Optimal Maintenance Cost Research Articles

Prognostics of State-dependent Fractional Degradation Processes with Stochastic Disturbance

Predicting the remaining useful life (RUL) of in-service commercial plants is closely linked with safety production and maintenance cost optimization. It is noteworthy that real-life degradation processes could be affected by their past states coupled with unknown disturbances. To make a comprehensive consideration of multisource dependencies and uncertainties, we develop a generalized non-stationary, nonlinear, and non-Markovian degradation model consisting of a Gaussian disturbed drift term and a sub-fractional Brownian motion (sub-FBM) based diffusion term. Both parts are state-dependent, and reflect two different types of memory effects. The main parameters and the approximate probability density function (PDF) of RUL can be solved on foundation of the Markovian transformation theories. A case study finally illustrates the effectiveness of the proposed scheme.

Метод пошуку рішень у динамічній моделі управління запасами за невизначеності

The article considers the method of finding solutions in the dynamic model of inventory management under uncertainty. An algorithm for formulating an optimal inventory management strategy is proposed using the developed method of determining the size of the optimal order lot and forming an optimal supply plan under conditions of stochastic demand. The developed solution is aimed at ensuring profit maximization in goods supply operations due to the optimization of inventory maintenance costs, an increase in inventory turnover ratio, a reduction of working capital maintenance costs, etc. The modelling was performed considering the mono-product strategy, the even distribution of sales in the cycle, and the instant supply of goods at the beginning of the cycle. The most common variables were listed as limitations of the model, which allows for a demonstration of the operation of the algorithm. The paper compares the simulation results of alternative methods of planning the inventory management process. The given results indicate the superiority of the proposed model.

Optimization of equal-cycle maintenance strategy considering imperfect preventive maintenance

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

Effect of Railway Track Segmentation Method on the Optimal Solution of Tamping Planning Problem

The safety and continuality of the railway network are guaranteed by carrying out a lot of maintenance interventions on the railway track. One of the most important of these actions is tamping, where railway infrastructure managers focus on optimizing tamping activities in ballasted tracks to reduce the maintenance cost. To this end, this article presents a mixed integer linear programming model of the Tamping Planning Problem (TPP) and investigates the effect of track segmentation method on the optimal solution by three scenarios. It uses an opportunistic maintenance technique to plan tamping actions. This technique clusters many tamping works through a time period to reduce the track possession cost as much as possible. CPLEX 12.6.3 is used in order to solve the TPP instances exactly. The results show that the total number of machine preparations increases by increasing the number of track segments. It is also found that the total costs increase by 6.1% and 9.4% during scenarios 2 and 3, respectively. Moreover, it is better to consider the whole railway track as a single segment (as in scenarios 1) that consists of a set of sections during the tamping planning in order to obtain the optimal maintenance cost. Doi: 10.28991/cej-2021-03091774 Full Text: PDF

Evaluating the Efficiency of Water Distribution Network Sectors Using the DEA-Weight Russell Directional Distance Model: The Case of the City of Valencia (Spain)

In many cities, sectorization projects of the drinking water distribution network have been implemented. This study provides a methodology to evaluate the efficiency of the sectors of a water distribution network by applying a data envelopment analysis weighted Russell directional distance (DEA-WRDD) model. This non-radial DEA model gives the overall efficiency of each unit of analysis, as well as each input, output, and undesirable output considered in the evaluation. The variables used in the analysis provide a multidisciplinary view: economic factors (covering costs), water quality parameters, and technical aspects. The empirical analysis was performed for the sectors of the water distribution network of the city of Valencia (Spain) for the year 2016. In this particular case, the results showed that approximately half of the sectors were efficient. The efficiency values of each variable indicate that the main challenges (faced by the water distribution company) were the optimization of maintenance costs and the reduction of leaks, both of which have an impact on the quality of the distributed water. So, the purpose of this article is to highlight the usefulness of efficiency analysis to help the decision making of managers of sectorized water distribution networks so that they can optimize the management.

