Condition-based Maintenance Optimization for Gamma Deteriorating Systems under Performance-based Contracting

With the further development of service-oriented,performance-based contracting(PBC)has been widely adopted in industry and manufacturing.However,maintenance optimization problems under PBC have not received enough attention.To further extend the scope of PBC’s application in the field of maintenance optimization,we investigate the condition-based maintenance(CBM)optimization for gamma deteriorating systems under PBC.Considering the repairable single-component system subject to the gamma degradation process,this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC.In the proposed CBM model,the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate.Then,a particle swarm algorithm(PSO)and related solution procedure are presented to solve the multiple decision variables in our proposed model.In the end,a numerical example is provided so as to demonstrate the superiority of the presented model.By comparing the proposed policy with the conventional ones,the superiority of our proposed policy is proved,which can bring more profits to providers and improve performance.Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy.A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.

Condition-Based Maintenance Decision-Making for Equipment

At present, condition monitoring and fault diagnosis technology and their application in engineering have been widely studied. Relatively little attention has been paid to condition-based maintenance decision-making for equipment. In this paper,based on the decision-making policy in traditional condition-based maintenance,the connotation of condition-based maintenance for equipment was defined, and its characteristics were analyzed.Working contents of condition-based maintenance for equipment were provided,which were divided into three stages. The influence factors in condition-based maintenance for equipment were analyzed. The key links of equipment maintenance contents and decision-making process were proposed. The condition-based maintenance decision-making policy presented in this paper can provide a practical reference for equipment maintenance.

Research on Carbon Emission for Preventive Maintenance of Wind Turbine Gearbox Based on Stochastic Differential Equation

Time based maintenance(TBM)and condition based maintenance(CBM)are widely applied in many large wind farms to optimize the maintenance issues of wind turbine gearboxes,however,these maintenance strategies do not take into account environmental benefits during full life cycle such as carbon emissions issues.Hence,this article proposes a carbon emissions computing model for preventive maintenance activities of wind turbine gearboxes to solve the issue.Based on the change of the gearbox state during operation and the influence of external random factors on the gearbox state,a stochastic differential equation model(SDE)and corresponding carbon emission model are established,wherein SDE is applied to model the evolution of the device state,whereas carbon emission is used to implement carbon emissions computing.The simulation results indicate that the proposed preventive maintenance cannot ensure reliable operation of wind turbine gearboxes but reduce carbon emissions during their lifespan.Compared with TBM,CBM minimizes unit carbon emissions without influencing reliable operation,making it an effective maintenance method.

Development of Maintenance Management Strategy Based on Reliability Centered Maintenance for Marginal Oilfield Production Facilities

The present work adopted Reliability Centered Maintenance (RCM) methodology to evaluate marginal oilfield Early Production Facility (EPF) system to properly understand its functional failures and to develop an efficient maintenance strategy for the system. The outcome of the RCM conducted for a typical EPF within the Niger Delta zone of Nigeria provides an indication of equipment whose failure can significantly affect operations at the production facility. These include the steam generation unit and the wellhead choke assembly, using a risk-based failure Criticality Analysis. Failure Mode and Effect Analysis (FMEA) was conducted for the identified critical equipment on a component basis. Each component of the equipment was analyzed to identify the failure modes, causes and the effect of the failure. The outcome of the FMEA analysis aided the development of a robust maintenance management strategy, which is based on an optimized mix of corrective, preventive and condition-based monitoring maintenance for the marginal oilfield EPF.

Condition-based maintenance policy for gamma deteriorating systems

A condition-based maintenance model for gamma deteriorating system under continuous inspection is studied. This methodology uses a gamma distribution to model the material degradation, and the impact of imperfect maintenance actions on the system reliability is investigated. The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process. Furthermore, the explicit expressions for the long-run average cost and availability per unit time of the system are evaluated, an optimal policy （ε^＊） could be determined numeri- cally or analytically according to the optimization model. At last, a numerical example for a degrading system modeled by a gamma process is presented to demonstrate the use of this policy in practical applications.

Condition-based maintenance optimization for continuously monitored degrading systems under imperfect maintenance actions

Condition-based maintenance(CBM) is receiving increasing attention in various engineering systems because of its effectiveness. This paper formulates a new CBM optimization problem for continuously monitored degrading systems considering imperfect maintenance actions. In terms of maintenance actions,in practice, they scarcely restore the system to an as-good-as new state due to residual damage. According to up-to-data researches, imperfect maintenance actions are likely to speed up the degradation process. Regarding the developed CBM optimization strategy, it can balance the maintenance cost and the availability by the searching the optimal preventive maintenance threshold.The maximum number of maintenance is also considered, which is regarded as an availability constraint in the CBM optimization problem. A numerical example is introduced, and experimental results can demonstrate the novelty, feasibility and flexibility of the proposed CBM optimization strategy.

A dynamic condition-based maintenance optimization model for mission-oriented system based on inverse Gaussian degradation process

An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. Meanwhile, the risk of early failure is high. Therefore, this paper proposes a dynamic condition-based maintenance(CBM) optimization model for mission-oriented system based on inverse Gaussian(IG) degradation process. Firstly, the IG process with random drift coefficient is used to describe the degradation process and the relevant probability distributions are obtained. Secondly, the dynamic preventive maintenance threshold(DPMT) function is used to control the early failure risk of the mission-oriented system, and the influence of imperfect preventive maintenance(PM)on the degradation amount and degradation rate is analysed comprehensively. Thirdly, according to the mission availability requirement, the probability formulas of different types of renewal policies are obtained, and the CBM optimization model is constructed. Finally, a numerical example is presented to verify the proposed model. The comparison with the fixed PM threshold model and the sensitivity analysis show the effectiveness and application value of the optimization model.

Joint optimization of sampling interval and control for condition-based maintenance using availability maximization criterion

Most of the maintenance optimization models in condition-based maintenance(CBM) consider the cost-optimal criterion, but few papers have dealt with availability maximization for maintenance applications. A novel optimal Bayesian control approach is presented for maintenance decision making. The system deterioration evolves as a three-state continuous time hidden semi-Markov process. Considering the optimal maintenance policy, the multivariate Bayesian control scheme based on the hidden semi-Markov model(HSMM) is developed, the objective is to maximize the long-run expected average availability per unit time. The proposed approach can optimize the sampling interval and control limit jointly. A case study using Markov chain Monte Carlo(MCMC)simulation is provided and a comparison with the Bayesian control scheme based on hidden Markov model(HMM), the age-based replacement policy, Hotelling’s T2, multivariate exponentially weihted moving average(MEWMA) and multivariate cumulative sum(MCUSUM) control charts is given, which illustrates the effectiveness of the proposed method.

Maintenance and Condition-Based Maintenance

The evolution of maintenance management is briefly introduced in this paper, from corrective maintenance to preventive maintenance. First, a range of condition monitoring and fault diagnosis techniques developed in different industries are surveyed; Second, many methods of condition monitoring are presented; Third, mathematical methods used in condition monitoring are given; Then the merits and shortcomings are discussed. Efficient maintenance policies are of fundamental importance in system engineering because of their fallbacks into the safety and economics of plant operation. Applying condition-based maintenance to a system can reduce the cost and extend the availability of facilities. With the advent of personal computers as fast and cost effective machines for data acquisition and processing of multiple signals some shortcomings mentioned in condition monitoring could be solved or reduced to some extent. These PCs can be a solution as a condition monitoring based maintenance system.

Overview of Condition-Based Maintenance Decision-Making Optimization Modeling of Multi-component System

Overview about three key contents of condition-based maintenance decision-making of a multi-component system is analyzed based on maintenance optimization and modeling. The component deterioration model, the correlation between the degraded components and the system configuration are analyzed separately in the deterioration model of multi-component system.For the maintenance polices,the opportunistic maintenance( OM)policy and the grouping maintenance( GM) policy are analyzed and summarized in combination with the condition-based maintenance( CBM) modeling of multi-component system. It is put forward that CBM modeling of multi-component system should be further researched based on the inspection interval and the maintenance threshold of multi-component system in availability.

Analysis of Condition-Based Maintenance for High-Valtage Electric Power

The development process of high-voltage electric power equipment maintenance was introduced. It is pointed out that the trend of high-voltage electric power equipment maintenance is so called condition-based maintenance. With the development of computer technology and sensors, on-line monitoring of high-voltage electric power equipment has developed rapidly. By introducing the main principle of Schering bridge to measure tanδ, the way of on-line monitoring of high-voltage electric power equipment was explained. Difference methods of on-line monitoring of insulation parameters for 35 kV substation were discussed. Finally, the shortcomings as well as its tendency of on-line monitoring were analyzed.

A Dynamic Maintenance Strategy for Multi-Component Systems Using a Genetic Algorithm

In multi-component systems,the components are dependent,rather than degenerating independently,leading to changes inmaintenance schedules.In this situation,this study proposes a grouping dynamicmaintenance strategy.Considering the structure of multi-component systems,the maintenance strategy is determined according to the importance of the components.The strategy can minimize the expected depreciation cost of the system and divide the system into optimal groups that meet economic requirements.First,multi-component models are grouped.Then,a failure probability model of multi-component systems is established.The maintenance parameters in each maintenance cycle are updated according to the failure probability of the components.Second,the component importance indicator is introduced into the grouping model,and the optimization model,which aimed at a maximum economic profit,is established.A genetic algorithm is used to solve the non-deterministic polynomial(NP)-complete problem in the optimization model,and the optimal grouping is obtained through the initial grouping determined by random allocation.An 11-component series and parallel system is used to illustrate the effectiveness of the proposed strategy,and the influence of the system structure and the parameters on the maintenance strategy is discussed.

Optimization of extended warranty cost for multi-component systems with economic dependence based on group maintenance

During extended warranty(EW)period,maintenance events play a key role in controlling the product systems within normal operations.However,the modelling of failure process and maintenance optimization is complicated owing to the complex features of the product system,namely,components of the multi-component system are interdependent with each other in some form.For the purpose of optimizing the EW pricing decision of the multi-component system scientifically and rationally,taking the series multi-component system with economic dependence sold with EW policy as a research object,this paper optimizes the imperfect preventive maintenance(PM)strategy from the standpoint of EW cost.Taking into consideration adjusting the PM moments of the components in the system,a group maintenance model is developed,in which the system is repaired preventively in accordance with a specified PM base interval.In order to compare with the system EW cost before group maintenance,the system EW cost model before group maintenance is developed.Numerical example demonstrates that offering group maintenance programs can reduce EW cost of the system to a great extent,thereby reducing the EW price,which proves to be a win-win strategy to manufacturers and users.

A condition-based maintenance policy for reconfigurable multi-device systems

The exploration of component states for optimizing maintenance schedules in complex systems has garnered significant interest from researchers.However,current literature usually overlooks the critical aspects of system flexibility and reconfigurability.Judicious implementation of system reconfiguration can effectively mitigate system downtime and enhance production continuity.This study proposes a dynamic condition-based maintenance policy considering reconfiguration for reconfigurable systems.A double-layer decision rule was constructed for the devices and systems.To achieve the best overall maintenance effect of the system,the remaining useful life probability distribution and recommended maintenance time of each device were used to optimize the concurrent maintenance time window of the devices and determine whether to reconfigure them.A comprehensive maintenance efficiency index was introduced that simultaneously considered the maintenance cost rate,reliability,and availability of the system to characterize the overall maintenance effect.The reconfiguration cost was included in the maintenance cost.The proposed policy was tested through numerical experiments and compared with different-level policies.The results show that the proposed policy can significantly reduce the downtime and maintenance costs and improve the overall system reliability and availability.

