Maintenance Performance Research Articles

Organising digital twin in the built environment: a systematic review and research directions on the missing links of use and user perspectives of digital twin in Architecture, Engineering and Construction (AEC) sector

There has been growing interest in the adoption of advanced digital technologies in the Architecture, Engineering and Construction (AEC) sector, as shown by the increasing number of review studies on the adoption of Digital Twin (DT) in the sector. While previous reviews on DT in the AEC sector have emphasised the technical opportunities and challenges, reviews that take a specific organisational and management focus on the use of DT are lacking. In this systematic review, we close this gap by analysing 102 papers from three main scientific databases (Google Scholar, Scopus and Web of Science), which emphasise organisational and management aspects of using DT in the AEC sector across the project and asset lifecycle phases. The findings indicate that, whereas there is still a stronger focus on finding optimisations for various performance concerns (e.g. project efficiency, health and safety and maintenance performance), there is increasing awareness and interest in using DT to encourage collaboration and (end-)user participation. Despite this recognition, our review also identified a number of critical knowledge gaps on the use and user perspectives of DT, which includes how powerful computational tools can be developed into user-friendly interfaces to reduce complexity and increase accessibility to all stakeholders in the decision-making process, and how participatory design frameworks can be combined with structured feedback systems and standardised data access protocols in order to stimulate communication, continuous improvement, and data-driven decision making.

Effects of Nutritional Status During Sexual Maturation and Resource Availability on the Resource Allocation of Females in Burying Beetles.

Resource availability should have consequences for life-history functions and trade-offs among them because it influences the amounts of resources allocated to different functions. Nutritional status during a key developmental window (sexual maturation) may also have an important impact on life-history functions and such trade-offs. However, less is known about whether and how they interact to influence the resource allocation of individuals. Here, we simultaneously manipulated female nutritional status during sexual maturation and resource availability during breeding in a burying beetle Nicrophorus vespilloides. We then monitored the main and interactive effects of these two factors on somatic maintenance and reproductive performance of burying beetle females. We found that variation in nutritional status during sexual maturation affects the resource allocation of burying beetle females only at the pre-hatching stage. Poor-fed females compensated for the initial differences in energy reserves by feeding from the carcass or engaged in terminal investment strategy and invested heavily at the post-hatching stage. Specifically, poor-fed females allocated more into somatic maintenance (gained more weight) and less into reproduction (provided less pre-hatching care) than well-fed females, whereas they provided a similar amount and duration of post-hatching care. In addition, burying beetles with different nutritional statuses vary in their response to resource availability. Poor-fed females allocated more into both somatic maintenance (gained more weight) and reproduction (provided more pre-hatching care) when bred on large versus small carcasses, whereas well-fed females tend to work near their maximum capacity and thus show no response to resource availability. Finally, our findings suggest that poor-fed females did not suffer a future cost in offspring performance. Meanwhile, a large carcass allowed females to produce more and heavier offspring. These findings enhance our understanding of how important nutritional status during a key developmental window and resource availability during breeding is for the expression of resource allocation.

Avaliação do Sistema Wood Frame em HIS plurifamiliar no Paraná

This article presents a study of multi-story buildings in the Wood Frame construction system, implemented in the state of Paraná. The objective is to evaluate the referred construction system from the point of view of the user in multifamily social interest housing. The study started from two methodological approaches: Literature review and the case study through post-occupancy evaluation – POE. The POE was applied in two buildings located in the Metropolitan Region of Curitiba, using the following tools: interviews with intervening agents and questionnaires applied to users, aiming to characterize the object, understand its operation and recognize the residents perception of quality and performance of their housing unit. The requirements were: luminous comfort, thermal comfort, acoustic comfort, maintenance and spatial analysis of the apartments. The results demonstrate that the performance in use of multifamily buildings in Wood Frame is satisfactory, although there are non-conformities recurring, reported by users, with regard to acoustic, thermal and maintenance performance.

