Relevant bibliographies by topics / Simulation based preventive maintenance optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Simulation based preventive maintenance optimization'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Simulation based preventive maintenance optimization.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Simulation based preventive maintenance optimization"

1

Ge, En Shun, Qing Min Li, and Ao Lin Huang. "Optimization of Condition-Based Maintenance Policy for Deteriorating System Based on Monte-Carlo Simulation." Advanced Materials Research 544 (June 2012): 44–48. http://dx.doi.org/10.4028/www.scientific.net/amr.544.44.

Full text
Abstract:
Condition-based Maintenance (CBM) can not only efficiently improve the performance of deteriorating system but also guarantee the system operation safety. This paper assumes that the system state is periodically inspected, and a preventive maintenance is performed if the degradation level exceeds a threshold. The effect of maintenance is imperfect, which means that maintenance can restore the system state to somewhere between as good as new and as bad as old. The algorithm is presented to get the solution of long run cost based on Monte-Carlo simulation, and the joint optimization of inspection rate, the threshold value and the number of preventive maintenance activities is investigated for the minimization of long run cost rate. A case study is given to show the procedure of the maintenance model and simulation. Therefore, the correctness and rationality of the model are proved.
APA, Harvard, Vancouver, ISO, and other styles
2

Wang, Keren, and Dragan Djurdjanovic. "Joint Optimization of Preventive Maintenance, Spare Parts Inventory and Transportation Options for Systems of Geographically Distributed Assets." Machines 6, no. 4 (November 1, 2018): 55. http://dx.doi.org/10.3390/machines6040055.

Full text
Abstract:
Maintenance scheduling for geographically dispersed assets intricately and closely depends on the availability of maintenance resources. The need to have the right spare parts at the right place and at the right time inevitably calls for joint optimization of maintenance schedules and logistics of maintenance resources. The joint decision-making problem becomes particularly challenging if one considers multiple options for preventive maintenance operations and multiple delivery methods for the necessary spare parts. In this paper, we propose an integrated decision-making policy that jointly considers scheduling of preventive maintenance for geographically dispersed multi-part assets, managing inventories for spare parts being stocked in maintenance facilities, and choosing the proper delivery options for the spare part inventory flows. A discrete-event, simulation-based meta-heuristic was used to optimize the expected operating costs, which reward the availability of assets and penalizes the consumption of maintenance/logistic resources. The benefits of joint decision-making and the incorporation of multiple options for maintenance and logistic operations into the decision-making framework are illustrated through a series of simulations. Additionally, sensitivity studies were conducted through a design-of-experiment (DOE)-based analysis of simulation results. In summary, considerations of concurrent optimization of maintenance schedules and spare part logistic operations in an environment in which multiple maintenance and transpiration options are available are a major contribution of this paper. This large optimization problem was solved through a novel simulation-based meta-heuristic optimization, and the benefits of such a joint optimization are studied via a unique and novel DOE-based sensitivity analysis.
APA, Harvard, Vancouver, ISO, and other styles
3

Xie, Lubing, Xiaoming Rui, Shuai Li, and Xin Hu. "Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy." Energies 12, no. 14 (July 10, 2019): 2650. http://dx.doi.org/10.3390/en12142650.

Full text
Abstract:
Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.
APA, Harvard, Vancouver, ISO, and other styles
4

Goti, Aitor, Aitor Oyarbide-Zubillaga, Ana Sanchez, Tugce Akyazi, and Elisabete Alberdi. "Multi Equipment Condition Based Maintenance Optimization Using Multi-Objective Evolutionary Algorithms." Applied Sciences 9, no. 22 (November 13, 2019): 4849. http://dx.doi.org/10.3390/app9224849.

Full text
Abstract:
Thanks to the digitalization of industry, maintenance is a trending topic. The amount of data available for analyses and optimizations in this field has increased considerably. In addition, there are more and more complex systems to maintain, and to keep all these devices in proper conditions, which requires maintenance management to gain efficiency and effectiveness. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, but often these programs are complex to manage and understand. The problem becomes more complex when equipment is analyzed in the context of a plant, where equipment can be more or less saturated, critical regarding quality, etc. Thus, this paper focuses on CBM optimization of a full industrial chain, with the objective of determining its optimal values of preventive intervention limits for equipment under economic criteria. It develops a mathematical plus discrete-event-simulation based model that takes the evolution in quality and production speed into consideration as well as condition based, corrective and preventive maintenance. The optimization process is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case, where the data gathered by the IoT (Internet of Things) devices at edge level can detect when some premises of the CBM model are no longer valid and request a new simulation. The simulation performed in a centralized way can thus obtain new optimal values who fit better to the actual system than the existing ones. Finally, these new optimal values can be transferred to the model whenever it is necessary. The approach developed has raised the interest of a partner of the Deusto Digital Industry Chair.
APA, Harvard, Vancouver, ISO, and other styles
5