Research on Civil Aircraft Direct Maintenance Cost Analysis and Optimization Based on Data Mining

Civil aircraft maintenance cost is an important indicator to measure the maintainability and economy of civil aircraft, and it accounts for a considerable proportion of aircraft operating costs. Data mining technology can unearth potentially high-value data from massive aircraft operating data. In this paper, aiming at the problem that there are very few actual aircraft maintenance data that can be effectively used in the development stage of civil aircraft, the research on the direct maintenance cost analysis and optimization method of civil aircraft based on data mining is carried out. The theoretical basis of direct maintenance cost analysis based on data mining is studied, the factors affecting the direct maintenance cost of civil aircraft are analyzed based on data mining, and the DMC analysis method is established. On the basis of the above research, the direct maintenance cost analysis model of civil aircraft was established and optimized to achieve the goal of reducing direct maintenance costs. It is of great significance for reducing aircraft life cycle costs and improving aircraft market competitiveness.

An integrated mathematical model of dynamic production and maintenance planning in pumped-storage hydroelectricity

PurposePumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity.Design/methodology/approachIn this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems.FindingsThe results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable.Originality/valueIn pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

Replacement and imperfect repair of deteriorating system: Study of a CBM policy and impact of repair efficiency

This paper studies a condition-based predictive maintenance policy in the presence of imperfect repairs for deteriorating systems. The effect of imperfect repairs is assumed to be random in the sense that a maintenance action reduces the systems degradation level by a random proportion. The associated distribution allows characterizing the repair efficiency. As an example, the beta distribution is considered. It allows defining a wide range of repair efficiencies. A maintenance policy with an aperiodic and predictive inspection planning is considered and a new decision criterion is introduced to evaluate the extent to which a repair would be beneficial. The aim is to find a proper balance between repair and replacement for preventive action which leads to optimal maintenance cost. With this consideration, the cost model is developed from regenerative and semi-regenerative properties. The expected cost is evaluated and the optimal policy is reached as a function of repair efficiency. Finally, a numerical study is drawn up to demonstrate the implementation and highlight the potential benefits of the proposed methods. A sensitivity analysis on critical parameters is also performed.

Soil bioengineering in northeastern Brazil: An Overview

This article presents an overview of the application of soil bioengineering techniques, also modeled as natural engineering, in the state of Sergipe, northeastern Brazil, showing the importance of integrating living and inert elements to protect river banks from erosion. The employed techniques are different, ranging from the characterization of susceptibility to erosion to the use of biotechniques, considering knowledge in the areas of agronomic engineering, forestry engineering, civil engineering, biology, pedology, geology, geomorphology and geotechnics. It is an approach that uses techniques and methodologies in a multidisciplinary way, seeking to maximize synergies (for example, natural engineering techniques to combine inert materials in ways that help plants to develop increasingly efficient systems). This approach also considers maintenance-cost optimization in the conduction of the works, using different materials, differing from traditional engineering, which uses predominantly inert materials. The research work carried out in different locations sought the availability of local materials such as rocks, geotextiles made from fibers from the native flora or even available on the market, in addition to the use of native species to recovery of the banks or slopes, according to the ecological conditions of the northeastern Brazil. Size and technological and ecological reach were also considered, in addition to different biotechnical aesthetic objectives adapted to different situations.

Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty

Maintenance usually plays a key role in controlling a multi-component production system within normal operations. Furthermore, the failure of components in the production system will also cause large economic losses for users due to the shutdown. Meanwhile, manufacturers of the production system will be confronted with the challenges of the warranty cost. Therefore, it is of great significance to optimize the maintenance strategy to reduce the downtime and warranty cost of the system. Opportunistic maintenance (OM) is a quite important solution to reduce the maintenance cost and improve the system performance. This paper studies the OM problem for multi-component systems with economic dependence under base warranty (BW). The irregular imperfect preventive maintenance (PM) is performed to reduce the failure rate of components at a certain PM reliability threshold. Moreover, the OM optimization model is developed to minimize the maintenance cost under the optimal OM reliability threshold of each component. A simulated annealing (SA) algorithm is proposed to determine the optimal maintenance cost of the system and the optimal OM threshold under BW. Finally, a numerical example of a belt conveyor drive device in a port is introduced to demonstrate the feasibility and advantages of the proposed model in maintenance cost optimization.

