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This study proposes an approach for conducting comparative assessments between renovation and new construction through the use of CIB utility theory systems and applies the methodology to an adapti...

The safe and reliable operation of power grid equipment is the basis for ensuring the safe operation of the power system. At present, the traditional periodical maintenance has exposed the abuses such as deficient maintenance and excess maintenance. Based on a multiagent deep reinforcement learning decision-making optimization algorithm, a method for decision-making and optimization of power grid equipment maintenance plans is proposed. In this paper, an optimization model of power grid equipment maintenance plan that takes into account the reliability and economics of power grid operation is constructed with maintenance constraints and power grid safety constraints as its constraints. The deep distributed recurrent Q-networks multiagent deep reinforcement learning is adopted to solve the optimization model. The deep distributed recurrent Q-networks multiagent deep reinforcement learning uses the high-dimensional feature extraction capabilities of deep learning and decision-making capabilities of reinforcement learning to solve the multiobjective decision-making problem of power grid maintenance planning. Through case analysis, the comparative results show that the proposed algorithm has better optimization and decision-making ability, as well as lower maintenance cost. Accordingly, the algorithm can realize the optimal decision of power grid equipment maintenance plan. The expected value of power shortage and maintenance cost obtained by the proposed method is $71.75$ $MW·H$ and $496000$ $yuan$.

Reliability is widely used as a performance indicator of mining equipment to achieve a cost-effective maintenance plan. Reliability is a function of time as well as environmental and operational factors. Applying an adequate model by taking into account the mentioned factors is vital to ensure an accurate estimation of reliability characteristics. The aim of this study is to investigate the application of mixed frailty model to describe both observed and unobserved heterogeneity in reliability analysis of mining equipment. The capability of the model is assessed using field data from a fleet of dump trucks in an open-pit mine. The results indicate that the proposed model is superior to the traditional Cox model when data are heterogeneous. The results also show that the operator's skill and road conditions have a significant effect on the reliability of dump trucks.

The importance of facility management (FM) has gradually been recognized in the life cycle of a building. Both new and existing buildings require a more efficient approach and advanced technology to improve the efficiency of the FM. The study is aimed to enhance the facility repair process. Thus, the study presents a building information modeling (BIM)-based facility repair platform framework, which enables expedited reporting for repairs and a comprehensive listing of the status, location, and maintenance record facilities. To effectively facilitate the FM information transfer among stakeholders, firstly, the study presents a facility traceability coding structure for building facilities, the proposed platform framework. The proposed facility traceability information coding in QR code format can help general users and FM personnel identify and locate the specific or abnormal facility quickly. Secondly, the study demonstrates that how to apply the proposed code in QR code format in the BIM-based facility repair platform with a case test. The research findings showed that the proposed method enables FM personnel to significantly improve the efficiency of FM, which can help FM personnel make preliminary facility repair judgments and schedule maintenance plan to track the status of the facility repair which can help improve the efficiency of facility management and simplify the repair process.

One critical point to improve the economic and technical results of every industrial process lies on the fact of achieving a good optimization, and applying a smart maintenance plan. In this contex...

This paper proposes an availability-based maintenance scheduling for a vibrating-grate biomass boiler. The main objective is to minimise the maintenance programme cost while maintaining the system ...

International audience; The aging prognosis model of Proton Exchange Membrane Fuel Cell (PEMFC) can predict the aging state of PEMFC to develop an effective prognostic maintenance plan. This paper proposes an aging prognosis model of PEMFC in different operating conditions based on the Backpropagation (BP) neural network and evolutionary algorithm. The influence of PEMFC current, hydrogen pressure, temperature, and relative humidity on the aging of PEMFC can be considered by the proposed method. Firstly, the aging prognosis model of PEMFC is built by the BP neural network. Then, the evolutionary algorithm including Mind Evolutionary Algorithm (MEA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) is used to optimize the parameters of the established aging prognosis model of PEMFC. Finally, the accuracy of the proposed aging prognosis model is validated by 3 PEMFC aging experiments in different operating conditions. The results show that MEA, GA, and PSO can greatly improve the accuracy of the aging prognosis model of PEMFC. The MEA improves the accuracy by 10 times, while the computing time increases by 0.085s. The proposed MEA-BP that has a very short computing time can be applied to online applications.

Train scheduling and maintenance planning compete for the resources in a railway network. A commonly used way is dealing with maintenance planning first and then train scheduling, or vice versa. In this paper, we propose a joint optimization model for the two problems in a railway network with double-track, where the upstream and downstream trains are independent and a maintenance task on a section cannot be split or disrupted. In order to solve the model, a heuristic algorithm using Lagrangian relaxation is developed. Due to the large number of constraints, we use a dynamic constraint-generation technique in the iterations of the sub-gradient optimization procedure. We apply the model and algorithm to a practical problem in the Chinese railway network, in which some additional trains are inserted into a fixed existing timetable and the maintenance plan on the involved high-speed railway sections is adjusted. The computational results illustrate the effectiveness and efficiency of the proposed model and algorithm.

