Maintenance Methods Research Articles

Strategic maintenance planning in the digital era: a hybrid approach merging Reliability-Centered Maintenance with digitalization opportunities

In the age of digital transformation, maintenance operations are crucial for leveraging the potential of Industry 4.0 and 5.0. Yet, this domain remains significantly under-optimized in terms of strategic maintenance planning and enhancing asset performance. The advent of smart technologies offers a myriad of innovative avenues; however, harnessing these effectively requires systematic planning that incorporates these new, various and quite diversified, smart practices. Thus, this paper proposes a new methodological approach to maintenance planning, based on the Reliability-Centered Maintenance method, aimed at providing an operative tool for organizations to foster the evolution of their maintenance plans towards the paradigm of digitalization. This novel method enables the identification of hidden opportunities of improvement not identifiable through the use of the traditional approach through the proposal of an Opportunity Index, to use together with the Criticality Index in asset selection, and a Digitalization Score to use during Failure Mode, Effects, and Criticality Analysis. The proposed method is applied to transform the maintenance planning of a production line, thus identifying the opportunities of the approach and testing its feasibility.

Research on performance variations of different asphalt binders results from microwave heating during freeze-thaw cycles

Microwave heating (MH) as a sustainable pavement maintenance method can effectively repair the cracks caused by freeze-thaw (FT) damage. However, binders' properties may be weakened during this process then reduces the pavement life. For this purpose, this work aims to investigate the performance changes of neat binders (Nb) and high-viscous binders (Hb) during FT and MH. The physicochemical, rheological, and deformation properties are investigated after FT and MH. Results indicate that asphalt binders become harder and lead to an increase in carbonyl index (CI) and sulfoxide index (SI) after FT. MH has a limited damage level for binders especially for Hb, causing a slight increase in CI and SI, compared to binders after FT. Polymers play an important role in the viscoelastic responses of asphalt binders. Changes in viscoelastic properties of Nb mainly result from the binder damage of FT and MH, while viscoelastic changes of Hb are mainly due to the damage of polymers. This different damage mechanism causes Hb to show better resistance compared to Nb, which is reflected in modulus and phase angle. BBR tests indicate that MH can further deteriorate the damage of both binders, but Hb shows a lower performance decline compared to Nb, and it is recommended to conduct MH at the region with a minimum temperature above −12 °C. MSCR results reveal that FT and MH can improve the rutting resistance of Nb due to the hardening phenomenon after damage, and reduce the elastic stability of Hb due to the damage to polymers. In summary, Nb is sensitive to MH, its performance can be further damaged after MH. Hb has better resistance to MH, its properties do not further deteriorate, so Hb is more applicable to MH.

A MATLAB APP FOR BALANCING A CAPACITOR BANK IN THE DOUBLE STAR CONNECTION - NEUTRAL, NOT CONNECTED

This study presents a methodology for maintaining and rebalancing Double Star configuration capacitor banks, which are critical for managing power consumption peaks. As electricity demand is projected to rise by 21% by 2040, efficient maintenance methods are essential to ensure energy security. The paper introduces a novel approach to rebalance capacitor banks using a Matlab application, which simulates the unbalance current that may occur due to capacitive unit failures. Key aspects of capacitor banks, such as construction, connections, and protection methods, were reviewed to inform the methodology. Capacitor banks are used to control voltage, correct power factor, and reduce losses, but they can experience imbalances due to natural variances in capacitance or failures. The study developed a mathematical model to calculate the unbalance current and validated this model through simulations in LTspice software. The resulting rebalancing flowchart provides a step-by-step guide for technicians to follow during maintenance. The project achieved its goals, demonstrating through 24 simulations that the developed methodology and Matlab application could successfully predict unbalance currents with a negligible margin of error. The paper concludes that the methodology is ready for implementation, and each capacitor bank will require a tailored rebalancing application based on the presented calculations.

