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.

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.

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.

Impact of Safety-Maintenance Practices on the Overall Performance of an Industry

The study aims to evaluate how safety-maintenance practices affect the mechanical engineering industry’s overall performance in Ghana. The study used a descriptive survey design technique to ascertain the type of maintenance engineering that was practiced in Ghanaian mechanical engineering workshops at the time of the study. In the mechanical engineering workshops, respondents provided both qualitative and quantitative data using a variety of data collecting instruments, with the quantitative approach being more common. The study employed Kumasi, Tamale, and Accra’s mechanical engineering workshops as a case study. The number of mechanical engineering workshop enterprises that made up the sample size for the questionnaire administration was sixty (60), chosen at random from the AGI membership registry. Primary data was gathered using interview guides and questionnaires. To analyse the data, descriptive statistics were employed. According to the study’s findings, mechanical engineering companies combined different maintenance techniques in order to best fit their organisational culture and equipment. Preventive shut-down, with a mean score of 4.78 and RII = 0.98, placing first (1st) in the Likert rating order, is the most frequently used maintenance system by respondents. The maintenance procedures employed by mechanical engineering organisations were influenced not only by their equipment and organisational culture but also by other factors such as cost, personnel expertise and external partnerships.

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.

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.

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.

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 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 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.

A New Method to Optimize the Maintenance Strategy of HVDC Transmission System

A method based on fuzzy comprehensive evaluation to optimize the maintenance strategy of HVDC transmission system is proposed to provide quantitative reference for the maintenance arrangements. Firstly, a system based on fuzzy comprehensive evaluation, is established to fuzzy the index results of power system adequacy evaluation, so as to analysis the degree of risk in the operation of power system and the effect brought by the maintenance of HVDC. Then, the proposal on the maintenance of HVDC can be formed through the quantization and evaluation summary of the fuzzy results. The equivalent network of the China Southern Power Grid in 2011 ,which respectively operates in the circumstances of peak load, general load and low load, demonstrates the HVDC transmission systems in different operation modes have corresponding Overhaul timing .The result shows that the method proposed is valid and in accordance with engineering practice.

Evaluation of Maintenance Strategies Based on Leakage Risk Assessment on Side Impervious Walls at Coastal Landfill Sites

Asset management is a strategic decision-making aspect of social infra-structure that ensures safety by predicting long-term conditions and maximizing effectiveness under budgetary constraints. Predicting the deterioration of impervious walls is essential in the asset management of coastal landfill sites, particularly in the design of their maintenance and repair strategy. In this paper, a quantitative evaluation of the leakage of toxic substances in coastal landfill sites where deterioration of side impervious walls has decreased the water interception performance is reported. In addition, risk evaluation based on the asset management of the leakage is applied to determine an appropriate repair method. The strategy of repairing the walls when the concentration of the toxic substances leaking into the sea area exceeds the closure and abandonment of coastal landfill sites is demonstrated to be superior. Moreover, the strategy of repairing only the seaside side impervious wall is shown to be cost-effective.

Optimization of Equipment Maintenance Strategy Based on Availability

It is very important to optimize maintenance strategy in maintenance plan. Proper parameters play a decisive role for the optimization. In the opinion of writer, availability is a basic parameter, failure consequence cost and failure characteristic are also important parameters. Maintenance strategy can be optimized on the base by means of quantitative analysis and diagram.

Maintenance Strategies and Spare Parts Inventory Management for Use of Reconditioned Items

The maintenance management of construction equipment occupies a prominent place in the overall strategy for managing the equipment fleet. It is also linked to the management of the stock of spare parts and particularly reconditioned spare parts. Because of the relatively low purchase cost of these, most companies are tempted by this option. The purpose of this article is precisely to study the impact of this category of parts in the stock and also in the optimization of maintenance costs, knowing that to do this;their use must obey certain constraints. It is therefore important to be able to characterize these reconditioned parts by estimating their optimal age, and studying their advantages and also their limits. The determination of the optimal age of reconditioned parts will be such that the total cost of replacement with used parts is at most equal to the total cost of replacement with new parts at the end of the operating period.