More and more equipment manufacturers are contracting with customers for maintenance planning (MP) of their equipment; this maintenance being either corrective, preventive or predictive. Due to the costs involved, customers are increasingly asking for a business case justifying the maintenance plan. This paper describes a study conducted with the MATISA Company, a track construction and renewal train manufacturer, and the business case for the equipment MP put forward to a customer. The concept developed consists of a method enabling the Company to provide a systematic explanation of the adopted maintenance strategy based on a joint cost-availability analysis regarding the ‘critical’ components. We begin by presenting MATISA practice, followed by a brief review of equipment maintenance principles. We then present the MATISA business case, and conclude with some remarks about the prospects for the method adopted and its generalizability from this experimental study.

The use of learning factories for education in maintenance concepts is limited, despite the important role maintenance plays in the effective operation of organizational assets. A training programme in a learning factory environment is presented where a combination of gamification, classroom training and learning factory applications was used to introduce students to the concepts of maintenance plan development, asset failure characteristics and the costs associated with maintenance decision-making. The programme included a practical task to develop a maintenance plan for different advanced manufacturing machines in a learning factory setting. The programme stretched over a four-day period and demonstrated how learning factories can be effectively utilized to teach management related concepts in an interdisciplinary team context, where participants had no, or very limited, previous exposure to these concepts.

Purpose The purpose of this paper is to propose and confer a strategic cost model as a concept for good decision making for highway asset treatment in the transport industry. Design/methodology/approach The paper is based on asset performance condition and treatment renewals using a five-point performance for developing prospective treatment strategies. The strategic cost model is presented in the similitude of picturesque and its outcomes via an exploratory data analysis. Findings The results articulate the best maintenance plan for the forthcoming and future years. The strategic cost model uses the combination of the current condition band, the sample area and likely treatment cost for proposing the optimal treatment solution based on consideration of desired treatment level. Practical implications The strategic cost model is suitable for outlining the asset performance condition, treatment renewals and analytical cost optimisation. The formulated analytical cost model and developed prospective strategies enable good decision making, long-term contract negotiations and whole life cost maintenance and management. Originality/value Embracing eminent performance condition from the research area of lifecycle planning and deterioration models of a physical asset, a prospective cost strategy for asset maintenance is proposed in the study. The resultant treatment strategies using the analytical approach portray the ability that enables the adaptation of expected outcomes.

In a processing facility, gasses and fluids are transported through the network of piping. Inspection and maintenance plan are required to ensure the integrity of the piping to avoid failures that can be catastrophic in nature. In some cases where the piping cannot be accessed externally such as underground piping and piping under insulation, internal inspection is the most practical solution. Due to their size which can be quite small, these piping can only be accessed internally using robotic crawlers. The robotic crawler can conduct visual as well as other type of NDT inspection. It has to be able to pass through various piping sections such as 90 and U bends as well as vertical section. This paper looks at the mechanical design of such crawlers and the issues and challenges associated with it. The design features for each robotic module are covered from the concept stage until the prototype stage. This is followed by the test and validation activities conducted on the prototype parts. The test results are presented and the areas for improvements for the next development stage are highlighted.

Governments face numerous challenges in sustaining road network conditions. This is attributed to road authorities’ shortages of financial and physical infrastructure. As a result, low-cost automated solutions are being pursued to solve these problems and provide people with appropriate road conditions. Several attempts have been made to improve these technologies and incorporate them into a Pavement Management System (PMS) but limited attempts are made for developing countries. This study aimed to design a low-cost pavement management system for flexible pavement maintenance. A detailed literature review has been carried out, followed by a qualitative assessment of the various indicators considered for PMS. The priority ranks of the PMS indicators were made using an Analytical Network Process (ANP) and each rank was validated by a sensitivity assessment test using the Super Decision-Making tool. This paper also provides the conceptual framework for the low-cost PMS, followed by a fishbone diagram of the indicators and sub-indicators. It is concluded that an emergency maintenance plan with an ANP weight of (0.41) is one of the most significant plans for a low-cost PMS, followed by a routine with an ANP weight of (0.39) and periodic maintenance plans with a (0.20) ANP weight. Moreover, the functional indicators with an ANP weight of (0.32) are the most significant indicators for a low-cost PMS, followed by structural (0.26), safety (0.24), and serviceability(0.18) indicators. This model will assist the road planners in making better decisions on pavement maintenance management plans. The model will suggest the pavement sections on a higher priority to be added in the maintenance plans, especially where the maintenance budget is limited.