DING, FANGFANG, and ZHIGANG TIAN. "OPPORTUNISTIC MAINTENANCE OPTIMIZATION FOR WIND TURBINE SYSTEMS CONSIDERING IMPERFECT MAINTENANCE ACTIONS." International Journal of Reliability, Quality and Safety Engineering 18, no. 05 (October 2011): 463–81. http://dx.doi.org/10.1142/s0218539311004196.

Full text
Abstract:
Currently corrective maintenance and time-based preventive maintenance strategies are widely used in wind power industry. However, few methods are applied to optimize these strategies. This paper aims to develop opportunistic maintenance approaches for an entire wind farm rather than individual components that most of the existing studies deal with. Furthermore, we consider imperfect actions in the preventive maintenance tasks, which address the issue that preventive maintenance do not always return components to the as-good-as-new status in practice. In this paper we propose three opportunistic maintenance optimization models, where the preventive maintenance is considered as perfect, imperfect and two-level action, respectively. Simulation methods are developed to evaluate the costs of the proposed opportunistic maintenance policies. Numerical examples are provided to demonstrate the advantage of the proposed opportunistic maintenance methods in reducing the maintenance cost. The two-level action method demonstrates to be the most cost-effective in different cost situations, while the imperfect maintenance policy, which is a simpler method, is a close second. The developed methods are expected to bring immediate benefits to wind power industry.
APA, Harvard, Vancouver, ISO, and other styles
6

Bányai, Ágota. "Energy Consumption-Based Maintenance Policy Optimization." Energies 14, no. 18 (September 9, 2021): 5674. http://dx.doi.org/10.3390/en14185674.

Full text
Abstract:
The optimal predictive, preventive, corrective and opportunistic maintenance policies play an important role in the success of sustainable maintenance operations. This study discusses a new energy efficiency-related maintenance policy optimization method, which is based on failure data and status information from both the physical system and the digital twin-based discrete event simulation. The study presents the functional model, the mathematical model and the solution algorithm. The maintenance optimization method proposed in this paper is made up of four main phases: computation of energy consumption based on the levelized cost of energy, computation of GHG emission, computation of value determination equations and application of the Howard’s policy iteration techniques. The approach was tested with a scenario analysis, where different electricity generation sources were taken into consideration. The computational results validated the optimization method and show that optimized maintenance policies can lead to an average of 38% cost reduction regarding energy consumption related costs. Practical implications of the proposed model and method regard the possibility of finding optimal maintenance policies that can affect the energy consumption and emissions from the operation and maintenance of manufacturing systems.
APA, Harvard, Vancouver, ISO, and other styles
7

Supsomboon, Srisawat, and Kanthapong Hongthanapach. "A Simulation Model for Machine Efficiency Improvement Using Reliability Centered Maintenance: Case Study of Semiconductor Factory." Modelling and Simulation in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/956182.

Full text
Abstract:
The purpose of this study was to increase the quality of product by focusing on the machine efficiency improvement. The principle of the reliability centered maintenance (RCM) was applied to increase the machine reliability. The objective was to create preventive maintenance plan under reliability centered maintenance method and to reduce defects. The study target was set to reduce the Lead PPM for a test machine by simulating the proposed preventive maintenance plan. The simulation optimization approach based on evolutionary algorithms was employed for the preventive maintenance technique selection process to select the PM interval that gave the best total cost and Lead PPM values. The research methodology includes procedures such as following the priority of critical components in test machine, analyzing the damage and risk level by using Failure Mode and Effects Analysis (FMEA), calculating the suitable replacement period through reliability estimation, and optimizing the preventive maintenance plan. From the result of the study it is shown that the Lead PPM of test machine can be reduced. The cost of preventive maintenance, cost of good product, and cost of lost product were decreased.
APA, Harvard, Vancouver, ISO, and other styles
8

Li, Yan, Peng Han, Jinkuan Wang, and Xin Song. "Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries." Mathematical Problems in Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/9798406.