航天发射场PMSCM任务可靠性仿真评估

为了解决航天发射场复杂可维修多阶段任务系统(phased-mission system,PMS)的任务可靠性评估问题,依据考虑维修的多阶段任务系统(phased-mission system considering maintenance,PMSCM)理论和蒙特卡罗方法,基于系统特殊的任务成功定义规则,通过任务阶段的形式化描述与零部件的虚节点处理,建立可靠性评估仿真模型。将模型应用于航天发射场垂直总装厂房液压系统,成功分析了系统多阶段任务的可靠性均值、方差和置信区间。仿真结果表明:该模型能够找出系统的关键部件,为垂直总装厂房及航天发射场系统总体任务进行可靠性预计、分配和评估提供重要参考和决策支持。

船舶维修决策中的PMS模型研究

海上航运业飞速发展,运输船只的维修效率是各国航运业竞争的有力保障;同时,船舶朝着大型、精密化及高度智能化发向发展,传统依靠人经验的船舶维修策略已经越来越不能适应现代船舶维修要求,需要一套高效的智能化维修保养系统来保障船舶的高频次、高效率运行。PMS系统是现代船舶整个服役周期重要的营运体系,提供了基于软件自动分析的维修保养模型。本文重点研究基于PMS模型的船舶维修策略,最后进行仿真。

船舶机械计划保养系统与PMS检验

船舶机械计划保养体系作为一种新型的机务管理模式,正在我国得到推广。介绍了船舶机械计划保养系统的类型及主要功能,阐明了船舶的机械保养体系与PMS检验的关系,以及船舶申请实施PMS检验的重要意义。

基于PMS系统的输变电红外图谱库管理系统设计及应用

为了实现输变电红外检测数据的集中管理,提高数据的实用性,基于生产管理系统(PMS)建立了输变电设备红外图谱管理系统。该系统建立了统一的红外图谱采集、维护、存储规范,保证了数据的完整性和准确性,并实现管理部门与运维工区之间数据信息的快速共享,建立了红外图谱数据分析流程,根据设备分类、拍摄部位自动选择分析规则,快速诊断设备健康状态,为状态检修辅助决策系统提供数据支持。

一、二次设备状态监测信息融合及在PMS建设中的应用

针对现阶段部分地区二次设备状态监测系统独立于一次设备监测系统建设的情况,给出了一种兼顾PMS系统应用要求的一、二次设备状态监测信息融合的方案,包括工程应用模型构建、时钟同步、融合节点和检修策略等方面。将一次设备和监测组件作为独立的逻辑设备的高压设备监测信息建模可以满足监测组件自身状态诊断和远程维护的要求。将变电站继保装置、二次回路监测对象和作为监测组件的继保监测服务器作为独立的逻辑设备的二次设备监测模型可以方便地对应一台继保监测服务器监测多个保护装置及其回路的应用方式,并可根据继保装置等监测对象的不同进一步划分逻辑设备。该工程应用模型符合IEC 61850的层次结构。

Applying Geographic Information System (GIS) for Maintenance Strategy Selection

Spatial technologies, such as Geographic Information Systems (GIS), are particularly appropriate for integrating road- way data and enhancing the use and presentation of these data for highway management and operation by using spatial relationships to relate geographic and geometric objects and events. To different degrees, roadway management problems, such as pavement management, involve relations between objects and events located in different spatial positions. Because the data used in the decision-making process have spatial components, the use of spatial technologies emerges as a very appealing alternative. Spatial technologies may enhance the analysis of several transportation-related issues and may improve the quality of the decision-making process. This paper built a GIS based system that provides information for use as a platform on which all aspects of the Pavement Maintenance and Management System (PMMS) process can be built. The resulting system, GPMMS, represents a significant enhancement of all aspects of the PMMS process. A variety of spatially integrated data are important to pavement management decision making. GIS technology is shown to be the most logical way of relating these diverse, but relevant, data. In this paper, 23 sections is selected along the roadways of Nahrain University and all these sections are distresses due to different causes like weathering, ageing, traffic load, and also the bad maintenance, etc. The PSI of these sections in the range between 1 to 4, and most of these sections in the low range (between 1 to 2). That cause of need to future developments including other elements of a road maintenance management system should be considered. Completion of the whole roads database with all the types of surveys recorded i.e. all distresses, construction and maintenance history and so on.