Resumen: Se presenta el desarrollo de cinco fases basadas en el Design Thinking (Empatizar, Definir, Idear, Prototipar, Evaluar) con el propósito de diseñar una metodología integrando herramientas de Reliability Centered Maintenance (RCM), World Class Manufacturing (WCM) y Lean Manufacturing, la cual permita generar un plan de mantenimiento aplicable en procesos de trefilado de alambrón particularmente en una empresa mexicana del sector del acero. En las fases “Empatizar, Definir e Idear”, se identifican los problemas principales en procesos del sector del acero de empresas colombianas y una en México, planteando alternativas de solución basadas en las necesidades y realidades, considerando los Key Perfomance Indicators (KPI) esperados. Posteriormente se seleccionan herramientas acordes al problema y a las alternativas de solución planteadas. En las fases “Prototipar y Evaluar”, se integran las herramientas seleccionadas generando un plan de mantenimiento el cual es descrito y representado por un diagrama como evaluación de la metodología diseñada. Abstract: The development of five phases based on Design Thinking (Empathize, Define, Ideate, Prototype, Evaluate) is presented in order to design a methodology integrating Reliability Centered Maintenance (RCM), World Class Manufacturing (WCM) and Lean Manufacturing tools, which allows generating a maintenance plan applicable in wire drawing processes, particularly in a Mexican company in the steel sector. In the "Empathize, Define and Devise" phases, the main problems in processes of the steel sector of Colombian companies and one in Mexico are identified, proposing solution alternatives based on needs and realities, considering the expected Key Performance Indicators (KPI). Subsequently, tools are selected according to the problem and the alternative solutions proposed. In the "Prototype and Evaluate" phases, the selected tools are integrated, generating a maintenance plan which is described and represented by a diagram as an evaluation of the designed methodology.

Deposition of waxes, asphaltenes, scales or hydrates is one of the most challenging operational problems in the oil and gas industry, both during production and transportation. Direct inspection procedures, such as employing a closed-circuit television system, allow visual assessment of the blockage, yet discretely in time and, consequently, of low value for the purpose of ensuring production over time. Therefore, an indirect predictive maintenance method for systematic evaluation of the internal pipe section is herein developed, adding a much needed solution to the current body of knowledge. Using continuous field measurements, it is now possible to predict when pigging should be performed to avoid significant blockages. Moreover, evaluating the maintenance plan risk is another major achievement. Finally, the proposed methodology and model were applied to a real case-study yielding good results compared to the current scheduled maintenance approaches.

During the rainfall, different types of sediments are transported (organic and inorganic) and can end up decreasing the hydraulic efficiency of Pervious Concrete (PC). This phenomenon is known as clogging and occurs naturally in the PC due to its high area exposed to the weather. This study aims to identify and characterize the phenomenon of clogging in PC with natural aggregates and recycled aggregates, subjected to three types of sediment: two types of sand (Sand 1 and Sand 2, respectively) and a mixture of sand and clay (S + C). Besides, this research aims on proposing a maintenance plan to avoid loss of functionality of structures produced with PC. To fulfil these aims, the constant head permeability test will be adapted to evaluate the variation of permeability (k) during the clogging process. The results show that PC with recycled aggregates have the best hydraulic performance when compared with PC with natural aggregates. The results present values of 17.5 % and 19.6 % of porosity, and 6.2 mm/s and 10.0 mm/s of permeability for natural and recycled aggregates, respectively. Regarding clogging phenomenon, natural aggregate PC presents permeability reductions of 50 % (Sand 2), 60 % (S + C) and 70 %, (Sand 1) whereas in the case of recycled aggregate the maximum reduction was 30 % (S + C), 40 % (Sand 1) and 50 % (Sand 2). These results show the hydraulic advantage of implementing the use of recycled aggregates for PC production. On the other hand, the results show that a maintenance cycle of 5 years would make possible an increasing of the hydraulic life of PC independently of the type of aggregate used.

This paper presents a new variant of the selective maintenance problem (SMP) to jointly optimize the maintenance planning and resource allocation problems for multiple missions. The classical SMP deals with components and maintenance level selection with the aim of maximizing the system reliability given limited budget and break duration. Of the few papers dealing with the multimission SMP, none addresses the repairperson assignment problem. This work develops an SMP model for jointly optimizing maintenance and assignment decisions in a system running multiple missions. The resulting SMP addresses five joint decisions: selection of components to maintain, selection of maintenance levels performed on the selected components, identification of breaks where maintenance tasks are performed, repairpersons selection, and maintenance tasks assignment to selected repairpersons. The objective is to minimize the total maintenance and labour costs for a maintenance plan that guarantees a given reliability threshold. The fundamental constructs and the relevant parameters of this SMP are developed and discussed. Given its combinatorial complexity, a heuristic method based on the genetic algorithm is developed and implemented as a solution technique. Results from numerical experiments carried out demonstrate the validity and the benefits of the proposed approach, and show the robustness and efficiency of the developed heuristic.

Railway superstructure and the rolling stock form a complex mechanical system. Due to the interaction between the rolling stock and the rail, wears occur, both at the wheel profile, as on the rail. This wears generate interaction forces that accelerates the railway track deterioration. This phenomenon leads to expensive maintenance works both on rails as on rolling stock wheels. The purpose of the paper is to investigate the relationship between rail and rolling stock wheels wear, both of them being connected in the railway maintenance plan, rail safety and noise propagation. Wheel wear can be dangerous especially in low temperature season when, connected with the rail wear; it can produce rail cracks with dangerous effects on the traffic safety. It is essential to identify a crack from the initiation phase and the point where it becomes a dangerous point under traffic loads.