Analysis of OPC Data Using Federated Learning: An Evaluation of Performance and Privacy

This study examines the benefits of applying federated learning (FL) technology to OPC (Operational Performance Control) systems within industrial automation and data analysis processes. FL enables each production facility to process its data locally while only transmitting model parameters to a central server, thereby preserving data privacy. This approach provides significant advantages in industrial environments, particularly concerning data privacy and communication costs. The study evaluates FL's potential to ensure data privacy, reduce communication costs, improve efficiency in training time, and deliver high performance in predictive maintenance and quality estimation. Model performance was analyzed using accuracy, F1 score, precision, and loss metrics; the results demonstrated that FL achieved a 90% accuracy rate, offering competitive performance compared to centralized modeling. In predictive maintenance and quality analysis specifically, FL achieved 85-88% accuracy while reducing network data load by 65%. These findings validate that FL provides a secure, cost-effective, and efficient solution for industrial data analysis processes by eliminating the need for centralized data collection. In conclusion, FL and OPC integration supports data privacy, cost savings, and communication efficiency in industrial processes. The study highlights that FL could become a prevalent technology in industrial data analysis, establishing a new standard particularly in digital manufacturing processes.

Optimum sugar syrup feeding intervals for Apis cerana Fab. during the winter dearth period in the sub-tropical area of Nepal

The study aimed to identify the optimal sugar syrup feeding interval for honeybee colonies during the winter dearth period in subtropical region of Nepal to ensure colony survival and maintenance. The focus was on evaluating sealed brood area, sealed honey area, egg-laying activity, and pollen collection. The experiment was conducted in an apiary located in Lamjung district of Nepal. Sugar syrup (1 water: 1 sugar) was fed to honeybee colonies at intervals of 7, 10, 15, and 20-days, along with a control group. Each treatment was replicated across four replications with five beehives in each replication, and data were collected weekly. Parameters such as the sealed brood area, honey storage, egg-laying rate, and pollen cells were measured by counting eggs, pollen cells, and assessing areas covered by sealed brood and honey. Colonies fed sugar syrup at 15-days intervals exhibited the best performance across all measured parameters, including the largest sealed brood area, highest honey reserves, maximum eggs laid by the queen bee, and the most pollen cells. These results indicate that feeding at 15-days intervals supports optimal colony health and activity during low-temperature winter conditions. Feeding sugar syrup at 15-days intervals is the most effective practice for maintaining colony health, ensuring optimal honey reserves, brood production, and pollen collection during the winter dearth period in subtropical areas of Nepal. This feeding strategy is recommended for improving colony survival, maintenance, and overall performance during challenging winter conditions in subtropical region of Nepal.

ARTIFICIAL INTELLIGENCE, ETHICAL CONSIDERATIONS, FUTURE TRENDS AND CHALLENGES

Artificial intelligence has somehow become the force that has transformed various sectors, including the military. Moreover, AI technology has revolutionized the military with its ability to rapidly process large amounts of data, make decisions, and analyze complex patterns. Analyzing the question of how it is used and what ethical norms exist in military structures is not an easy task, because artificial intelligence components are supported by the defense sector in many directions - autonomous weapons and vehicle systems, intelligent command and control systems, predictive maintenance performance, logistics and maintenance services. , cyber security, intelligence and surveillance, decision support systems, simulations and training, artificial intelligence applications and more. We have already discussed these issues in detail in the main part of the book, analyzed and discussed all the relevant issues related to the introduction, use and development of artificial intelligence technologies. The development of artificial intelligence has raised hopes of bringing great benefits, which can be reflected on the one hand in the Internet of Things (IoT), a huge set of capabilities, such as unmanned surveillance and targeting, health monitoring of soldiers, situational awareness and other critical applications. The trend is that decisions in future wars will require seconds, minutes, or even hours rather than days and weeks. This implies that the operational environment should be analyzed. By using artificial intelligence and machine learning, rapid information can be delivered to the frontline, which also means rapid decision-making. The Internet of Military Things is known to encompass many different tools, from battlefield sensors and weapon systems, to surveillance, intelligence, communications, wearables, and sensors on ships, aircraft, tanks, and the body. These tools collectively share an unprecedented amount of information in real-time during the war. The success of this issue depends on the ability to collect and store huge amounts of data from thousands of devices. However, a much more problematic issue is to quickly understand this information and deliver results to the fighters so that said information is useful and can be used. Ethical norms for the use of artificial intelligence differ from general ethical standards, artificial intelligence is more automated and scalable than most other processes, roles also include ethical risks - risk mitigation, legal risks reduction, human discrimination reduction, etc.