Full text
Abstract:
Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.
APA, Harvard, Vancouver, ISO, and other styles
9

Wang, Rongcai, Zhonghua Cheng, Enzhi Dong, Chiming Guo, and Liqing Rong. "Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty." Discrete Dynamics in Nature and Society 2021 (May 7, 2021): 1–16. http://dx.doi.org/10.1155/2021/5541902.

Full text
Abstract:
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.
APA, Harvard, Vancouver, ISO, and other styles
10

Aldubaisi, Ali, and Jorge Valenzuela. "Maintenance Optimization of Wind Turbines Using Weather-Dependent Equivalent Age Model." Journal of Energy and Power Technology 03, no. 03 (April 26, 2021): 1. http://dx.doi.org/10.21926/jept.2103036.

Full text
Abstract:
Aging models are important input into wind farm maintenance and financial viability models. Aging of wind turbines depends on many factors, including both ambient and usage conditions. This paper presents a virtual age based maintenance model for wind turbines considering the effect of wind speed and ambient air temperature on turbine aging. Two maintenance thresholds (i.e., corrective threshold and preventive threshold) and three repair actions (i.e., unscheduled corrective, scheduled corrective and preventive actions) are integrated into the maintenance model. The objective is to determine the optimal thresholds values that minimize the expected total maintenance costs. A discreet time simulation model is developed to produce 20 years of weather and usage scenarios for a single onshore wind turbine. The optimization model is formulated as a mixed-integer nonlinear problem and solved using the Nelder–Mead method. A numerical example is presented to highlight the benefits of the proposed approach. Compared with traditional age-based maintenance, the proposed approach can achieve improvement in both availability and costs. The results show up to 50% reduction in maintenance cost as well as the significance of the effects of wind speed and ambient air temperature in maintenance planning.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Simulation based preventive maintenance optimization"

1

Scaglioso, Giovanni. "Modelling, simulation and optimization of maintenance considerations on condition based maintenance." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8308/.

Full text
Abstract:
Globalization has increased the pressure on organizations and companies to operate in the most efficient and economic way. This tendency promotes that companies concentrate more and more on their core businesses, outsource less profitable departments and services to reduce costs. By contrast to earlier times, companies are highly specialized and have a low real net output ratio. For being able to provide the consumers with the right products, those companies have to collaborate with other suppliers and form large supply chains. An effect of large supply chains is the deficiency of high stocks and stockholding costs. This fact has lead to the rapid spread of Just-in-Time logistic concepts aimed minimizing stock by simultaneous high availability of products. Those concurring goals, minimizing stock by simultaneous high product availability, claim for high availability of the production systems in the way that an incoming order can immediately processed. Besides of design aspects and the quality of the production system, maintenance has a strong impact on production system availability. In the last decades, there has been many attempts to create maintenance models for availability optimization. Most of them concentrated on the availability aspect only without incorporating further aspects as logistics and profitability of the overall system. However, production system operator’s main intention is to optimize the profitability of the production system and not the availability of the production system. Thus, classic models, limited to represent and optimize maintenance strategies under the light of availability, fail. A novel approach, incorporating all financial impacting processes of and around a production system, is needed. The proposed model is subdivided into three parts, maintenance module, production module and connection module. This subdivision provides easy maintainability and simple extendability. Within those modules, all aspect of production process are modeled. Main part of the work lies in the extended maintenance and failure module that offers a representation of different maintenance strategies but also incorporates the effect of over-maintaining and failed maintenance (maintenance induced failures). Order release and seizing of the production system are modeled in the production part. Due to computational power limitation, it was not possible to run the simulation and the optimization with the fully developed production model. Thus, the production model was reduced to a black-box without higher degree of details.
APA, Harvard, Vancouver, ISO, and other styles
2

Albright, Michael H. "An optimization-based decision support model for the Navy H-60 helicopter preventive maintenance program." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1998. http://handle.dtic.mil/100.2/ADA355527.

Full text
Abstract:
Thesis (M.S. in Operations Research) Naval Postgraduate School, September 1998.
"September 1998." Thesis advisor(s): Gerald G. Brown. Includes bibliographical references (p. 35-36). Also available online.
APA, Harvard, Vancouver, ISO, and other styles
3

Li, Jin. "Simulation and Optimization of Integrated Maintenance Strategies for an Aircraft Assembly Process." Thesis, Cranfield University, 2013. http://dspace.lib.cranfield.ac.uk/handle/1826/8439.