International audience; The scheduling of maintenance operations in railway is a major concern for both maintenance planners and train dispatchers since it requires the track to be blocked and the rail traffic to be disrupted. This paper provides a mathematical programming model aimed at adjusting the timetable of trains in a single track according to maintenance operations. The uncertainty of the maintenance activities might cause delays in the initial maintenance plan which is further overlapped with pre-determined train scheduling. This study addresses the uncertainty in maintenance activities through including buffer time to the modified scheduling. We also addressed the operational constraints such as speed limit due to maintenance operations in the adjusted scheduling. The result of the model provides railway planners with a modified timetable which includes both maintenance plan and train operations schedules

Executing a successful maintenance plan during the operation period is one of the essential parts to improve the performance of energy systems. The plan is conventionally regulated by periodic inspections and reactive repairs. In this study, we introduce the condition monitoring of major facilities in a central boiler room, steam boiler, by predictive maintenance techniques such as thermography and vibration analyses. We have diagnosed thermal and vibrational defects, and we used diagnosis results for quantitative estimation of the resource saving by courtesy of fault correction in the system. The probable troubleshooting program does not include only resource saving, but also the environmental, economic, technical, and social aspects. Such various impacts have been measured in the form of life cycle and sustainability assessments. The results revealed that the maintenance program with condition monitoring and probable troubleshooting is more sustainable than the periodic one. The new program can save 591312 kWh of gas and power consumption and 151795 Liter of water consumption in a boiler room in our case study. This is equivalent to the cost saving of 2330 US dollars in resource consumption and 35400 US dollars in maintenance cost. Moreover, the sustainability performance can be improved at least 28%. Such a decent performance improvement implies that the condition monitoring and the predictive maintenance can be a successful strategy in boiler rooms for better sustainability performance.

A methodology for maintenance planning is developed which helps in improving the reliability of the components and safety performance in process facilities. This methodology helps design an optimum safety maintenance investment plan by integrating the optimization techniques and a fuzzy dynamic risk-based method. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) is applied to deal with uncertain data. The proposed approach employs multi-experts’ knowledge which helps to optimize the maintenance investments. A separator system in an offshore process facility platform is selected as a case study to demonstrate the application of the proposed methodology. A practical example in the separator system is surveyed and potential failures and Basic Events (BEs) are identified. Finally, a risk-based maintenance plan is provided for future safety investment analysis. The results indicate that the developed methodology estimates the risk more accurately, which enhances the reliability of future process operations.

This paper presents a new algorithm for systematic coordinated maintenance of the elements of a transmission bay. The proposed method implements a knowledge-based Markov model to introduce a nonperiodic model for maintenance scheduling. The mode-based maintenance scheduling is implemented in this work, which is preferred to element-based one, due to the practical issues. To investigate the effects of maintenance on system's reliability, the network is modeled through its second-order equivalent cut set. Contrary to previous works, which consider each element separately, the presented approach tries to evaluate the optimum maintenance plan for entire elements of a bay by considering all elements of a bay together and coordinating the maintenance plan of each element. In this paper, various types of maintenance plan are considered, and the optimum plan for each element is evaluated using a genetic algorithm. Finally, the practicality of the proposed method is investigated using a typical transmission bay.

We develop a stochastic optimization framework for integrated condition-based maintenance and operations scheduling for a fleet of generators with explicit consideration of unexpected failures. Our approach is based on a model that uses condition-based failure scenarios derived from the remaining lifetime distributions of the generators, as well as a chance constraint to ensure a reliable maintenance plan. We derive a deterministic safe approximation of the difficult chance constraint. The large number of failure scenarios is handled by a combination of sample average approximation and an enhanced scenario decomposition algorithm in a distributed framework. We introduce a number of algorithmic improvements by exploiting the polyhedral structure of the problem, utilizing its time decomposability, and an analysis of the transmission line capacities. Finally, we present a case study demonstrating the significant cost savings and computational benefits of the proposed framework.

PurposeThis paper aims to identify the different system approach that is equipped with decision making processes. Presently, most maintenance organisations are still implementing conventional methods rather than fully integrated information and communication technology (ICT) to manage the information database on maintenance of residential building. The significant factor to select an ICT is much more advantageous than just a way to improve interfirm communication and cooperation on maintenance management processes and be able to perform the task needed without stressing the budget. ICT could be a pillar of fundamental importance for the implementation of an effective and efficient maintenance management on residential building and facility.Design/methodology/approachThis paper presents a review of recent publications on the topic regarding residential maintenance systems, which also takes into consideration the heritage structures, due to their same maintenance requirements and processes.FindingsThe findings reveal the need for ICT tools and techniques specific to the needs of reducing poor service delivery, inadequate financial support, poor maintenance plan and maintenance backlogs.Originality/valueThe paper concludes with a comprehensive research framework of ICT-based system as the basis for further progress in the development of the residential maintenance schemes of system.