Market Performance and Customer Satisfaction Relation in Automotive Sales, Maintenance, and other Services

Market Performance and Customer Satisfaction Relation in Automotive Sales, Maintenance, and other Services

Estimation of Bubble Size and Gas Dispersion Property in Column Flotation

This study investigates bubble size measurements, bubble characteristics, and the relationship between key operating variables and gas dispersion properties in column flotation. As the frother concentration increased to 120 ppm, the bubble size distribution (BSD) transformed from bimodal to unimodal and achieved a minimum bubble size of 0.62 mm. The critical coalescence concentration (CCC) was identified as 120 ppm. Gas velocity and wash water velocity significantly influenced bubble size, with gas holdup peaking at 27% at 1.08 cm/s a gas velocity. The bubble-rising velocity increased as the bubble size increased, indicating that the bubble size and bubble-rising velocity were proportional. The bubble surface area flux decreased linearly with increasing bubble size and was significantly affected by the gas velocity. A strong correlation (R2 = 0.86) between measured and calculated bubble sizes was achieved, with an average size of 0.64 mm and an estimation error of ±13%. The study demonstrated that bubble size and distribution could be effectively controlled under specific operational conditions (Jg = 0.65–1.3 cm/s, JW = 0.13–0.52 cm/s, frother = 30–120 ppm). These findings highlight the importance of optimizing key variables to enhance column stability, regime maintenance, and flotation performance.

Modeling nuclear power plant piping reliability by coupling a human reliability analysis-based maintenance model with a physical degradation model

Reliability and availability analysis for repairable components, considering the underlying physical degradation and maintenance, is crucial in support of risk assessment and management. In nuclear power plants (NPPs), reactor coolant piping is a representative example of safety-critical repairable components that are subjected to long-term physical degradation interacting with maintenance activities. The existing methods for piping reliability analysis suffer from a limitation in their capability to analyze the time-dependent physics-maintenance interactions that could occur during the component lifetime and alter the underlying maintenance processes, for instance, an enhancement of maintenance programs based on condition monitoring data or an observed defect. To address this limitation, this paper develops a new piping reliability analysis methodology that couples a physics-of-failure (PoF) model with a maintenance performance analysis model. The contributions of this paper are two-fold: (i) developing a human reliability analysis (HRA)-based maintenance performance analysis model for NPP piping that can quantify maintenance outcomes under multiple types of maintenance programs, including time-based and condition-based preventive maintenance; and (ii) developing a computational methodology to couple the HRA-based maintenance performance analysis model with PoF models. The proposed physics-maintenance coupling methodology is applied to an NPP piping case study.

Organization of truck maintenance

Increased maintenance performance is able to contribute in growing the profitability of a transport company. Maintenance produces financial costs as well as losses in terms of availability. While the financial costs are a direct economic loss, availability losses causes indirectly an economic loss. Therefore, proper maintenance of trucks leads to high availability, thus increasing short-term profit of a transport company. This paper deals with the development production and technological tasks development of innovative system of vehicle operating in the Republic of Kazakhstan, due to the centralized specialized technical repair organizations or auto services in the context of the specific modifications of trucks together with the manufacturers. It presents a methodology for assessing the operational efficiency of contemporary commercial vehicles from different brands and manufacturers for which there isn’t yet a legal framework.

Operational Performance Evaluation Model for Food Processing Machinery Industry Chain

This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.

Technical strategy for reapplying coatings on solar tower receiver tubes using concentrated flux