Maintenance model of aircraft structure based on three-stage degradation process

There are three-stage degradation processes for aircraft structures which are normal stage, crack stage, and after-repaired-stage respectively. However, there has been limited maintenance model for three-stage degradation data of aircraft structures. Therefore, this paper proposes a new approach for three-stage maintenance optimization management. Based on non-linear Wiener process and three-stage degradation analysis, a novel maintenance cost method is presented for aircraft structures and a novel four-level planning algorithm is developed to solve the maintenance cost problem. The first level planning aims at acquiring maximum usage time and the other three-level planning minimizes the maintenance cost of three stages respectively. The experimental data from China Eastern Airlines is adopted to validate and the experimental results show that the proposed method effectively expresses three-stage degradation characteristics to decrease the total maintenance cost; the proposed algorithm achieves a better optimal maintenance cost rate and saves runtime by 10%-20% than the state-of-the-art methods.

CIB - UTILITY BASED SYSTEMS FRAMEWORK FOR EXISTING RESIDENTIAL BUILDING

ABSTRACT 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 adaptive case study. To this end, the theoretical underpinnings of CIB were explained in the literature review, and the method of data analysis, selection of usability functions, and standard condition assessment scale were explained. The proposed model can be used to evaluate CIB utility theory systems and for life-cycle sustainability assessment (LCSA). The current findings revealed that the maintenance planning system and 5 G information must be improved because they are the key to Taiwan’s future development. Considering that the aim of cost-optimal maintenance and renovation planning is to not only optimise the service life-cycle costs of building components but also to maintain appropriate conditions and the performance of the respective components, the model used in this study prioritises performance over cost. Therefore, proposals are made for the future development of LCSA considering stakeholders of various projects for new construction by enhancing objectivity and accessibility.

Opportunistic Maintenance Policy for A Multi-Component System Subject To Random Failures

In this paper we study an opportunistic maintenance policy (OMP) for a multi-component system. The objective is to minimize the maintenance cost while guaranteeing a minimum level of reliability for the system and for each of its components. We suppose that each component is subject to random failures and at most one spare part of it should be kept in stock or ordering at any time. The lifetime of this system will be divided into several periods. At the beginning of each period we must determine the set of actions (among many others) that will achieve the objective mentioned above. The policy OMP is characterized by two parameters; the first one is the scheduled time for spare ordering and the second one is the period of realization of the maintenance action (if any). These parameters will be derived from the joint optimization of maintenance cost and the inventory cost for each component. Finally, we will give a numerical example to explain the proposed maintenance policy and the optimization procedure.

Dashboard proposition for health monitoring of production system in the automotive industry

Abstract In the context of industry 4.0, the predictive maintenance (PdM) approach plays an important role in the optimization of maintenance costs, as breakdowns and over-maintenance costs. Health supervision of production behaviors is one of the critical steps to implement PdM. To do this, specific Maintenance KPIs, called also Health Key Performance indicators (HKPI) must be identified. Furthermore, dealing with real data, finding the right HKPIs, and validating the final proposed solution by the industrial actors, are less seen in theoretical studies. In this paper, based on available historical and real-time data and information, some suitable HKPIs have been proposed, allowing to build the dashboards for monitoring the health state at machine and production system levels. Regarding the variety of real-time data to present in the dashboard, Principal Component Analysis (PCA) method has been applied, allowing to find the most appropriate features. At the production system level, HKPI aggregation and identification of decision levels are rarely studied. We propose also for each HKPI, a suitable decision-level, and an appropriated aggregation methodology. The proposed methodology has been applied to production equipment of the FPT Industrial Company and the results were appreciated by managers.