The functional rural road network has a significant effect on the socio-economic growth of a nation. Newly constructed road pavements deteriorate with time, their regular maintenance will not only keep them functional but also increase their service life. Planning and scheduling of maintenance activities is an important part of any maintenance program for a large network of roads. The present study proposes a maintenance plan for low volume rural roads at network level as well as project level. In the first step of network level planning, the roads in the network are prioritized for pavement maintenance, depending primarily on their pavement condition and traffic volume. In the second step of project level planning, a suitable repair and maintenance technique is selected for each road based on the predominant pavement defects, traffic volume, and climatic conditions. ArcGIS was used to visualize the roads on a map and manage the data collected for each road. The maintenance planning was automated through a tool developed within ArcGIS. Verification of the methodology was done by applying it to a case study of 203 rural roads in the state of Himachal Pradesh in India. The results show that the pavement condition of a road (56.4%) is the most critical factor for prioritizing roads for maintenance. Pavement condition is followed by socio-economic facilities located along the road (26.2%), average daily traffic volume (11.7%), and type of connectivity provided by the road (5.7%). The outcome of the maintenance plan proposed in this study is the priority ranking along with the most suitable repair technique for each road in the network.

A methodology to implement a maintenance plan for buildings’ facades is presented. The theoretical proposal is based on relevant literature and was applied and adjusted in a survey of 30 buildings. It considers a three-step methodology: detailed inspection, post-inspection maintenance actions, and proactive maintenance planning. The proposal is based on systematized procedures, involving detailed information on the facade. A methodology to use multi-criteria to prioritize maintenance actions is suggested, namely environmental; extension; consequences; and safety requirements. Considering four types of maintenance operations, they are used to solve the main anomalies in facades (aesthetical, adhesion loss and fastening defects).

In the recent years, a series of studies which investigate the building retrofitting and maintenance plan optimization have been proposed. In these studies, items are categorized into several homogeneous groups to address the complexity. However, the grouping method involves the impacts of the groupings to the optimization results. This paper investigates the robustness of the maintenance plan performances with different groupings. A mathematical description is illustrated, including the definition of grouping, the grouping based control system formulation and the definition of the performance robustness. Taking advantage of the definitions and a sensitivity analysis approach, the performance robustness in practical maintenance plan optimization can be evaluated.

For many maintenance organizations, on-condition maintenance tasks are the most important source of spare part demand. An uneven distribution of maintenance tasks over time is an important cause for intermittency in spare parts demand, and this intermittency complicates spare parts inventory control severely. In an attempt to partially overcome these complications, we propose to use the maintenance plan, i.e. the planned maintenance tasks, as a source of advance demand information. We propose a simple forecasting mechanism to estimate the spare part demand distribution based on the maintenance plan, and develop a dynamic inventory control method based on these forecasts. The value of this approach is benchmarked against state-of-the art time series forecast methods, using data from two large maintenance organizations. We find that the proposed method can yield cost savings of 23 to 51% compared to the traditional methods.

This paper presents the results of the evaluation of the effectiveness that rolling stock maintenance (RSM) has on quality assurance (QA) at the largest rail, port and pipeline company in South Africa, as a case study conducted at its Koedoespoort depots and factories. Using a quantitative approach descriptive in nature, the researchers aimed to gain an insight into the research problem and to investigate the effectiveness RSM has on QA at freight rail company. Data was collected from a sample of 30 employees randomly selected at the engineering division. The evidence collected shows that the engineering division does not have a criterion to monitor the effectiveness of the current maintenance plan, the division does not have a maintenance system that is well understood by the artisans as well as technicians. The recommendations emphasized on a continuous training program on quality planning and implementation for the whole engineering division to ensure that the proposed maintenance strategy delivers as expected right the first time.

Current researches about maintenance scheduling problems of wind turbines only focus on small-sized instances. When the scale of the problem increases, the large number of variables and constraints is adverse for obtaining the optimal solution. This paper proposed a nonlinear integer programming model for large-scale maintenance scheduling of wind turbines. The performance of the model is less sensitive to the size of the scheduling problem than existing method. Genetic algorithm is used to identify the maintenance plan that maximizes the power production. Numerical examples are illustrated to validate the developed method.

Based on the characteristics of offshore wind farm and marine meteorology, combined with the design-build-operate life cycle process, this paper studied the definition and framework of smart offshore wind farm. The overall monitoring of offshore wind turbines, offshore substation and onshore control center is realized, with surveillance, operation control, comprehensive information analysis, intelligent alarm, management and other functions. In this way, the real-time monitoring of offshore substation, onshore control center, marine environment, vessels and offshore personnel is achieved to optimize the dispatch resources and construction maintenance plan. Finally, the smart offshore wind farm solution in this paper realized the life cycle management of offshore wind farms, which reduces construction and operation costs, increases generating capacity, extends equipment life and ensures personnel safety.

Corrosion mapping of fuel tank walls plays an important role in determining corrosion level for periodical maintenance plan or repairing plan, thus increasing life and maintaining stability in operating. Currently, the corrosion mapping based on ultrasonic testing using Phased Array technology is still being done manually, depending on the features of the used equipment, therefore the accuracy is timely and depends on the skill or inspector. This paper represents a new approach to corrosion mapping of fuel tanks from collected corrosion images using Phased Array technique with overlapping edges of 5 mm. The technique of identifying the edge of two adjacent images apply to merge them together to thank to the direction and dimensions of the scan plan. A program for corrosion mapping based on the above approach has been developed. Experimental results showed that, the corrosion mapping are built with high accuracy and performed quickly. Thereby, this allows rapid mapping with high accuracy without dependence of technician skills, thus increasing economic efficiency and safe inspection for the fuel tank.