Reapplying the coating is crucial to restore optimal receiver performance. However, the heat treatment must be conducted onsite since the receiver cannot be removed from the tower. This study explored effective strategies for maximizing the coating’s performance after reapplication. The impact of different aimpoint strategies on the receiver’s surface temperature was analyzed using the heliostat field and the three-dimensional receiver model. Experimental tests were conducted using a solar lamp to study temperature variation curves of coatings on different tube panels under various aiming strategies, and absorptance was then measured. The optimal recoating strategy was determined through a comprehensive analysis of the system’s power generation and its Levelized Cost of Energy across its entire lifecycle. The “image size priority” strategy led to significant temperature variations among tube panels and within each panel. In contrast, the “segmented target flux” strategy effectively minimizes temperature differences, ensuring that over 91.25 % of the receiver tube panel reached temperatures above 550 °C. Comparatively, under the “image size priority” and “segmented target flux” strategies, the coating’s absorptance at the molten salt inlet panel is lower by 1.84 % and 0.10 %, respectively, compared to the standard sample. The effectiveness of the “segmented target flux” strategy becomes more pronounced with shorter recoating intervals. The research contributes to enhancing the maintenance performance of the coating and the operational efficiency of the receiver.

Does Coproduction Enhance Quality of Public Infrastructure?

Coproduction is viewed in this paper as joint effort or cooperation between citizens and public infrastructure service providers. There is a paucity of studies on the impact of coproduction on public infrastructure quality or performance. Poor public infrastructure development poses a financial burden to many developing countries. In this paper, we use road maintenance as the example of public infrastructure. Using the Afro-barometer wave-6 dataset on Uganda, we develop the appropriate coproduction indexes as well as the road maintenance performance indexes from the survey data. Our results show that coproduction has significantly positive impacts on public road maintenance performance (RMP), which raises social welfare and economic development. Our results are robust to various model specifications and the conclusions remain valid after controlling for any potential endogenous influence or reverse causality problem that might arise. Our analysis points to the practical importance of cooperation between community and government in transport infrastructure provision such as road maintenance. It also provides practical implications for policy makers on how coproduction between community and government could be arranged.

Maintenance Tasks for 20 Kv Medium-Voltage Switchgear Based on Technical Judgment Experience and Manufacturer

A 20 kV medium-voltage switchgear is an important equipment in the electricity system that distributes electricity generated by the 20 kV electric power generator to electricity users. Calor Emag, Merlin Gerin, Alsthom, Fuji, AEG, Schneider, Meidensha, Goldstar, Modalek, Areva, and Siemens are among the companies that make products. This study describes a method for maintaining 20 kV medium-voltage switchgear, an essential equipment in the electricity system. In less technical terms, the failure rate is high at the beginning of an asset's life, which follows the curve of the bathtub. However, the failure rate quickly declines as we identify and discard defective components and eliminate early sources of potential failures, such as installation errors. This study introduces a novel approach by examining the relationship between maintenance tasks, which are based on technical judgment and experiences, and the maintenance tasks provided by the manufacturer for 20 kV medium voltage switchgear. The goal is to develop and deliver the most effective maintenance method for 20 kV medium voltage switchgear, to prevent malfunctions or even catastrophic explosions, while maintaining the lowest possible maintenance costs. Total use of labor over 2 years (24 months) for daily, monthly, 3 monthly, and 2 yearly is 3554-man hours (MH). It provides a comprehensive approach to preventing malfunctions and explosions, resulting in optimal maintenance costs and performance.

Maintenance, operational costs, and plant performance in three extensive green roof designs from Northwest México

Green roofs (GR) are nature-based solutions for climate change adaptation and mitigation in buildings and cities. However, few GR maintenance, installation, and challenge-solving guidelines are available for semiarid climates. We present how three case-study types of GR (urban gardens (UGR), native gardens (NGR), and wetland roofs (WR)) varied in installation costs, irrigation volumes, maintenance times, vegetation cover, survival, biomass and yield, in Ensenada, México, from 2022 to 2023. In UGR, nine edible species were cultivated to yield produce; in NGR, six native plants were planted, and four were grown in WR. UGR installation costs were 31 % and 21 % lower, but maintenance costs were four and 1.5 times higher than NGR and WR, respectively. UGR consumed 17 % more water annually than NGR and 42 % less than WR. Likewise, UGR demanded 94 and 92 % more annual maintenance time than NGR and WR. WR presented the highest survival, height, cover, and biomass values, followed by NGR (except for biomass) and UGR. Our results point to different GR solutions for distinct types of applications and users, demonstrating their versatility in design. All GR categories are suitable to reduce the ecological footprint of buildings; however, we emphasize that each GR design involves different economic, time, and challenge-solving commitments that should be considered before installation and operation.