Update on the Obstetric Anesthesia Practice in Flanders/Belgium: A 10-year follow-up survey and review

Background: With 75% of women receiving neuraxial anesthesia for labor and cesarean section (CS) in Flanders, Belgium, obstetric anesthesia is an essential part of perinatal care. Despite advancements in obstetric anesthesia and guidelines being updated regularly, past surveys have shown great variability among hospitals. Objective: This investigation aims to observe current obstetric anesthesia practices, compare them with previous surveys, and assess adherence to guidelines among anesthesiologists. Methods: An online questionnaire-based survey, approved by the KU Leuven Ethics Committee, was conducted focusing on three main topics: analgesia during labor, anesthesia for CS, and postoperative analgesia after CS. The survey, consisting of 127 questions, was distributed via email to the heads of anesthesia departments in 57 Flemish hospitals providing obstetric anesthesia care. Responses were anonymously analyzed. Results: For labor analgesia initiation, a conventional epidural with administration of ropivacaine 0.2% (+- sufentanil) remains the most widespread used technique, although Combined-Spinal Epidural (CSE) has gained significant popularity. Patient-controlled epidural analgesia (PCEA) in combination with continuous epidural infusion (CEI) is the preferred maintenance method, however programmed-intermittent bolus (PIEB) has found its way into standard practice. CSs are mostly done by performing CSE or single shot spinal, using hyperbaric bupivacaine 0.5% with sufentanil. Spinal-induced hypotension is treated with a combination of left lateral tilt, fluid administration and vasopressor administration, usually as a bolus. Post-CS pain is mainly treated by a combination of oral/ parenteral analgesics and neuraxial analgesia (PCEA +- CEI), with only a minority choosing regional techniques such as wound infiltration, transverse abdominal plane blocks, quadratus lumborum blocks, etc. Conclusion: Compared to previous surveys, the Flemish anesthesiologists adhere well to the latest guidelines and gold standards in obstetric anesthesia, consistently modernizing their practices. Nevertheless, with the continual introduction of novel techniques and methods, it is imperative for practitioners to maintain efforts in pursuing ongoing innovation.

The application and development of drone vision technology in railway inspection industry

The inspection and preventive maintenance of railway facilities and their surrounding environments are critical tasks for ensuring the safety of railway operations. Inspection is the prerequisite for maintenance, and therefore, comprehensive inspection and maintenance methods can effectively reduce operational risks and ensure safe train operations. This paper summarizes the application of drone vision technology in railway inspections, analyzing the use of drones for the inspection of high-altitude equipment and environments, ground-level equipment and environments, and disaster prevention and control. It also reviews the recent applications of drone vision inspection technology in the railway industry, identifies the constraints, and offers a perspective on future developments.

Solution to the problem of setting up medical points and road maintenance in mountainous areas based on optimization

Assume there are 100 villages in a mountainous area. To improve the medical standards of the local residents, three medical points need to be established in several villages, and the roads need to be repaired. This paper modifies the Floyd algorithm to derive all the shortest paths between nodes. Based on the Prim algorithm, a minimum spanning tree model is constructed to find the road maintenance method with the lowest cost; a nested greedy algorithm is used to construct an optimization model under multiple variables, effectively solving the problem of setting up medical points and road maintenance in mountainous areas.

Data-driven predictive maintenance framework considering the multi-source information fusion and uncertainty in remaining useful life prediction

The existing equipment maintenance methods mainly separate the two related phases of prediction and predictive maintenance (PdM) by looking at remaining useful life (RUL) prediction without considering maintenance or optimizing maintenance schedules based on the given prediction information. To address this issue, we propose a framework based on a multi-stream attention fusion network with quantile regression model and deep reinforcement learning (DRL). In this novel framework, the multi-stream attention fusion block is used to comprehensively capture the operating status of industrial equipment and eliminate the extracted duplicate information. Quantile regression is employed to obtain the probabilistic RUL prediction results with uncertainty expression. We further formulate the PdM problem for DRL, where maintenance actions are triggered based on the estimates of the RUL distribution. To illustrate the superiority of our framework, we compare it with some state-of-the-art models using a public data and our private data. The experimental results indicate that our method exhibits high accuracy and stability in bearing RUL prediction and predictive replacement.