Full text
Abstract:
In this thesis, the COMAC ARJ21 fuselage’s final assembly process is used as a case study. High production rate (i.e. number of aircraft assembled per year) with reasonable cost is the overall aim in this example. The output of final assembly will essentially affect the prior and subsequent processes of the overall ARJ21 production. From the collected field data, it was identified that a number of disruptions (or bottlenecks) in the assembly sequence were caused by breakdowns and maintenance of the (semi-)automatic assembly machines like portable computer numerical control (CNC) drilling machine, rivet gun and overhead crane. The focus of this thesis is therefore on the maintenance strategies (i.e. Condition-Based Maintenance (CBM)) for these equipment and how they impact the throughput of the fuselage assembly process. The fuselage assembly process is modelled and analysed by using agent-based simulation in this thesis. The agent approach allows complex process interactions of assembly, equipment and maintenance to be captured and empirically studied. In this thesis, the built network is modelled as the sequence of activities in each stage. Each stage is broken down into critical activities which are parameterized by activity lead-time and equipment used. CBM based models of uncertain degradation and imperfect maintenance are used in the simulation study. A scatter search is used to find multi-objective optimal solutions for the CBM regime, where the maintenance-related cost and production rate are the optimization objectives. In this thesis, in order to ease computation intensity caused by running multiple simulations during the optimization and to simplify a multi-objective formulation, multiple Min-Max weightings are applied to trace Pareto front. The empirical analysis reviews the trade-offs between the production rate and maintenance cost and how these objectives are influenced by the design parameters.
APA, Harvard, Vancouver, ISO, and other styles
4

Bergkvist, Bo, and Mattias Örjas. "Monte Carlo simulation based preventive maintenance plan for a sewage pump system Case study - Nacka Municipality." Thesis, KTH, Tillämpad maskinteknik (KTH Södertälje), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152209.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Nasri, Imed. "Développement d'une méthodologie d'ordonnancement/optimisation adaptée aux systèmes industriels de type HVLV (High-Variety, Low-Volume)." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00831002.

Full text
Abstract:
Les travaux présentés dans cette thèse portent sur la conception d'une méthodologie d'ordonnancement/optimisation pour les systèmes de production à grande variété de produits et faible densité de flux appelés systèmes HVLV (High-Variety, LowVolume). Les caractéristiques de ces systèmes nous permettent d'appréhender la représentation des flux y circulant par un modèle discret. Le comportement discontinu des systèmes HVLV peut être caractérisé par la connaissance des dates de début et de fin des activités de production. L'algèbre (max, +) est utilisée pour représenter ce type de systèmes où les relations entre les dates de début des activités nécessitent l'utilisation des opérateurs maximum et addition. Afin d'utiliser l'algèbre (max, +) pour l'ordonnancement des systèmes HVLV, il est indispensable de résoudre un problème de conflit et d'optimisation sous contraintes dans cette algèbre. D'abord, nous avons développé dans ces travaux de recherche un modèle d'ordonnancement (max, +) pour les systèmes HVLV dans lequel des variables de décision ont été introduites afin de résoudre le problème de conflit entre les opérations exécutées sur les machines. Ensuite, nous avons amélioré le modèle proposé pour tenir compte de la maintenance préventive. Deux types de maintenance ont été considérés : Maintenance Périodique Répétitive (MPR) et Maintenance Flexible Périodique (MFP). Dans les deux cas, un problème d'ordonnancement non-linéaire sous contraintes a été résolu afin de minimiser certains critères de performance. Enfin, la méthodologie proposée a été validée par simulation, sur des systèmes HVLV complexes de type job-shop.
APA, Harvard, Vancouver, ISO, and other styles
6

Singh, Inderjeet 1978. "Risk-averse periodic preventive maintenance optimization." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-08-4203.

