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 METHODS FOR CIVIL AEROENGINE

To provide some feasible condition-based maintenance （CBM） decision making methods for civil aeroengine, firstly, the theory of aeroengine CBM decision making is described. The proportional intensity（PI） model is established based on the reliability and condition monitoring data. According to the model, the decision making methods are proposed for the optimal preventive maintenance（PM） interval and removal. Then, the time on wing （TOW） is predicted by collecting actual data based on the engine age and operating conditions. Finally, an example of a fleet for CF6-80C2 engines is illustrated. It shows that sufficient engine operation data are the key of accurate decision making. Results indicate that the CBM decision making methods are helpful for engineers in airlines to control engine maintenance actions and TOW, thus decreasing risks and maintenance costs.

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.

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.

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.

Review of Condition-Based Maintenance Strategies for Offshore Wind Energy

The existing maintenance strategies of offshore wind energy are reviewed including the specific aspects of condition-based maintenance, focusing on three primary phases, namely, condition monitoring, fault diagnosis and prognosis, and maintenance optimization. Relevant academic research and industrial applications are identified and summarized. The state of art, capabilities,and constraints of condition-based maintenance are analyzed. The presented research demonstrates that the intelligent-based approach has become a promising solution for condition recognition, and an integrated data platform for offshore wind farms is significant to optimize the maintenance activities.

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.

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.

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 the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance

Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.

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.

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.

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.

基于CBM的共用信息系统装备维修保障体系分析与架构设计

随着信息化和数字化技术的不断发展,企业和组织之间信息共享和协作的迫切需求驱使着共用信息系统的产生。企业和组织可以通过共用信息系统装备实现资源的共享和互通,避免信息孤岛和资源浪费,提高信息协同和决策效率。然而环境、人为等因素会导致共用信息系统装备出现故障,使系统无法正常工作。虽然已有相应的装备维修体系,但针对共用信息系统的装备维修方法落后,架构老旧且维修可扩展性低。为解决该问题,以基于状态的维修理论(CBM)为基石,结合模糊理论、灰色模型以及现有共用信息系统维修体系,分析基于CBM的共用信息系统维修保障体系所需功能和流程,构建基于CBM的全新共用信息系统装备维修架构。所提出架构优化了传统装备维修保障模式,为维修管理工作提供了科学的参考依据。

SOMS: A Subway Operation and Maintenance System Based on Planned Maintenance Model with Train State

This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function modules, and the research problem is to determine one auxiliary maintains plan, including the time allocation and frequency of maintenance. The case of Guangzhou metro is conducted to illustrate the applicability of SOMS, and the results reveal a number of interesting insights into subway maintenance system, i.e., the worksheet can reduce duplication of redundant maintenance work, the repair cost, and the damage caused by frequent disassembly.

Optimal Maintenance Modeling for Systems with Multiple Non-Identical Units Using Extended DSSP Method

In the optimal maintenance modeling, all possible maintenance activities and their corresponding probabilities play a key role in modeling. For a system with multiple non-identical units, its maintenance requirements are very complicated, and it is time-consuming, even omission may occur when enumerating them with various combinations of units and even with different maintenance actions for them. Deterioration state space partition (DSSP) method is an efficient approach to analyze all possible maintenance requirements at each maintenance decision point and deduce their corresponding probabilities for maintenance modeling of multi-unit systems. In this paper, an extended DSSP method is developed for systems with multiple non-identical units considering opportunistic, preventive and corrective maintenance activities for each unit. In this method, different maintenance types are distinguished in each maintenance requirement. A new representation of the possible maintenance requirements and their corresponding probabilities is derived according to the partition results based on the joint probability density function of the maintained system deterioration state. Furthermore, focusing on a two-unit system with a non-periodical inspected condition-based opportunistic preventive-maintenance strategy;a long-term average cost model is established using the proposed method to determine its optimal maintenance parameters jointly, in which “hard failure” and non-negligible maintenance time are considered. Numerical experiments indicate that the extended DSSP method is valid for opportunistic maintenance modeling of multi-unit systems.

CBM标准化研究现状及发展趋势

基于状态的维护(CBM)是一种新的设备维护模式,建立CBM方式的设备维护系统是一个复杂的系统工程,为规范相关软硬件产品的研制开发、提高不同厂商产品的可互换性与可互操作性,IEEE、ISO、OSA-CBM、MIMOSA等组织相继制定了一些标准,对CBM技术的发展起到了很好的促进作用。本文介绍了国际上CBM标准化研究的现状及相关成果,分析了CBM标准化研究的发展趋势,介绍了作者在CBM研究方面的成果,并对我国CBM标准化研究工作提出了建议。

军队装备维修工程CBM综述

军队维修体制从传统的定期维修、预防性维修向以可靠性维修（reliability centered maintenance，RCM）为指导的状态维修（condition based maintenance，CBM）和设备健康状态管理（equipment health management，EHM）方式过渡，是军队维修工程信息化、智能化管理进程中的必经之路。介绍了状态维修的基本概念及层次结构，对其国内外应用现状及主要应用价值进行了分析，阐述了CBM在我军维修工程中的实施对策及对三级维修体制的影响。