Design Maintenance System on Mixer Machine to Prevent the Breakdown Using Reliability Centered Maintenance

Equipment, machinery, and labor are fundamental assets of an organization. Therefore, companies must have an appropriate and scheduled maintenance system. However, many manufacturing companies neglect maintenance, leading to frequent machine breakdowns that can result in machine downtime and financial losses. This research aims to determine the machine maintenance interval and the types of actions to be taken. The method employed is Reliability Centered Maintenance with the Failure Mode and Effect Analysis approach to identify failure patterns in a system and formulate the best strategies for designing a maintenance system. The results indicate that the CS-20 Type B mixer is the most critical machine, which can significantly reduce the company's production output due to machine downtime during the repair process. Based on the Reliability Maintenance method, the maintenance interval for components with potential failures is 273.17 hours for the bearing component, experiencing breakdowns three times with the highest damage occurrence within one year.

Implementasi Metode Reliability Centered Maintenance untuk Menunjang Ketersediaan Suku Cadang Unit Prime Mover Truck Tipe 550 Horse Power

One of mining materials transport units is a 550 horse power prime mover truck. The prime mover truck functions as the main power source of trailer unit. This research was motivated by unexpected failures of 550 horsepower prime mover truck which operating on extreme mining environments, and unreachable component lifetime also delays of part supply, which contributed to increased downtime. The research purposes are to improve and develop the best maintenance system by identifying critical components, determining reliability values, determine maintenance intervals, and ensuring spare parts availability. The research was conducted using the Reliability Centered Maintenance (RCM) method, with independent variables are failure frequency data and failure duration data. The results identified five critical components, air piping and hose, fast fuel filler, radiator components, radiator hose, and wheel stud and nut. Maintenance intervals were determined when the reliability value approached 0.6, with the air piping and hose component reaching 1750 hours of operation or every 97 days, the fast fuel filler component reaching 1,250 hours or every 69 days, the radiator and reservoir tank component reaching 2250 hours or every 125 days, the radiator hose and line component reaching 2750 hours or every 152 days, and the wheel stud and nut component of 3000 hours or every 166 days.

Analisis Perawatan pada Unit Dump Truck FMX 440 Kapasitas 30 Ton dengan Metode Reliability Centered Maintenance (RCM)

One of the coal mining activities is to move coal from pit to rom using transport equipment, namely dump trucks. In the case study in the field, the dump truck used is FMX 440 with a capacity of 30 tonnes which operates for 18 hours/day. The obstacles or problems encountered during operations include damage and disruption to the dump truck unit system, which can interfere with the mining process and result in a reduction in the amount of coal production targeted by the landowner. Therefore, other methods are needed so that maintenance can be planned and carried out properly. This research aims to find critical components, and maintenance intervals on dump trucks. This research uses the reliability centreed maintenance (RCM) method. The results obtained are critical components, MTBF and MTTR values are cooling system 5,011.96 hours and 1.44 hours, transmission (T / M) system 14,446.24 hours and 2.75 hours, hydraulic oil hose and piping 22,326 hours and 10.54 hours, and air piping and hose 17,541.86 hours and 4.86 hours. From the calculation of the reliability value of critical components, the maintenance time interval for each component is obtained, namely the cooling system is carried out maintenance after 138 operating days, the transmission (T / M) system is carried out maintenance after 416 operating days, hyd. oil hose & piping is carried out maintenance after 638 operating days, and air piping & hose after 500 operating days.

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

Development of a Damage Assessment Method for the Efficient Maintenance of Aging Small- to Medium-Sized Reinforced Concrete Slab Bridge Decks

A Transformer Maintenance Interval Optimization Method Considering Imperfect Maintenance and Dynamic Maintenance Costs

As one of the most critical components of the power grid system, transformer maintenance strategy planning significantly influences the safe, economical, and sustainable operation of the power system. Periodic imperfect maintenance strategies have become a research focus in preventive maintenance strategies for large power equipment due to their ease of implementation and better alignment with engineering realities. However, power transformers are characterized by long lifespans, high reliability, and limited defect samples. Existing maintenance methods have not accounted for the dynamic changes in maintenance costs over a transformer’s operational lifetime. Therefore, we propose a maintenance interval optimization method that considers imperfect maintenance and dynamic maintenance costs. Utilizing defect and maintenance cost data from 400 220 KV oil-immersed transformers in northern China, we employed Bayesian estimation for the first time to address the distribution fitting of defect data under small sample conditions. Subsequently, we introduced imperfect maintenance improvement factors to influence the number of defects occurring in each maintenance cycle, resulting in more realistic maintenance cost estimations. Finally, we established an optimization model for transformer maintenance cycles, aiming to minimize maintenance costs throughout the transformer’s entire lifespan while maintaining reliability constraints. Taking a transformer’s strong oil circulation cooling system as an example, our method demonstrates that while meeting the reliability threshold recognized by the power grid company, the system’s maintenance cost can be reduced by 41.443% over the transformer’s entire life cycle. Through parameter analysis of the optimization model, we conclude that as the maintenance cycle increases, the factors dominating maintenance costs shift from corrective maintenance to preventive maintenance.

PRESCRIPTIVE MAINTENANCE SYNCHRONIZED TO THE CHARACTERISTICS OF INDUSTRY 5.0: A THEORETICAL DISCUSSION

This article aims to examine and understand the current scope of Prescriptive Maintenance integrated with the human-centric characteristics of Industry 5.0. Therefore, the main research question is the following: “In the view of the managers of the companies visited, located in the Southeast Region of Brazil, what are the main technical and administrative difficulties that companies encounter in successfully implementing proactive combinations on the factory floor, such as Prescriptive Maintenance integrated with the characteristics of Industry 5.0”?. The evolution of industrial processes in recent decades and the advent of Industry 4.0 integrated with human-centered characteristics have placed maintenance as one of the protagonists of industrial processes. In a scenario where automation and humans are gaining more and more space, the future of industries lies in Prescriptive Maintenance. To achieve the objective of the article, professional experiences from participation in congresses, seminars and technical visits to several factories located in the Southeast Region of Brazil are used. In data collection, we explored documentary observation and bibliographic research in the Science Direct and Web of Science databases. The study focuses on research areas related to maintenance integration, Industry 4.0 (Techno centric) and human-centric characteristics (Industry 5.0). The article brought important conclusions, as it addresses the impact and trends on the factory floor so that managers can develop competitiveness and productivity. The article highlights the role of maintenance methods in improving factory floor performance, emphasizing human knowledge and Prescriptive Maintenance practices to ensure operations within World Class standards.

Tool Condition Monitoring in the Milling Process Using Deep Learning and Reinforcement Learning

Tool condition monitoring (TCM) is crucial in the machining process to confirm product quality as well as process efficiency and minimize downtime. Traditional methods for TCM, while effective to a degree, often fall short in real-time adaptability and predictive accuracy. This research work aims to advance the state-of-the-art methods in predictive maintenance for TCM and improve tool performance and reliability during the milling process. The present work investigates the application of Deep Learning (DL) and Reinforcement Learning (RL) techniques to monitor tool conditions in milling operations. DL models, including Long Short-Term Memory (LSTM) networks, Feed Forward Neural Networks (FFNN), and RL models, including Q-learning and SARSA, are employed to classify tool conditions from the vibration sensor. The performance of the selected DL and RL algorithms is evaluated through performance metrics like confusion matrix, recall, precision, F1 score, and Receiver Operating Characteristics (ROC) curves. The results revealed that RL based on SARSA outperformed other algorithms. The overall classification accuracies for LSTM, FFNN, Q-learning, and SARSA were 94.85%, 98.16%, 98.50%, and 98.66%, respectively. In regard to predicting tool conditions accurately and thereby enhancing overall process efficiency, SARSA showed the best performance, followed by Q-learning, FFNN, and LSTM. This work contributes to the advancement of TCM systems, highlighting the potential of DL and RL techniques to revolutionize manufacturing processes in the era of Industry 5.0.

Analysis of Extrusion Blow Molding Machine Maintenance Planning with Reliability Centered Maintenance and IRRO Method

High demand for plastic products from year to year creates the need for plastic molding machines that can mass produce plastic products. An example of a plastic molding machine used at PT. X is a VK type extrusion blow molding (EBM) machine. Based on data from PT. X, the downtime of the VK type EBM machine reached 215.74 hours in 2021-2023. Therefore, improvements are needed in the machine maintenance management system. The purpose of this research is to determine the critical components, determine the reliability value of the critical components, and also establish a preventive maintenance schedule along with a cost budget plan for each critical component of the VK type extrusion blow molding machine at PT. X to increase the effectiveness of existing production activities. The method used is Reliability Centered Maintenance (RCM) with the application of RCA and FMEA methods to find critical components, then calculate the reliability of critical components as a reference for making preventive maintenance schedules. The data used are the failure data of VK type EBM machine in 2021-2023 period. The results of this study obtained 4 critical components with a reliability value of 0.5, namely the clamping unit at 210.3149 hours, the cutting unit at 79.9911 hours, the head unit at 677.5324 hours, and the hydraulic unit at 424.1550 hours. Maintenance planning is based on the IRRO (Inspection, Repair, Replace, Overhaul) method. The total maintenance cost for the period 2025 is Rp 35,093,903, which reduces the cost by 8.5% compared to 2023.

Types of stress and methods of stress reduction in cattle

Recently, stress has become the most urgent problem of modern animal husbandry. With the industrialization of agriculture, this problem is becoming more and more acute, as a result, livestock enterprises and farms suffer significant economic losses. Throughout its life, the animal is exposed to numerous stressors that have a completely different nature of occurrence, but invariably lead to the same changes in the body. The animal noticeably loses weight, weakens, its resistance to diseases decreases. A review of scientific sources on some types of stress loading on cattle: heat stress, transportation stress, pre-slaughter stress is given. According to many studies, the stress state of an animal depends on feeding and maintenance by 70-80% and only 20-30% on genetics. The body of farm animals is constantly affected by various environmental factors. These include production technology, method of maintenance, density of accommodation, size of groups, microclimate of premises, type and level of feeding, biological full-value of diets, methods of preparation and distribution of feed, quality of drinking water, veterinary and preventive and zootechnical measures (vaccination, sanitary treatment of animals, weighing, castration, etc.). When the above factors change, certain reactions occur in the animal body. The nature of stress can be different: mechanical, physical, chemical, biological, mental. Knowledge of the causes of stress, the patterns of its course, its consequences, outlined in the mentioned scientific sources, will allow rational use of the proposed ways to reduce the adverse effects of various stress factors on animals to preserve their health and high productivity.

Optimization algorithms for transmit waveform design in radar-centric dual-function radar-communication systems

We study the transmit waveform optimization problem in multiple-input-multiple-output (MIMO) dual-function radar-communication (DFRC) systems. A penalty-based formulation is adopted where engineering concerns on radar and communication are integrated in a weighted manner. We transform the original problem into an unconstrained formulation and propose a novel waveform synthesis algorithm via combination of multiple algorithm updates. The combination operation experimentally reaches a better objective value than without. We develop two combination strategies and invent a shrinkage-expansion line search method for monotonicity maintenance. Numerical experiments show that the proposed algorithm suffices to generate constant modulus waveforms which achieve radar and communication purposes.