Full text
Abstract:
We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can be repaired upon failure, through corrective maintenance (CM). We develop analytical and simulation-based optimization models that seek an optimal periodic PM policy, which minimizes the sum of the expected total cost of PMs and the risk-averse cost of CMs, over a finite planning horizon. In the simulation-based models, we assume that both types of maintenance actions are imperfect, whereas our analytical models consider imperfect PMs with minimal CMs. The effectiveness of maintenance actions is modeled using age reduction factors. For a repairable unit of equipment, its virtual age, and not its calendar age, determines the associated failure rate. Therefore, two sets of parameters, one describing the effectiveness of maintenance actions, and the other that defines the underlying failure rate of a piece of equipment, are critical to our models. Under a given maintenance policy, the two sets of parameters and a virtual-age-based age-reduction model, completely define the failure process of a piece of equipment. In practice, the true failure rate, and exact quality of the maintenance actions, cannot be determined, and are often estimated from the equipment failure history. We use a Bayesian approach to parameter estimation, under which a random-walk-based Gibbs sampler provides posterior estimates for the parameters of interest. Our posterior estimates for a few datasets from the literature, are consistent with published results. Furthermore, our computational results successfully demonstrate that our Gibbs sampler is arguably the obvious choice over a general rejection sampling-based parameter estimation method, for this class of problems. We present a general simulation-based periodic PM optimization model, which uses the posterior estimates to simulate the number of operational equipment failures, under a given periodic PM policy. Optimal periodic PM policies, under the classical maximum likelihood (ML) and Bayesian estimates are obtained for a few datasets. Limitations of the ML approach are revealed for a dataset from the literature, in which the use of ML estimates of the parameters, in the maintenance optimization model, fails to capture a trivial optimal PM policy. Finally, we introduce a single-stage and a two-stage formulation of the risk-averse periodic PM optimization model, with imperfect PMs and minimal CMs. Such models apply to a class of complex equipment with many parts, operational failures of which are addressed by replacing or repairing a few parts, thereby not affecting the failure rate of the equipment under consideration. For general values of PM age reduction factors, we provide sufficient conditions to establish the convexity of the first and second moments of the number of failures, and the risk-averse expected total maintenance cost, over a finite planning horizon. For increasing Weibull rates and a general class of increasing and convex failure rates, we show that these convexity results are independent of the PM age reduction factors. In general, the optimal periodic PM policy under the single-stage model is no better than the optimal two-stage policy. But if PMs are assumed perfect, then we establish that the single-stage and the two-stage optimization models are equivalent.
text
APA, Harvard, Vancouver, ISO, and other styles
7

AlBarbary, Haitham Gamal. "Simulation-based maintenance schedule optimization under supply and demand uncertainty." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-08-3763.

Full text
Abstract:
This MS thesis studies the effect of uncertainty in the demand of finished products, supply of raw materials, and maintenance resources availability on the maintenance schedule of a manufacturing facility. A simulation model is formulated in order to realistically model manufacturing systems of various complexities, consisting of multiple interacting machines that degrade and fail over time, and are repaired using imperfectly available maintenance crews and resources. A design of experiments (DOE) based sensitivity study is conducted to find the system parameters that mostly affected the maintenance decisions and corresponding profits.
text
APA, Harvard, Vancouver, ISO, and other styles
8

Byon, Eunshin. "Simulation and Optimization of Wind Farm Operations under Stochastic Conditions." Thesis, 2010. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7791.

Full text
Abstract:
This dissertation develops a new methodology and associated solution tools to achieve optimal operations and maintenance strategies for wind turbines, helping reduce operational costs and enhance the marketability of wind generation. The integrated framework proposed includes two optimization models for enabling decision support capability, and one discrete event-based simulation model that characterizes the dynamic operations of wind power systems. The problems in the optimization models are formulated as a partially observed Markov decision process to determine an optimal action based on a wind turbine's health status and the stochastic weather conditions. The rst optimization model uses homogeneous parameters with an assumption of stationary weather characteristics over the decision horizon. We derive a set of closed-form expressions for the optimal policy and explore the policy's monotonicity. The second model allows time-varying weather conditions and other practical aspects. Consequently, the resulting strategy are season-dependent. The model is solved using a backward dynamic programming method. The bene ts of the optimal policy are highlighted via a case study that is based upon eld data from the literature and industry. We nd that the optimal policy provides options for cost-e ective actions, because it can be adapted to a variety of operating conditions. Our discrete event-based simulation model incorporates critical components, such as a wind turbine degradation model, power generation model, wind speed model, and maintenance model. We provide practical insights gained by examining di erent maintenance strategies. To the best of our knowledge, our simulation model is the rst discrete-event simulation model for wind farm operations. Last, we present the integration framework, which incorporates the optimization results in the simulation model. Preliminary results reveal that the integrated model has the potential to provide practical guidelines that can reduce the operation costs as well as enhance the marketability of wind energy.
APA, Harvard, Vancouver, ISO, and other styles
9

Chen, You-Ying, and 陳又熒. "Optimal Condition-Based Maintenance and Inventory Policy in a Continuously Monitoring System Using Simulation Optimization." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/z2nhnq.