This paper proposes an innovative smart maintenance (SM) model for scheduling proactive preventive maintenance of static synchronous compensators (STATCOMs). The approach is primarily useful for optimal operational planning of STATCOMs to maximize net benefit that comes from the difference between the power losses reduction savings and the cost of STATCOM’s acquisition and maintenance. The SM model incorporates: 1. Markov chains to describe STATCOM reliability with aging features; and 2. Type I restoration factor to describe the impact of maintenance over component’s virtual age. The optimization problem is solved using the Accelerated Quantum Particle Swarm Optimization (AQPSO), which involves three stages. The first stage determines the optimum number, size, and placement of the STATCOMs. The second stage set the effective maintenance plan. The last stage governs the best operation of the STATCOMs. The results show the efficacy of the proposed model, opening a new pathway to future applications in smart grids.

A statistical survey on the pathology and rehabilitation of linoleum and vinyl floorings is presented. It is based on the visual inspection of 101 vinyl and linoleum floorings, in six health infrastructures in Lisbon, Portugal, which enabled the validation of the classification/nomenclature previously proposed, as well as the corresponding correlation matrices. It was also possible to identify the most common types of anomalies, their probable causes, the most adequate in situ diagnosis methods, and the most useful repair techniques. Anomalies, diagnosis methods, and repair techniques files were also validated. The obtained data enabled anomalies to be related to their causes, in situ diagnosis methods, and respective repair techniques e.g., a high number of scratches/wear were detected associated with dragging of equipment. The conclusions drawn intend to raise awareness among the industry actors and minimize the development of anomalies and their causes at the design and application stages. Furthermore, the main sensitive issues of the cladding system during its service life were revealed, highlighting the importance of a correct maintenance plan to minimize the surface’s susceptibility to various degradation mechanisms.

The reasonable damage evaluation method for tunnel structure can be used to determine the overall safety state of the tunnel structure and can help to establish the maintenance plan of the ...

In this work, we establish that maintenance and inspection are a risk factor in helicopter accidents. Between 2005 and 2015, flawed maintenance and inspection were causal factors in 14% to 21% of helicopter accidents in the U.S. civil fleet. For these maintenance-related accidents, we examined the incubation time from when the maintenance error was committed to the time when it resulted in an accident. We found a significant clustering of maintenance accidents within a short number of flight-hours after maintenance was performed. Of these accidents, 31% of these accidents occurred within the first 10 flight-hours. This is reminiscent of infant mortality in reliability engineering, and we characterized it as maintenance error infant mortality. The last quartile of maintenance-related accidents occurred after 60 flight-hours following maintenance and inspection. We then examined the "physics of failures" underlying maintenance-related accidents and analyzed the prevalence of different types of maintenance errors in helicopter accidents. We found, for instance, that the improper or incomplete (re)assembly or installation of a part category accounted for the majority of maintenance errors with 57% of such cases, and within this category, the incorrect torquing of the B-nut and incomplete assembly of critical linkages were the most prevalent maintenance errors. We also found that within the failure to perform a required preventive maintenance and inspection task category, the majority of the maintenance programs were not executed in compliance with federal regulations, nor with the manufacturer maintenance plan. Maintenance-related accidents are particularly hurtful for the rotorcraft community, and they can be eliminated. This is a reachable objective when technical competence meets organizational proficiency and the collective will of all the stakeholders in this community. We conclude with a set of recommendations based on our findings, which borrow from the ideas underlying the defense-in-depth safety principle to address this disquieting problem.

Timely maintenance is crucial to ensure the long-term performance of asphalt pavements. Due to the large amount of greenhouse gases (GHG) emitted during construction, it is important to evaluate the environmental impacts of various maintenance technologies, so that the whole life impacts of asphalt pavements can be understood and reduced. This paper estimated the GHG emissions of 16 maintenance technologies in the four categories of surface seal or coating system, thin overlay system, hot recycling system and cold recycling system by using life cycle assessment (LCA), and identified the technologies and the combination of them that have the least GHG emissions. In order to compare the maintenance technologies on a level-playing basis, this study designed maintenance scenarios for the entire life cycle of the pavement, and established a system boundary where all maintenance scenarios are compared transparently for a defined functional unit. Results show that, among the preventive maintenance technologies, micro-surface and fog seal have the lowest GHG emissions. In order to meet the same performance requirements of highway pavement, cold recycling with extra overlay will generate more than twice GHG emissions that of hot recycling. Increasing the frequency of preventive maintenance, and reducing the occurrence of corrective maintenance can reduce GHGs emissions by 30%–45% in pavement life. Reasonably designed maintenance plan for the entire life cycle can significantly reduce the GHG emissions of asphalt pavements.

Railway rolling stock is one of the most expensive assets of railway operators. Efficient utilization of rolling stock is one of the most important objectives pursued in practice. This research focuses on the improvement in rolling stock rostering efficiency for high-speed rail system. According to the circulation schedule and long-term maintenance plan, the rostering planner decides the assignment between rolling stock and duties subject to a set of practical constraints. Owing to its complexity, this task remains a manual process at the Taiwan High Speed Rail Corporation. Experienced railway practitioners can generally create a good and feasible plan, but they cannot guarantee optimality of the solution considering only short-term process. In this research, we developed an exact optimization model and a heuristic method to automate this process and improve the efficiency of rolling stock utilization. Results from the case studies demonstrate that the efficiency of the rolling stock usage can be increased by $3\%\sim 4\%$ , and that the process time can be significantly reduced from hours to seconds.

Age replacement is one of the most used maintenance policies based on preventive action in order to prevent the failure of a system. Age replacement means that a system is replaced at failure or at a specified replacement age, whichever occurs first. In current age replacement policies, the replacement age is identified without consideration of the effects from operating conditions. However, the lifetime of a system may be affected by various operating conditions, such as the surrounding environment and the operators. In such cases, the replacement age of the system should differ for different situations. Thanks to the improvement of information communication technology, various information about the systems operating conditions can be obtained via the on-line monitoring. This research proposed an adaptive age replacement policy for systems under variable operating conditions using a cumulative exposure model. Based on the on-line information, we proposed a new time-scale instead of the age with consideration of operating conditions. Next, the new time-scale is used to determine the optimal replacement interval which will minimize the average maintenance cost per unit time (also known as cost rate). Some numerical examples are carried out in order to illustrate the proposed adaptive age replacement policy. The optimal age replacement policy considering the operating conditions reduces the total maintenance costs and enhances the effective maintenance plan for systems operating under various conditions.

The paper presents a risk management system on the basis of Living PSA models which are developed under a proposed generic GO-FLOW modeling method with a hierarchical and modular structure. The design of the risk management system is aiming at assisting plant personnel to manage maintenance plan and system configuration, and conduct system reliability monitoring, risk monitoring and risk management quickly and conveniently through graphical user interfaces without going deep into the details of building, updating and analyzing reliability and risk models. The performance of the proposed risk management system was tested on a full-scale simulator of PWR nuclear power plant and demonstrated that the fast solution time derived from utilization of hierarchical and modularized Living PSA models is strongly supportive for instantaneous risk assessment as well as for daily risk management at NPPs.

In the past decades, many shield tunnels have been constructed for use in important lifeline infrastructure such as roads, railways, water supply systems and sewers. A good performance of the tunnel requires appropriate maintenance associated with a substantial cost; therefore, a rational maintenance approach is required. Preventive maintenance has been previously applied in an efficient and effective manner. However, the evaluation of structural performance, as well as the choosing an appropriate maintenance management strategy, is still a challenge. This paper proposes a maintenance framework for the shield tunnel. Structural performance and life cycle cost are evaluated as the major indicators accounting for the major deterioration (e.g. steel corrosion, cracking, etc.). The structural performance-based strength cost for an expected service time is used as the criterion to select a rational maintenance plan. Furthermore, structural reliability analysis is performed to validate the proposed fram...

Technical installations can be placed on accessible flat roofs in hospitals. However, flat roofs also increase the risk of leaks and other drawbacks, which may alter the ordinary conditions of use of the building. This research aims to optimise the periodicity of flat roofs maintenance operations in hospitals to increase their useful life and guarantee their reliability. This research considered flat accessible roofs with three types of waterproofing membranes: bitumen, PVC and elastomeric. A sample of 12 hospitals in Extremadura (Spain) was processed using the Markov Chain. The results show that the degradation of flat roofs can be estimated and consequently the most appropriate maintenance plan considering reliability. The authors found that preventive maintenance contributed towards extending the lifetime of the roofs up to 8 years with reliability exceeding 63.21%. In this respect, the PVC membrane was found to suffer the least degradation. The average operating life of the membranes was calculated: 28 years for PVC, 24 years for elastomer and 21 years for bitumen. The time between replacements was also estimated, which means maintenance operations can be systematised to optimise costs and boost reliability.

The Italian way of thinking about maintenance is too often one-sided. Indeed, it is considered not so much as a useful practice to prevent the occurrence of a fault (ex ante), but as an intervention to solve it (ex post). Analyzing the legislation relating to the construction sector, it can be seen that it does not clearly define the responsibilities, timescales and methods in which maintenance interventions must be planned and carried out. For this reason, this practice is still very weak compared, for example, to the industrial sector, where it is an established practice. Currently, the complexity of reading the maintenance plans drawn up by designers and the considerable costs associated with maintenance operations discourage owners and managers from even carrying out preliminary inspection operations. This research aims to stimulate these stakeholders to carry out inspection operations regularly, highlighting their costs and benefits. In particular, working on a case study in Piedmont, the costs of visual inspections carried out in the traditional way are compared with those that would be incurred if unmanned aerial vehicles (UAVs) were used. Finally, the collateral benefits of inspections carried out with UAVs are highlighted.