تحسين جدول صيانة المعدات الدوارة باستخدام معيار التكلفة المتوقعة الكلية ومعيار تباين التكلفة

Inspection and maintenance of rotating equipment have gained credit in petrochemicals, refineries and oil and gas industries over the past decades due to the hazard failures resulting from overpressures and fluctuated temperatures surrounding the industrial zone. Therefore, any equipment operating under the harsh operational conditions should take the cost and time of inspection and maintenance into account. Maintenance of rotating equipment is an expensive event in terms of the cost and time, which are the driving forces to improve the maintenance performance. The paper aimed at optimizing the maintenance schedule for the grouped pumps in the refinery plant using the expected cost criterion and expected cost-variance criterion. This is characterized by the application of techniques to prolong equipment life, minimize downtimes, and enhance all aspects of reliability, availability and maintainability. The results showed that the cost and time of maintenance could optimize based on the rotating equipment, which could implement according to the preventive and corrective maintenance policy. The results analysis has revealed that applying optimization of maintenance schedule could help practitioners in decision-making to estimate the optimal cost and time, and reduce planning efforts in the future. Keywords: Pumps equipment, Maintenance policy, Cost and time of maintenance.

A dynamic framework for contractors to measure the performance of highway maintenance based on grey theory

Highway maintenance performance measurement is the key to implementing performance-based contracting (PBC). However, contractors have struggled with accurately understanding client intent and translating performance goals into measurable indicators. To make PBC successfully applied, this study proposes a dynamic performance measurement framework of highway routine maintenance based on grey theory. A performance indicator system is established based on the organizational structure of highway assets and the bill of quantities in the real world. In addition, a statistical analysis using the data about maintenance cost and highway condition score has been conducted to ascertain the weights and thresholds assigned to various indicators. As a result, the performance indicators, their corresponding weights, and thresholds can be flexibly adjusted to accommodate diverse periods and areas. Then, the grey theory has been employed to evaluate the comprehensive performance level of service within a region. This framework is experimented with using the data of three maintenance areas in Shaanxi Province, China: Qiaogouwan, Huaziping, and Ansai. At the end of the process, comparison and sensitivity analysis are conducted. The results demonstrate the model’s reasonability and robustness, providing valuable tools for contractors to assess the performance of highway maintenance in meeting client specifications.

Based on graph theory, design of distributed control system for multi-quadcopter UAVs

This paper addresses the formation control system for multi-quadcopter UAVs, proposing a control strategy based on finite-time stability theory. It designs position controllers with a dual power structure and attitude controllers combined with non-singular terminal sliding mode to achieve fast convergence and high-precision tracking. Through Lyapunov stability analysis, the paper proves the finite-time convergence of the control strategy. Simulation experiments validate the method's excellent performance in formation establishment, maintenance, and complex trajectory tracking, demonstrating rapid convergence, high precision, and strong disturbance rejection capabilities. This research provides theoretical and technical support for cooperative control of multi-quadcopters.

Examination of the Impact of Value Engineering Implementation on the Overall Maintenance Performance of Gravel Roads Maintenance Projects in Tanzania

Examination of the Impact of Value Engineering Implementation on the Overall Maintenance Performance of Gravel Roads Maintenance Projects in Tanzania

Predictors of Successful Maintenance Practices in Companies Using Fluid Power Systems: A Model-Agnostic Interpretation

The study identifies critical factors influencing companies’ operational and sustainability performance utilising fluid power systems. Firstly, the study performs Machine Learning (ML) modelling using variables extracted from survey instruments in the West Balkan region. The dataset comprises 115 companies (38.75% response rate). The survey data consist of 22 predictors, including meta-data and three target variables. The K-Nearest Neighbours algorithm offers the highest predictive accuracy compared to the other seven ML models, including Ridge Regression, Support Vector Regression, and ElasticNet Regression. Next, using a model-agnostic interpretation, we assess feature importance using mean dropout loss. After extracting the most essential features, we test hypotheses to understand individual variables’ local and global interpretation of maintenance performance metrics. The findings suggest that Failure Analysis Personnel, data analytics, and the usage of advanced technological solutions significantly impact the availability and sustainability of these systems.