Full text
Abstract:
碩士
國立清華大學
工業工程與工程管理學系所
105
This paper considers condition-based maintenance and spare parts inventory policy simultaneously for a system consisting of different machines and components. The degradation of the components are modeled by Gamma process. By the sensors on the components, we continuously monitor the degradation level of the components, and once the degradation level exceeds the predefined degradation thresholds, imperfect repair maintenance or replacement maintenance are performed. A simulation-based optimization approach is proposed to find the optimal components inventory policy and degradation level thresholds of components. The proposed approach is based on Stochastic Trust-Region Response Surface Method (STRONG), coupled with the Kriging metamodel and the Nelder-Mead simplex method. A numerical study shows that the proposed model and the method can achieve minimized maintenance cost as expected.
APA, Harvard, Vancouver, ISO, and other styles
10

Dao, Cuong D., B. Kazemtabrizi, C. J. Crabtree, and P. J. Tavner. "Integrated condition-based maintenance modelling and optimisation for offshore wind turbines." 2021. http://hdl.handle.net/10454/18409.

Full text
Abstract:
Yes
Wind Energy published by John Wiley & Sons Ltd. Maintenance is essential in keeping wind energy assets operating efficiently. With the development of advanced condition monitoring, diagnostics and prognostics, condition-based maintenance has attracted much attention in the offshore wind industry in recent years. This paper models various maintenance activities and their impacts on the degradation and performance of offshore wind turbine components. An integrated maintenance strategy of corrective maintenance, imperfect time-based preventive maintenance and condition-based maintenance is proposed and compared with other traditional maintenance strategies. A maintenance simulation programme is developed to simulate the degradation and maintenance of offshore wind turbines and estimate their performance. A case study on a 10-MW offshore wind turbine (OWT) is presented to analyse the performance of different maintenance strategies. The simulation results reveal that the proposed strategy not only reduces the total maintenance cost but also improves the energy generation by reducing the total downtime and expected energy not supplied. Furthermore, the proposed maintenance strategy is optimised to find the best degradation threshold and balance the trade-off between the use of condition-based maintenance and other maintenance activities.
UK Engineering and Physical Sciences Research Council (EPSRC). Grant Number: EP/P009743/1
APA, Harvard, Vancouver, ISO, and other styles

Books on the topic "Simulation based preventive maintenance optimization"

1

Albright, Michael H. An optimization-based decision support model for the Navy H-60 helicopter preventive maintenance program. Monterey, Calif: Naval Postgraduate School, 1998.

Find full text
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Simulation based preventive maintenance optimization"

1

Riane, Fouad, Olivier Roux, Olivier Basile, and Pierre Dehombreux. "Simulation Based Approaches for Maintenance Strategies Optimization." In Handbook of Maintenance Management and Engineering, 133–53. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-472-0_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Gosavi, Abhijit, and Susan Murray. "Simulation-based Methods for Studying Reliability and Preventive Maintenance of Public Infrastructure." In Springer Series in Reliability Engineering, 107–21. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-213-9_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Cinus, Marco, Matteo Confalonieri, Andrea Barni, and Anna Valente. "An ANN Based Decision Support System Fostering Production Plan Optimization Through Preventive Maintenance Management." In Advances in Neural Networks, 447–55. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33747-0_44.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Bal, Alperen, and Sule Itir Satoglu. "Mathematical Optimization Models for the Maintenance Policies in Production Systems." In Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems, 252–68. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2944-6.ch012.