УМОВИ ТА ФАКТОРИ ЕФЕКТИВНОГО ВИКОРИСТАННЯ КОШТІВ МІСЦЕВИХ БЮДЖЕТІВ ПІД ЧАС РЕФОРМИ ФІНАНСОВОЇ ДЕЦЕНТРАЛІЗАЦІЇ

The implementation of the financial decentralization reform in Ukraine, which is the most important component of the general reform of local self-government in Ukraine for seven years, already has the first results and materials for research and conclusions. The state has proposed stages of reform and further activities of local governments. The government ensures the declared national expenditures delegated to local councils and recognizes the significant degree of their independence in planning, creating and implementing their budget plans. However, at the local level there are a number of problems that lead to inefficiency or inexpediency of costly financial activities. The article considers the most significant, effective and universal conditions and factors for improving the efficiency of spending financial resources of local budgets in the implementation of local government reform in Ukraine. The reasons for the need to implement the reform of financial decentralization and the problems it should solve are presented. Among the described bases of increase of efficiency of use of means – legislative, organizational, resource. Their definition was made possible by studying the results of community spending management during the first years of the reform. Most of them have an organizational character, i.e. one that is possible for the community to implement as a cohesive social body at the local level, have a low level of costs or opportunities for external financing or co-financing. Factors of its implementation, author’s comments and evaluation of efficiency are provided to each defined condition. The most important among the basics of effective spending of local budgets are: the availability of necessary and quality legislation, preparation and use of motivated staff of local governments, creation and implementation of social dialogue in the community, comprehensive control and analysis of public spending, determining responsibility for job responsibilities relevant employees, use of foreign experience and best financial practices of Ukrainian communities, use of energy-saving technologies, optimization of local government maintenance costs. Each of the presented bases has the described factors of their implementation which are described in article. The use of such factors makes it possible to use the available on a possible basis the effectiveness of the use of local funds, an important component of the community’s own resources during the reform of local self-government.

Scheduling optimal replacement policies for a stochastically deteriorating system subject to two types of shocks

This paper is aimed at scheduling optimal preventive replacement policies for a single unit system which is subject to stochastic deterioration and concurrently suffers from external shocks. Different from existing literature, two types of shocks are taken into account according to the effectiveness upon arrival of a random shock, in which Type Ⅰ shock is a non-fatal one increasing the damage magnitude on current degradation amount and Type Ⅱ shock is a fatal one resulting in system catastrophic failure immediately. System survival function is investigated numerically based on the degradation-threshold-shock (DTS) modelling framework, and subsequently, two categories of bivariate maintenance policies are scheduled from different perspectives. The optimal solutions for both policies are derived analytically, and the relative gain on the optimal average maintenance cost rate is incorporated to determine which policy is more profitable. An illustrative example is provided to validate the theoretical results.

Condition monitoring analysis of rolling element bearing based on frequency envelope

In recent years, fault diagnosis analysis techniques and various methods are developed over a period of time, in that condition monitoring of rotating machinery equipment is of great concern in industries. These fault detection method and technique development for machinery can have a direct impact in cost optimization of maintenance in terms of millions of dollars. And in this type of fault analysis, the rolling element bearings in rotating machinery, play the critical role, because it lead to total system failure or production loses in the company by wearing the parts associated in the total system. In this paper, the condition monitoring analysis of rolling element bearing fault detection and analysis is done. To deal with the envelope of frequency factor is developed, as these is one of the main factor to study the various failure stage of the rolling element bearing can done for the frequency spectrum obtained for the machine. And in this approach were the each faults can be set for the frequency factor envelope, and can be used as the reference standards for the dealing with the machine faults.

Comparative Analysis of Optimum Maintenance Cost for Water Boreholes in South-Eastern Nigeria

Aims: This study considered the optimal maintenance cost of water boreholes for a multiple pumping scenario in South-East Nigeria. The objective of the study was to determine the optimal maintenance cost of water boreholes for the Southeastern region of Nigeria.
 Place and Duration of Study: The data used in this study is secondary data obtained from selected community and commercial boreholes in the Abia State, Anambra State, Ebonyi State, Enugu State and Imo State.
 Methodology: The linear model and the quadratic model were used to determine the cost parameters for the optimization of the maintenance cost of the water boreholes.
 Results: The result of the study showed that the maintenance cost obtained for Anambra State is more adequate than the other states since it recorded a higher coefficient of determination value using the linear and quadratic model. Also, it was found the quadratic model was better than the linear model for the estimation of cost parameters used for determining the optimum maintenance cost of water boreholes in South-East Nigeria. The findings showed that the quadratic model recorded the best net savings for Abia, Anambra, and Enugu with the corresponding cost of ₦4,079,246.817, ₦5,198,716.141, and ₦4,767,680.392 respectively. It was found that the linear model recorded the best net savings for Ebonyi and Imo with the corresponding cost of ₦1,593,013.72 and ₦8,692,452.91 respectively. Hence, the quadratic models was identified as the best model for the estimation of cost parameters and enhance the performance of the optimal total operating cost of the water borehole model in South-East Nigeria.
 Conclusion: The study concludes by recommending the quadratic model for the estimation of cost parameters for the optimization of maintenance cost of water boreholes until further studies prove otherwise.

Component detection in piping and instrumentation diagrams of nuclear power plants based on neural networks

Piping and Instrumentation Diagrams (P&IDs) are the most commonly used engineering drawings to describe components and their relationships, and they are one of the most important inputs for data analysis in Nuclear Power Plants (NPP). In traditional analysis, the information related to the components is extracted manually from the P&IDs. This usually takes large amounts of effort and is error-prone. With the rapid development in the area of computer vision and deep learning, automatically detecting components and their relationships becomes possible. In this paper, we aim to use the latest neural network models to automatically extract information on components and their identifications, from the P&IDs in NPPs. We use a Faster Regional Convolutional Neural Networks (Faster RCNN) architecture called ResNet-50, to detect the components in the P&IDs. Compared to common object detection, object detection for P&IDs poses unique challenges to these methods. For example, the P&IDs symbols are much smaller than the background, and detecting such small objects remains a challenging task for modern neural networks. To address these challenges, we 1) propose several techniques for data augmentation that effectively solve the problem of training data shortage, and 2) propose a feature grouping strategy for detecting components with distinct features. Besides, we introduce a SegLink model for text detection, which can automatically extract components’ identifications from P&IDs. We also develop a method for building a data structure to reflect the relationships between components (e.g., to which pipe a component is connected, or what are the downstream or upstream components of one specific component) based on the extracted information. This data structure can be further used for plant safety analysis, and operation and maintenance cost optimization. Sensitivity analysis and comparison with other Convolutional Neural Networks (CNNs) are performed. The results of these analyses are also discussed in this paper.This analysis framework has been tested on the P&IDs from a commercial NPP. The Average Precision for components, which is used to measure the performance of the proposed method, is about 98%. The success rates of component-text mapping and component-pipe mapping are 270/275 and 319/319, respectively. It is worth noting that this framework is generic and can also be applied to P&IDs of non-nuclear industries.

Optimization method of fatigue maintenance for cable-beam anchorage zone of suspension bridge.

The cable-beam anchorage zone is the vital load-bearing component in suspension bridge. For maintenance of such structure, a method of probabilistic optimization was proposed by combining linear elastic fracture mechanics, structural reliability and life cycle cost analysis. In this method, the optimal maintenance time is obtained by determining the relative proportion between the costs under the condition that the structural reliability is higher than the minimum allowable reliability. While, the minimum total maintenance cost is obtained by determining the maintenance interval. Then, an example is presented to verify this method, with the following conclusions: the reliability index is inversely proportional to the failure probability, the change of maintenance cost and failure cost affects the optimal maintenance time, the optimal maintenance time will be ahead of time when consider the risk cost. And finally, when the maintenance time interval is determined, the optimal maintenance cost is affected by the maintenance probability and the failure probability.