proactive and sustainable maintenance of ageing infrastructure, promising enhanced structural integrity and serviceability in a cost-effective and well-informed manner.

Machine Learning Framework for Real-Time Pipeline Anomaly Detection and Maintenance Needs Forecast Using Random Forest and Prophet Model

This paper introduces an Intelligent Model for Real-Time Pipeline Monitoring and Maintenance Prediction to enhance infrastructure integrity and operational efficiency in Nigeria's oil and gas sector. Given the country's economic dependence on oil and gas revenue, efficient pipeline transportation is crucial. However, pipelines face challenges such as corrosion, mechanical failures, vandalism, and theft, leading to economic losses and environmental risks. Current monitoring systems are mainly reactive, lacking timely anomaly detection and predictive maintenance capabilities. To tackle these challenges, the study utilized sophisticated machine learning methods by combining the Random Forest classifier for real-time anomaly detection with the Prophet model for predictive maintenance forecasting. Datasets from Kaggle were used. The Random Forest classifier demonstrated robust performance with an accuracy of 93.48%, precision of 93.75%, recall of 96.77%, and an F1-score of 95.24%. The Prophet model provided accurate hourly forecasts of operational parameters, aiding proactive maintenance scheduling. Despite some errors encountered (RMSE: 21.48 and MAE: 18.17), the Mean Absolute Percentage Error (MAPE) of 14.87% indicates relatively minor discrepancies compared to actual values. In conclusion, the Intelligent Model shows significant advancements in pipeline monitoring and maintenance prediction by leveraging machine learning for early anomaly detection and timely maintenance interventions. This proactive approach aims to reduce downtime, prevent environmental damage, and optimize operational efficiency in Nigeria's oil and gas infrastructure. Future research could focus on enhancing system scalability across diverse terrains, employing advanced deep learning techniques such as Transformer Networks and Autoencoders for improved prediction accuracy, and exploring cybersecurity measures like blockchain integration to ensure data integrity and protect critical infrastructure from cyber threats.

Maintainability Assessment during the Design Phase: Integrating MTA and UNE 151001

The focus on maintenance actions in the early design phases has been a trend in recent years. The main sources of information during the design of the maintainability process include operator reports, maintainer experience, failure history, and manufacturer recommendations. During this process, an important aspect is related to the configuration of maintenance tasks and interventions, such as their main phases, activities, and durations. The allocation or estimation of maintainability involves identifying and/or estimating the mean time to repair (MTTR) for each component or system. The time of the maintenance tasks or the repair time are fundamental for companies, as the availability of equipment directly depends on this parameter. In this study, a new method for evaluating maintainability during the design phases is proposed. The method is based on the integration of the maintenance task analysis (MTA) principles and the UNE 151001 maintainability evaluation standard. A data structure is proposed that serves the application of the UNE151001 procedures, obtaining a data-based maintainability evaluation. As a validation procedure, an application of the proposed approach is presented using two overhead cranes. Comparisons and recommendations are made regarding the maintainability of both pieces of equipment. Finally, some managerial and engineering insights are presented.

A System-Level Reliability Growth Model for Efficient Inspection Planning of Offshore Wind Farms

Fatigue damage can lead to failures of structural systems. To reduce the failure risk and enhance the reliability of structural systems, inspection and maintenance interventions are required, and it is important to develop an efficient inspection strategy. This study, for the first time, develops a system-level reliability growth model to establish efficient inspection planning. System-level reliability growth is defined as an increase in the percentage of the system reliability index with and without inspection. The probabilistic S-N approach is used to obtain the reliability index without inspection. Moreover, advanced risk analysis and Bayesian inference techniques are used to obtain the reliability index with inspection. The optimal inspection planning is obtained by maximizing system-level reliability growth. This model is applied to an offshore wind farm. The results show that inspection efficiency can be improved by increasing the number of repair objects in response to a ‘detection’ inspection outcome, changing the inspection object for each inspection, and increasing the inspection quality. The maximum system-level reliability growth gained from one additional inspection decreases as the number of inspections increases. This study quantifies the inspection efficiency of offshore wind farms by explicit system-level reliability growth computation, offering valuable insights for promoting sustainable energy solutions.

An Individual vs Parent Supported Physical Activity Intervention in Adolescents with Intellectual Disabilities.

Moderate-to-vigorous physical activity (MVPA) is inadequate in adolescents with intellectual and developmental disabilities (IDD). This report describes the results of an 18-mo. clinical trial in adolescents with IDD which compared changes in accelerometer assessed daily MVPA, gross motor quotient and leg press strength between participants randomized to an exercise intervention delivered to adolescents only (AO) or to the adolescent and a parent (A + P). The 18-mo. trial included a 6-mo. active intervention, 6-mo. maintenance interventions, and a 6-mo. no-contact follow-up. Adolescents in both arms were asked to attend 40 min. remotely delivered group video exercise sessions (0-6 mos. =3 sessions·wk-1., 7-12 mos. =1 session·wk-1). In the A + P arm, one parent/guardian was asked to attend all group remote video exercise sessions and a monthly remotely delivered 30-min. educations/support session with their adolescent across the 12-mo. intervention. Adolescents (n = 116) with IDD (age ~ 16 yrs., 52% female) were randomized to the AO (n = 59) or A + P (n = 57) arms. Mixed modeling, controlling for baseline MVPA and season, indicated minimal but statistically significant changes in MVPA across 6 (p = 0.006), 12 (p < 0.001), and 18 mos. (p < 0.001). However, the change in MVPA in the two intervention arms did not differ significantly at any time point (all p > 0.05). Similarly, gross motor quotient and leg press strength improved significantly over time (p < 0.001) and these changes did not differ between intervention arms (all p > 0.05). Parental involvement had no impact on changes in daily MVPA, gross motor quotient or leg press strength in response to a remotely delivered exercise intervention in adolescents with IDD.

Implementation of a digital behavior change intervention (eCHANGE) for weight loss maintenance support: a service design and technology transfer approach.

Obesity is a chronic disease, and while weight loss is achievable, long-term weight loss maintenance is difficult and relapse common for people living with obesity. Aiming to meet the need for innovative approaches, digital behavior change interventions show promise in supporting health behavior change to maintain weight after initial weight loss. Implementation of such interventions should however be part of the design and development processes from project initiation to facilitate uptake and impact. Based on the development and implementation process of eCHANGE, an evidence-informed application-based self-management intervention for weight loss maintenance, this manuscript provides suggestions and guidance into; (1) How a service design approach can be used from initiation to implementation of digital interventions, and (2) How a technology transfer process can accelerate implementation of research-based innovation from idea to market.

Evaluation of Different Materials used in Prosthetic of Dental Implants: A Comparitive Study

ABSTRACT Background: Implant-supported prostheses have become a cornerstone of restorative dentistry, offering patients an effective solution for missing teeth. However, the choice of material for these prostheses can significantly impact their maintenance requirements and long-term success. Methods: Patient records of individuals who received implant-supported prostheses over a 2-year period were reviewed. Data on maintenance interventions, including adjustments, repairs, and replacements were collected and analyzed for metal alloys, ceramics, and composites. Results: Metal alloys exhibited slightly higher average numbers of adjustments compared to ceramics and composites. Ceramics required a higher mean number of repairs and replacements compared to other materials. Statistical analysis revealed significant differences in adjustment frequency between metal alloys and ceramics (P = 0.047), but no significant differences were observed for repairs or replacements. Conclusion: The outcomes imply that material choice plays a significant role in the maintenance requirements of implant dental prostheses. While metal alloys may require more frequent adjustments, ceramics and composites may necessitate more repairs and replacements over time. Clinicians should consider these factors when selecting materials for implant prostheses and develop tailored maintenance protocols to optimize treatment outcomes.

Comparison of Maintenance in Different Materials for Implant Dental Prostheses

ABSTRACT Context: In contemporary prosthodontics, implant-supported dental prostheses are frequently utilized to restore function and esthetics for individuals who are edentulous. The prosthetic material selection has a big impact on long-term performance and maintenance needs. Methods: A retrospective review of patient files from the dental implant clinic of a tertiary care facility was done. Included were patients who had dental prosthesis supported by implants between January 2018 and December 2022. Data were gathered and examined on the prosthesis material, follow-up visits, and maintenance interventions (adjustments, repairs, and replacements). Results: Materials for 50 prostheses made of porcelain, 45 prostheses made of acrylic, 35 prostheses made of metal, and 40 prostheses made of composite were assessed. When it came to modifications and repairs, porcelain prosthesis needed less work than acrylic prostheses. Composite prostheses required the least amount of maintenance overall, whereas metal prostheses indicated a considerable demand for maintenance. Conclusion: Superior durability is provided by porcelain, frequent repairs are needed for acrylic, structural strength is provided by metal, and composite material gives promising esthetics with low maintenance requirements. These results highlight how crucial it is to take material properties into account when choosing a prosthesis to maximize long-term results and patient happiness.

A Study on Materials Used and Longevity of Implant-Supported Prostheses

ABSTRACT Objective: This retrospective research was directed to investigate the longevity and maintenance requirements of implant-supported prostheses in subjects treated at a tertiary care center. Methods: Patient records of individuals who received implant-supported prostheses between January 2018 and December 2020 were retrospectively analyzed. Demographic information, implant type, prosthetic design, and follow-up data were collected. The primary outcomes assessed were prosthetic survival rates and the incidence of complications requiring maintenance interventions. Statistical analysis was performed to identify associations between demographic and clinical variables and the observed outcomes. Results: The research included 150 subjects with an average follow-up duration of 3 years. The overall survival rate of implant-supported prostheses was 90%, with 20% requiring maintenance interventions. Common complications included peri-implantitis (10%), prosthetic fracture (6%), and screw loosening (4%). Significant associations were found between smoking status and peri-implantitis (P &lt; 0.05) and between prosthetic design and prosthetic fracture (P &lt; 0.01). Conclusion: Implant-supported prostheses demonstrated a high overall longevity rate, with a subset of subjects requiring maintenance interventions due to complications. Peri-implantitis, prosthetic fracture, and screw loosening were the most prevalent complications, emphasizing the importance of tailored patient care and risk stratification.

Unraveling the optimal strategies for asphalt pavement longevity through preventive maintenance: A case study in South Korea

This study provides a comprehensive evaluation of three pavement surface treatments—Re-Ascon, Micro-surfacing, and Fog-seal—aimed at enhancing the longevity of asphalt concrete pavement. Utilizing visual inspection, bearing capacity measurements, and linear regression modeling, this study rigorously assesses the effectiveness of these strategies in real-world road environments. Notably, Re-Ascon emerges as the least damaged method in visual inspection, offering crucial insights into initial pavement conditions. Visual inspections consistently underscore Re-Ascon's outstanding performance in mitigating pavement distress, particularly in addressing cracking. Quantitative analysis using the Surface Curvature Index (SCI) from Falling Weight Deflectometer (FWD) measurements highlights Re-Ascon's superior elastic modulus (E1) and resistance to deflection compared to alternatives. Re-Ascon's 20 % SCI reduction compared to Fog-seal highlights its superior deflection resistance, supported by logarithmic elastic modulus values. Correlation analysis confirms Re-Ascon's resilience, maintaining low SCI even under higher loads and adverse weather conditions. Geographical variations and method-specific influences are revealed through PCI analysis, emphasizing the vital impact of preventive maintenance. The identified PCI threshold of 60 % guides timely interventions for major maintenance, while service life analysis forecasts approximately 3.0, 2.5, and 1.5 years for Micro-surfacing, Re-Ascon, and Fog-seal methods, respectively. In conclusion, this research furnishes critical insights into preventive maintenance methods, advocating a holistic assessment through visual, structural, and predictive perspectives, and emphasizing the need for ongoing research to advance sustainable strategies.

Fault Detection and Prediction for a Wood Chip Screw Conveyor

Equipment maintenance is a key aspect to maximize its availability. The present work focuses on data analysis of a screw conveyor of a biomass industry. The screw velocity and load were monitored and analysed, in order to detect and predict possible faults. A machine learning approach was used to detect anomalies, where different algorithms were tested with the data available, in order to train an anomaly classifier. The anomaly classifier was able to accurately identify most anomalies, based on historical data, temporal patterns and information of the maintenance interventions performed. The research carried out allowed to conclude that the Extra Trees Classifier algorithm achieved the best performance, among all algorithms tested, with 0.7974 F-score in the test set. The anomaly classifier has been shown to achieve remarkable accuracy in identifying anomalies. This research not only improves understanding of the performance of screw conveyors in biomass industries, but also highlights the practical utility of employing machine learning for proactive fault detection.

Association between whole-grain consumption, tryptophan metabolism and psychological distress: a secondary analysis of a randomised controlled trial.

This study aimed to investigate whether psychological distress, whole-grain consumption and tryptophan metabolism are associated with participants undergoing weight management intervention. Seventy-nine women and men (mean age 49·7 (sd 9·0) years; BMI 34·2(sd 2·5) kg/m2) participated in a 7-week weight-loss (WL) period and in a 24-week weight maintenance (WM) intervention period. Whole-grain consumption was measured using 4 d food diaries. Psychological distress was assessed with the General Health Questionnaire-12 (GHQ), and participants were divided into three GHQ groups based on the GHQ scores before WL. Tryptophan metabolites were determined from the participants' fasting plasma using liquid chromatography-MS. GHQ scores were not associated with the whole-grain consumption. A positive association was observed between the whole-grain consumption and indole propionic acid (IPA) during the WM (P = 0·033). Serotonin levels were higher after the WL in the lowest GHQ tertile (P = 0·033), while the level at the end of the WM was higher compared with other timepoints in the highest GHQ tertile (P = 0·015 and P = 0·001). This difference between groups was not statistically significant. Furthermore, levels of several tryptophan metabolites changed within the groups during the study. Tryptophan metabolism changed during the study in the whole study group, independently from the level of psychological distress. The association between whole-grain consumption and IPA is possibly explained by the effects of dietary fibre on gut microbiota. This broadens the understanding of the pathways behind the health benefits associated with the intake of whole grains.

Evaluation of the efficacy of intervention in the management of AD chronic disease based on the theory of "prevention of the recrudescence of disease".

Atopic dermatitis (AD) is a common inflammatory skin disease with a chronic course and a high recurrence. Based on the theory of "prevention and recovery after ulceration", the application value and significance of compound ginseng cicada decoction in the intervention of chronic disease management in patients with AD were retrospectively analyzed. Through clinical retrospective observation, 60 patients with spleen deficiency and moisture type AD admitted to the outpatient clinic of our hospital after January 2019 were analyzed. After comprehensive treatment until the patient's Investigator's Global Assessment (IGA) Scale score is lower than 2 points, the study group was divided into a research group and a control group, according to the actual clinical follow-up whether to take compound ginseng cicada soup. The control group carried out chronic disease management education, conventional emollient topical with no drug maintenance intervention, and the research group included clinical patients who were orally administered to compound ginseng cicada decoction for 1 month, observed for 3 months, and compared with the clinical recurrence (recurrence rate, time to first recurrence, severity at recurrence, degree of pruritus), and the quality of life. After 3 months, the relapse rate, recurrence severity, itching degree and quality of life impact scores of the study group were significantly lower than those of the control group, and there were no obvious adverse events. The combined application of compound ginseng cicada decoction in the management of chronic diseases in patients with atopic dermatitis has the positive significance of reducing AD recurrence, alleviating the severity of recurrence, and effectively improving the life quality of patients. This method has high safety and is worthy of wide application.

Choosing Health: acceptability and feasibility of a theory-based, online-delivered, tailored weight loss, and weight loss maintenance intervention.

Few weight loss and weight loss maintenance interventions are tailored to include factors demonstrated to predict the user's behavior. Establishing the feasibility and acceptability of such interventions is crucial. The aim of this study was to assess the acceptability and feasibility of a theory-based, tailored, online-delivered weight loss and weight loss maintenance intervention (Choosing Health). We conducted a mixed methods process evaluation of the Choosing Health tailored intervention, nested in a randomized controlled trial (N = 288) with an embedded N-of-1 study, investigating participants' and implementers' experiences related to intervention context, implementation, and mechanisms of impact. Measures included: (i) surveys, (ii) data-prompted interviews (DPIs) with study participants, (iii) semi-structured interviews with implementers, and (iv) intervention access and engagement data. Five themes described the acceptability of the intervention to participants: (i) monitoring behavior change and personal progress to better understand the weight management process, (ii) working collaboratively with the intervention implementers to achieve participants' goals, (iii) perceived benefits of non-judgmental and problem-solving tone of the intervention, (iv) changes in personal perception of the weight management process due to intervention tailoring, and (v) insufficient intervention content tailoring. The intervention delivery was feasible, however, emails and text messages differed in terms of accessibility and resources required to deliver the content. The use of Ecological Momentary Assessment as a technique to gather personal data for further tailoring was acceptable, and facilitated behavior change monitoring. Personalization of the intervention content above and beyond domain-specific issues, for example, by addressing participants' social roles may better match their needs. Support from the implementers and feedback on body composition changes may increase participants' engagement.

Tritium management in ITER test blanket systems port cell for maintenance operations

Four Test Blanket Systems (TBS) will be tested in the International Thermonuclear Experimental Reactor equatorial ports #16 and #18 to verify tritium breeding and heat extraction technology. A significant quantity of tritium would be produced in TBM, and partly released into the port cell from the pipework of TBS or other high-temperature components due to its strong mobility and high permeation. The port cell should be accessible during equipment maintenance and human intervention. This work built a multi-dimensional geometric model to characterize HTO transport in the port cell, absorption/desorption, and diffusion in walls and discussed the effect of paint thickness, ventilation rate, source term, and epoxy properties on detritiation efficiency. The results suggest that a 0.1–0.16 mm paint with the lowest HTO solubility is optimal from the compromise between quick cleanup and tritiated waste decommission. A higher ventilation rate could accelerate detritiation while minimizing the radioactive source by a tritium-resisting layer is the most direct method. The optimized design options for reducing the time required to reach 1 DAC in 12 h still need further discussion because of the delayed HTO source from epoxy paint and dead zone of the flow field.

Assistance of analytical ferrography in the interpretation of wear test results carried out with biolubricants

Analytical ferrography plays a crucial role in predictive maintenance, which is a proactive approach to asset and equipment management. This technique provides valuable information about the internal condition of machines and components, allowing early identification of potential problems and the scheduling of maintenance interventions before catastrophic failures occur. Ferrography allows you to identify worn particles, non-metallic inclusions and other indicators of wear on components. By analyzing samples of lubricating oil or hydraulic fluid, analytical ferrography can offer insights into the health of internal components such as gears, bearings and other critical elements. Changes in particle concentration and composition may indicate abnormal wear. This work involves the use of analytical ferrography to interpret wear results carried out with two vegetable lubricants with additives, compared to a mineral lubricant, also with additives. To assist in the interpretation of the results, the open source software Image J and a small program developed in Python were used. It was found that it is possible to use these two tools to aid the interpretation of ferrograms.

Modelling Wear Phenomena Specific to Mixer Blades in Concrete Production Plants

In the cement concrete manufacturing industry, mixers are critical pieces of equipment that play an essential role. Mixers ensure, by mechanically mixing the materials that make up the concrete, the homogeneity of the mixture. Since the active elements of the mixer in the concrete industry—the mixing blades—come into permanent contact with the mineral aggregates in the mixture formed by water and cement, they are permanently subjected to a strong abrasive–erosive wear process. The authors of this article were concerned with the establishment of tribological models for studying the wear of mixing blades, in order to identify the influence of their constructive parameters on the wear intensity. A complex model (Kraghelsky–Nepomnyashchi model) was adopted for the study. The modeling results revealed that the wear intensity decreases with an increasing blade angle of attack and increases linearly with increasing speed, as well as with an increasing friction coefficient. The modeling results confirm that the wear intensity is lowest when the mixing blade is inclined at a 60° angle, while the highest value is recorded for 30°. By identifying the angle at which the greatest wear of blades occurs, interventions can be made in the design of a more durable mixer (with the optimal installation angle of the mixer blades), thus requiring fewer corrective maintenance interventions. Based on these findings, we conclude that the complex model used in the experiment can provide a convenient and efficient tool for the study of erosive–abrasive phenomena.

Technological innovations and optimized work methods in subsea maintenance and production

Subsea maintenance and production represent critical aspects of offshore operations, vital for sustaining energy production and ensuring operational efficiency. However, these endeavors face numerous challenges, including the complexities of deepwater environments, harsh weather conditions, and the high costs associated with traditional maintenance methods. To address these challenges, this paper explores the integration of technological innovations and optimized work methods in subsea operations. Technological innovations play a pivotal role in revolutionizing subsea maintenance and production. Remote monitoring and control systems enable real-time data collection and decision-making, enhancing operational visibility and efficiency. Autonomous underwater vehicles (AUVs) offer the capability to conduct inspections and repairs in remote and hazardous environments, reducing human intervention and associated risks. Robotics and automation further streamline maintenance tasks, improving accuracy and reducing downtime. Advanced materials and coatings enhance equipment durability and corrosion resistance, prolonging asset lifecycles and reducing maintenance requirements. In parallel, optimized work methods offer strategic approaches to enhance subsea operations' effectiveness. Predictive maintenance strategies leverage data analytics and machine learning to anticipate equipment failures, enabling proactive interventions and minimizing downtime. Condition-based monitoring facilitates real-time assessment of asset health, enabling timely maintenance interventions and cost savings. Integrated asset management systems provide holistic insights into asset performance and facilitate informed decision-making. Lean operations and continuous improvement methodologies further optimize workflows, driving operational excellence and cost efficiency. Through case studies and industry examples, this paper highlights the successful implementation of technological innovations and optimized work methods in subsea maintenance and production. Furthermore, it explores future trends, regulatory considerations, and the importance of industry collaborations in shaping the future of subsea operations. Ultimately, the integration of these approaches offers a pathway towards enhanced operational efficiency, reduced costs, and sustainable subsea operations. Keywords: Technological Innovations, Optimized Work Methods, Subsea Maintenance and Production.

I’m from the Government, and I’m Here to Help: Public Perceptions of Coercive State Power

Under what conditions does the US public support the domestic use of different institutions of coercive state power? We theorize how the type of situation, the type of actor, the mission, and the type of intervention influence public support for such missions. We use a preregistered conjoint survey experiment to test our hypotheses and find that participants (i) are less supportive of interventions in response to protests than to natural disasters or terrorism, (ii) generally prefer the police or the National Guard to the military, (iii) mistrust order maintenance interventions, and (iv) prefer intervening actors be unarmed. Preferences (ii)–(iv) are strongly conditioned on the type of event. We also find that Republicans are more accepting of military actors, order maintenance interventions, armed interventions, and policing responses to protests. We note implications for public trust in the military, the militarization of policing, and the domestic use of federal forces.

Detection of Fault in Solar Panel Using Thermal Image Processing

This paper explores the practical application of thermal cameras mounted on drones for thermal image processing in solar panel maintenance, with an emphasis on hotspot fault detection. Traditional manual inspection methods for solar panels are often time-consuming and labour-intensive, prompting the exploration of more efficient alternatives. By leveraging the capabilities of drones equipped with thermal cameras, high-resolution images and videos of solar panels can be captured swiftly and effectively. Advanced thermal image processing techniques are then employed to analyse these visuals, with a particular focus on identifying hotspot faults. The study introduces novel methodologies aimed at enhancing the accuracy and speed of anomaly detection in thermal imagery, thereby enabling proactive maintenance interventions. Real-time inspection capabilities integrated into the drone-based system provide immediate feedback to maintenance personnel, facilitating prompt decision-making and action. Through the adoption of this approach, solar panel maintenance operations are streamlined, leading to improved efficiency and cost-effectiveness. Ultimately, the implementation of drone-based thermal imaging solutions contributes to the sustainability and longevity of solar energy systems. Key Words: thermal image processing, solar panel, faults in solar panel, drones, hotspot, fault detection.