Full text
Abstract:
This chapter initially presents a brief information about production systems. At these systems, different types of maintenance policies are developed to cope with wear out failures. Mainly used maintenance policies can be classified as corrective, preventive, and condition-based maintenance. In the corrective maintenance, repair or replacement is applied whenever components of the machine breakdown. In the preventive maintenance approach maintenance activities are applied to the critical components on a periodic basis. On the other hand, maintenance activities are applied whenever critical reliability level is reached or exceeded. These types of maintenance policies are modeled using mathematical modeling techniques such as linear programming, goal programming, dynamic programming, and simulation. A review of current literature about the mathematical models, the simulation-based optimization studies examining these maintenance policies are categorized and explained. Besides, the solution methodologies are discussed. Finally, the opportunities for future research are presented.
APA, Harvard, Vancouver, ISO, and other styles
5

Khan, Laiq, Rabiah Badar, and Sidra Mumtaz. "Generators Maintenance Scheduling Using Music-Inspired Harmony Search Algorithm." In Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance, 448–83. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch015.

Full text
Abstract:
This work explores the potential of Music-Inspired Harmony Search (MIHS), meta-heuristic technique, in the area of power system for Generator Maintenance Scheduling (GMS). MIHS has been used to generate optimal preventive maintenance schedule for generators to maintain reliable and economical power system operation taking into account the maintenance window, load and crew constraints. The robustness of the algorithm has been evaluated for five different case studies: 8-units test system, 13-units test system, 21-units test system, 62-units test system, and 136-units test system of Water and Power Development Authority (WAPDA) Pakistan. As per previous practice, WAPDA used to use manual scheduling based on hit-and-trial. The simulations have been carried out in MATLAB®. Based on its comparison with Genetic Algorithm (GA), it has been found that MIHS has fast convergence rate and optimal schedule for all the test systems satisfying the stated constraints.
APA, Harvard, Vancouver, ISO, and other styles
6

Peng, Hao. "Condition-Based Maintenance." In Analyzing Risk through Probabilistic Modeling in Operations Research, 292–320. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9458-3.ch012.

Full text
Abstract:
Condition-Based Maintenance (CBM) is one type of preventive maintenance policy. CBM has attracted lots of attentions of both academia and industry due to the development of advanced sensor technology and measurement devices. The proper implementation of CBM can reduce the frequency of random failures and the expected cost of maintenance during the lifecycle of a system. In this chapter, a brief overview of different maintenance strategies is first provided for the readers who are not familiar with maintenance optimization models. Then several elementary models about CBM will be introduced to help the readers get a general idea of the optimization models in this field.
APA, Harvard, Vancouver, ISO, and other styles
7

Jang, D., I. Kim, H. Jung, and J. Koo. "Investigation of the control performance of the smart passive system based on MR damperusing hybrid simulation." In Bridge Maintenance, Safety, Management and Life-Cycle Optimization, 88. CRC Press, 2010. http://dx.doi.org/10.1201/b10430-22.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Bonnet, B., and P. Dersin. "Optimization of preventive maintenance policy based on operational reliability analysis (Application to tramway access doors)." In Advances in Safety, Reliability and Risk Management, 2720–23. CRC Press, 2011. http://dx.doi.org/10.1201/b11433-387.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Calixto, E., Yizhak Bot, and Amir Segal. "Integrated Logistic Support: RAM, preventive maintenance, inspection, spare parts and life cycle cost optimization based on dynamic programming method." In Safety and Reliability of Complex Engineered Systems, 873–81. CRC Press, 2015. http://dx.doi.org/10.1201/b19094-118.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Goti, Aitor, and Alvaro Garci. "Condition Based Maintenance Optimization of Multi-Equipment Manufacturing Systems by Combining Discrete Event Simulation and Multiobjective Evolutionary Algorithms." In Discrete Event Simulations. Sciyo, 2010. http://dx.doi.org/10.5772/9900.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Simulation based preventive maintenance optimization"

1

Cluever, Joseph, Thomas Esselman, and Sam Harvey. "Value-Based Bayesian Optimization of Preventive Maintenance Programs." In ASME 2018 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/pvp2018-84832.

Full text
Abstract:
The EPRI Preventive Maintenance Basis Database (PMBD) has become a standard in the industry to develop, validate, or examine the impact of custom changes to maintenance strategies for common power plant equipment. The PMBD provides failure modes and an indication of frequency of occurrence. Recent feedback from PMBD users has made it clear that including a “Cost Module” to work with PMBD data would be a useful addition to the PMBD program and allow users to view the cost impacts associated with alternate custom maintenance strategies. This paper presents a methodology for the merging of maintenance information extracted from PMBD with cost estimates and additional expert-provided reliability data to estimate a maintenance cost distribution. Additional expert information includes missing data and PM type: monitoring, wear-rate reducing (e.g. oil change), or life-restoring (e.g. refurbishment). The cost distribution is calculated via Monte Carlo simulation and is dependent on the PM plan currently considered. Value-based optimization of the PM plan is performed through Bayesian optimization of the mean PM cost by varying the various PM frequencies. Bayesian optimization iteratively uses Gaussian Process Regression (GPR) to fit a non-parametric meta-model to a noisy objective function. As a part of GPR it is necessary to fit a covariance function that describes the spatial correlation or smoothness of the objective cost function. The meta-model with the covariance function effectively produces a built-in sensitivity analysis for the optimization as well.
APA, Harvard, Vancouver, ISO, and other styles
2