This study presents an optimal lighting maintenance plan that takes into account lumen degradation failure. In lighting retrofit projects, retrofitted lights fail over time mainly owing to burnout and lumen degradation failures. These failures result in a reduced illumination level and lower project savings if proper maintenance is not performed. Previous studies developed lighting maintenance plans by modeling lamp population decay due to burnout failure. In this study, we present an optimal lighting maintenance plan based on lumen degradation failure. The lumen degradation failure is modeled based on the statistical properties of degradation rates. By using the Kaplan–Meier method, the formulated lumen degradation failure is used to model the surviving population. The surviving population model is used to design an optimal lighting maintenance plan, which maximizes energy savings and minimizes maintenance costs. The effectiveness of the formulated maintenance plan is demonstrated by an actual residential energy-efficient lighting retrofit project implemented in South Africa. Results show that the proposed maintenance plan is more cost-effective than full maintenance.

Since the hot metal pretreatment-steelmaking-continuous casting (PSCC) process has become the most common process in modern steel plants, the traditional steelmaking-continuous casting (SCC) scheduling is being extended and transferred to the more complex PSCC scheduling. In this paper, based on the existing studies for SCC scheduling, the maintenance plan and different accessibility relations between machines are considered in the PSCC scheduling to satisfy the practical production requirement in modern steel plants. A heuristic that contains a machine allocation procedure and a conflict eliminate procedure is developed first to obtain a good feasible schedule of this problem. Subsequently, by using the heuristic as a decoding algorithm, an adaptive genetic algorithm (AGA) featuring a novel adaptive evolutional strategy is presented to obtain a suboptimal solution of the PSCC scheduling problem. Experimental results based on instances generated from a realistic steel plant demonstrate that the AGA is effective for solving PSCC scheduling with maintenance plan and different accessibility relations.

International audience; The Remote Handling tasks scheduled during the ITER maintenance shutdown require transportation of in-vessel components and remote-handling tools from the Vacuum Vessel (VV) ports to the Hot Cell Building (HCB). These components and tools will be moved using the Cask and Plug Remote Handling System (CPRHS). During plasma operations, plasma facing components will be highly activated by neutrons and/or contaminated with tritium. After plasma operations, activated dust will be removed from the VV but some amounts will remain. Therefore, the CPRHS may be contaminated by residual activated dust due to the transportation of these components between the VV and the HCB. As the CPRHS is not shielded, residual activated dust may lead to a residual dose rate around the CPRHS. To assess the risk of external exposition in case of human intervention for maintenance purpose inside or close to the CPRHS, dose rate estimations were performed around and inside the CPRHS for several initial dust configurations with the normalized value of 1 g of residual activated dust. The results of this study constitute a dosimetric data base and may support ITER Organization in the definition of a decontamination level and maintenance plan.

This work develops a risk-based framework for a ship and structural design accounting for maintenance planning. The risk analysed here covers structural failure where, it is deemed as a failure when the structural capacity is less than the subjected loads, reducing the stipulated margin of safety. The risk in this context also includes hazards such as accidental spills, loss of cargo, ship and crew members during the operations stage. For structural failure, time profiles of performance, which will incorporate structural degradation in conjunction with ship hull strength to predict the expected behaviour in terms of structural integrity is analysed. The profiles are envisaged to be approximate as they are based on the limited data available during the early design stage. The risk-cantered maintenance methodology is applied for determining the maintenance plan of a ship hull structural system and permits the developed framework to be used in the early stage of design, accounting for different hazard scenarios, specific economic environment and degradation severity along the service life.

This paper addresses a maintenance plan optimization problem for building energy retrofitting with a novel differential evolution-based algorithm. The problem manifests substantial complexity due to the parallel optimization of the maintenance time scale, maintenance instants, and maintenance rates, with multiple objectives and time scales. The problem is formulated based on an impulsive and switched phenomenon, with objectives of maximizing the energy performances and economic indicators for the retrofitting project over a finite horizon. A multiscale differential evolution algorithm is accordingly proposed to be the numerical solver. The proposed algorithm is able to optimize the decision variables simultaneously, especially the maintenance time scale that can influence the number of other decision variables. Simulation results illustrate the effectiveness of the proposed approach.

As a power transmission device, gearbox is an indispensable component of the urban rail vehicle, and it is significant to determine the fault type of the gearbox and to provide the basis for the maintenance and maintenance plan of gearbox. In this paper, traditional VPMCD method is improved in the selection of the prediction variables and the parameter estimation, and based on the error between the estimated value and the actual value, the fault type of the gearbox can be accurately judged. The applicability of VPMCD is analyzed by an example, and compared with other methods, the superiority of the optimized VPMCD is verified.

The reliability of the power supply is an important index to evaluate the technology of distribution networks. The burn-in and failure of switches in distribution networks, the artificially maintenance plan and testing switches will reduce the reliability of the power supply of distribution networks. In this paper, we have proposed a method of schematically testing state of switches in distribution networks. We can check state of switches in distribution networks by means of the method to ensure that switches have a good state of remotely controlled and reduce artificially testing switches and planned outages. Finally we can efficiently exclude the trouble of the failure of switches and improve the reliability of the power supply of distribution networks.