Analisis Perawatan Mesin Bubut Baoji 1660A dengan Metode Reliability Centered Maintenance (RCM)

PT Swadaya Graha is a company that works in the field of construction, fabrication and steel manufacturing. One of the machines used in carrying out its operational activities is the Baoji 1660A lathe. The lathe often fails during the production process. This study aims to determine critical components, critical component reliability values, maintenance scheduling intervals and maintenance cost estimates of the Baoji 1660A lathe using the Reliability Centered Maintenance (RCM) method. The results of this study show that the electrical system with an RPN value of 240, v-belt with an RPN value of 168, and gearbox with an RPN value of 60 as critical components. The reliability value of the electrical system approaches 0.5 at a time interval of 640 hours or 80 working days, the reliability value of the v-belt approaches 0.5 at a time interval of 208 hours or 26 working days, and the reliability value of the gearbox approaches 0.5 at a time interval of 384 hours or 48 working days. From the scheduling interval, the estimated total maintenance cost in 2025 is IDR 7,019,092, in 2026 is IDR 3,615,386, in 2027 is IDR 4,187,484, in 2028 is IDR 4,276,752, and in 2029 is IDR 3,615,386.

Reliability analysis and preventive maintenance policy for consecutive k$k$‐out‐of‐n:F$n: F$ balanced system under failure criterion operating in shock environment

AbstractThis paper presents a consecutive ‐out‐of‐: balance system in a shock environment, where the state transition of component is induced by external shocks. If a predetermined threshold number of effective shocks are applied to component in a critical state, the component will fail. The state of the system is defined by the number of consecutive failing component groups in the system, which leads to system failure when a critical number of consecutive failing components is reached. To minimize maintenance costs, we propose a preventive maintenance method with an optimization model. We use finite Markov chain imbedding and Phase‐type distribution to calculate component group failure rates and associated probability functions in discrete and continuous time, respectively. The validity and accuracy of the model are confirmed by numerical examples and Monte Carlo simulations.

Detecting Potassium Rebound in a Prevalent Hemodialysis Population

Abstract Background One of the fundamental goals of hemo dialysis (HD) prescription is to maintain serum potassium (K) levels within a narrow normal range during both the intradialytic and interdialytic intervals. Considering the extraordinarily high rate of cardiovascular mortality in HD population, clinicians are obligated to explore whether factors related to dialytic K removal can be modified to improve clinical outcomes. Aim of the Work The aim of the study was to detect potassium rebound after HD sessions in patients on maintenance HD Patients and Methods This was a prospective cohort study that was held in Hemodialysis units in Nephrology department - Ain Shams University Hospital and Sheikh Zayed Specialized Hospital for 3 months. The study included 60 male and female ESRD patients on maintenance HD, in which prevalent HD patients on maintenance HD 3 times/week. Results We found that that there were significant positive correlations between K levels before the sessions, immediately after the sessions and after 6 hours of the sessions. While there was significant negative correlations between K levels immediately after HD sessions and Hb levels and urea levels. There was also a highly significant negative correlation between K levels before the sessions and time of session (in hours). While there were highly significant negative correlations between K levels immediately after the sessions, after 6 hours of sessions and time of session (in hours). There was non-significant negative correlations between all K levels (before HD sessions, immediately after the sessions and 6 hours after the sessions) and frequency of sessions (per week), with p value 0.388, 0.299 and 0.086 respectively. Also, it showed non-significant negative correlations between all K levels (before HD sessions, immediately after the sessions and 6 hours after the sessions) and frequency of sessions (per month), with p value 0.086, 0.089 and 0.083 respectively. Our results showed a significant positive relation between the number of K raising antihypertensive drugs used by the patients and K levels before HD sessions. Conclusion Patients with end-stage renal disease (ESRD) on maintenance dialysis have a high risk of developing hyperkalemia, generally defined as serum potassium (K+) concentrations of > 5.0 mmol/l, particularly those undergoing maintenance hemodialysis. Currently, the key approaches to the management of hyperkalemia in patients with ESRD are dialysis, dietary K+ restriction, and avoidance of medications that increase hyperkalemia risk. Management of these modifiable factors plays a crucial role in preventing hyperkalemia in patients undergoing dialysis. The availability of new oral K+-binders may potentially reduce the need for a highly restricted diet in patients with ESRD, and reduce the risk of potentially life-threatening hyperkalemia and the cardiovascular complications associated with rapid shifts in serum K+ concentrations that can occur with HD.