Hamedi, Maryam, Saeed Sharafi, and Mojtaba Tagheh Delshad. "Optimization of Preventive Maintenance Scheduling based on Monte Carlo Simulation in Processing Plants." In 2019 15th Iran International Industrial Engineering Conference (IIIEC). IEEE, 2019. http://dx.doi.org/10.1109/iiiec.2019.8720622.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Ramirez-Hernandez, Jose A., and Emmanuel Fernandez. "Optimization of Preventive Maintenance scheduling in semiconductor manufacturing models using a simulation-based Approximate Dynamic Programming approach." In 2010 49th IEEE Conference on Decision and Control (CDC). IEEE, 2010. http://dx.doi.org/10.1109/cdc.2010.5717523.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Lyubchenko, Alexander, Alexander Shiler, Evgeny Y. Kopytov, and Vasilii A. Maystrenko. "Computer-aided analysis of reliability and preventive maintenance optimization of radio communication equipment based on multivariate Monte Carlo simulation." In 2017 International Siberian Conference on Control and Communications (SIBCON). IEEE, 2017. http://dx.doi.org/10.1109/sibcon.2017.7998459.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Li, Yunpeng, and Utpal Roy. "Challenges in Developing a Computational Platform to Integrate Data Analytics With Simulation-Based Optimization." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46410.

Full text
Abstract:
The focus of the work presented in this paper is to identify and find possible solutions for major implementation challenges in designing a computational platform for integrating data analytics paradigm with the simulation-based optimization technique to facilitate the modeling of a smart manufacturing system. A simulation model of a manufacturing system generates real-time monitoring data for machine status and these data are then mined by data mining algorithms to discover hidden knowledge that might not be predefined in the simulation model. The new knowledge is then fed into the simulation model such that the model adapts and evolves, and eventually it can predict future status. This procedure involves heterogeneous modeling techniques, information exchange among different tools, as well as model composition and interaction. We extend an early presented “Hypercube” information model that was specifically developed for the purpose of formal representation of smart manufacturing systems, in order to harmonize the information required by the simulation modeling tool and the data analytics tool. A strong emphasis is given to emerging areas of multi-domain and multiscale modeling by means of integration and interoperability between existing modeling tools and technologies. A specific case study related to preventive and predictive maintenance of a typical manufacturing system has been elaborated in the paper as the initial scope and application area in order to illustrate and validate the proposed computational framework.
APA, Harvard, Vancouver, ISO, and other styles
6

Li, Xinyue, Yunxian Jia, Pengju Li, and Xiaoqian Zhang. "Optimization of preventive maintenance period based on AFSA." In 2011 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE). IEEE, 2011. http://dx.doi.org/10.1109/icqr2mse.2011.5976694.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Altuger, Gonca, and Constantin Chassapis. "Multi criteria preventive maintenance scheduling through Arena based simulation modeling." In 2009 Winter Simulation Conference - (WSC 2009). IEEE, 2009. http://dx.doi.org/10.1109/wsc.2009.5429668.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Yuting, Jiao, Feng Xiaodong, Lv Chuan, and Guo Zhiqi. "Research on preventive maintenance strategy optimization based on reliability threshold." In 2014 Prognostics and System Health Management Conference (PHM-2014 Hunan). IEEE, 2014. http://dx.doi.org/10.1109/phm.2014.6988240.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Xie, Jun, and Hongwei Wang. "Joint Optimization of Condition-Based Preventive Maintenance and Spare Ordering Policy." In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.1468.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chen, Zhen, Yaping Li, and Ershun Pan. "Joint optimization of degradation-based burn-in, quality, and preventive maintenance." In 2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2016. http://dx.doi.org/10.1109/ieem.2016.7798107.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Simulation based preventive maintenance optimization' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography