Reliability-BasedModel for Incomplete Preventive ReplacementMaintenance of Photovoltaic Power Systems

At present,the operation and maintenance of photovoltaic power generation systems mainly comprise regular maintenance,breakdown maintenance,and condition-based maintenance,which is very likely to lead to over-or under-repair of equipment.Therefore,a preventive maintenance and replacement strategy for PV power generation systems based on reliability as a constraint is proposed.First,a hybrid failure function with a decreasing service age factor and an increasing failure rate factor is introduced to describe the deterioration of PV power generation equipment,and the equipment is replaced when its reliability drops to the replacement threshold in the last cycle.Then,based on the reliability as a constraint,the average maintenance cost and availability of the equipment are considered,and the non-periodic incomplete maintenance model of the PV power generation system is established to obtain the optimal number of repairs,each maintenance cycle and the replacement cycle of the PV power generation system components.Next,the inverter of a PV power plant is used as a research object.The model in this paper is compared and analyzed with the equal cycle maintenance model without considering reliability and the maintenance model without considering the equipment replacement threshold,Through model comparison,when the optimal maintenance strategy is(0.80,4),the average maintenance cost of this paper’s model are decreased by 20.3%and 5.54%and the availability is increased by 0.2395% and 0.0337%,respectively,compared with the equal-cycle maintenance model without considering the reliability constraint and the maintenance model without considering the equipment replacement threshold.Therefore,this maintenance model can ensure the high reliability of PV plant operation while increasing the equipment availability to improve the system economy.

Joint Optimization of Imperfect Preventive Maintenance and Production Scheduling for Single Machine Based on Game Theory Method

In this study,an optimization model of a single machine system integrating imperfect preventive maintenance planning and production scheduling based on game theory is proposed.The costs of the production department and the maintenance department are minimized,respectively.Two kinds of three-stage dynamic game models and a backward induction method are proposed to determine the preventive maintenance(PM)threshold.A lemma is presented to obtain the exact solution.A comprehensive numerical study is provided to illustrate the proposed maintenance model.The effectiveness is also validated by comparison with other two existed optimization models.

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.

A preventive opportunistic maintenance method for railway traction power supply system based on equipment reliability

Conventional maintenance mode for the traction power supply system(TPSS)is to perform scheduled regular maintenance activities for power supply equipment,while such maintenance mode may result in undue maintenance tasks and low efficiency due to different degradation processes of different sorts of equipment.To address this problem,this paper introduces a preventive opportunistic maintenance(POM)method for TPSS based on equipment reliability.Firstly,a POM model is established by considering the equipment reliability degradation process based on Weibull distribution.Then,by considering the total power outage time in the planned operation cycle of TPSS as the optimization objective,the optimal maintenance scheme of TPSS is formulated by iterative method of maintenance strategies.The proposed method is verified by introducing practical maintenance strategies and fault record data of the traction transformer,circuit breaker and disconnector in an actual TPSS of a railway administration.Results show that the presented method can make full use of the existing fault data to develop a POM scheme for TPSS.It can improve maintenance efficiency and reduce power outage time,providing guidance to formulate scientific maintenance strategies for TPSS.

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products,providing customers with multiple maintenance options in the service contract becomes more popular,since it can help to improve customer satisfaction,and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance,totally three types of maintenance service contracts are designed.Moreover,attractive incentive and penalty mechanisms are adopted in the contracts.On this basis,Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers,and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation.Numerical experiments are conducted.The results show that by taking into account the incentive and penalty mechanisms,the revenue can be improved for both the customers and manufacturer.Moreover,with the increase of repair rate and improvement factor in the preventive maintenance,the revenue will increase gradually for both the parties.

Wind Turbine Optimal Preventive Maintenance Scheduling Using Fibonacci Search and Genetic Algorithm

Maintenance scheduling is essential and crucial for wind turbines (WTs) to avoid breakdowns andreduce maintenance costs. Many maintenance models have been developed for WTs’ maintenance planning, suchas corrective, preventive, and predictive maintenance. Due to communities’ dependence on WTs for electricityneeds, preventive maintenance is the most widely used method for maintenance scheduling. The downside tousing this approach is that preventive maintenance (PM) is often done in fixed intervals, which is inefficient. In thispaper, a more detailed maintenance plan for a 2 MW WT has been developed. The paper’s focus is to minimize aWT’s maintenance cost based on a WT’s reliability model. This study uses a two-layer optimization framework:Fibonacci and genetic algorithm. The first layer in the optimization method (Fibonacci) finds the optimal numberof PM required for the system. In the second layer, the optimal times for preventative maintenance and optimalcomponents to maintain have been determined to minimize maintenance costs. The Monte Carlo simulationestimates WT component failure times using their lifetime distributions from the reliability model. The estimatedfailure times are then used to determine the overall corrective and PM costs during the system’s lifetime. Finally,an optimal PM schedule is proposed for a 2 MW WT using the presented method. The method used in this papercan be expanded to a wind farm or similar engineering systems.

Product Modular Design Incorporating Preventive Maintenance Issues

Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.

Optimization Research on Two-Dimensional Preventive Maintenance Intervals

For the failures of two-dimensional product affected by the calendar time and usage time,traditional one-dimensional preventive maintenance can't meet the actual demand. Therefore,the concept of two-dimensional preventive maintenance innovatively is proposed,in order to make decision for two-dimensional product through calendar time and usage time. Firstly, failure rate function expression of two-dimensional product is established and the process of two-dimensional preventive maintenance is analyzed in detail.Then a model of two-dimensional preventive maintenance to minimize the consumer's cost per unit of time is proposed. And examples are given to analyze the model's applicability and validity.Furthermore,the optimal two-dimensional preventive maintenance interval is derived. Finally,a brief discussion on future research area about two-dimensional maintenance is given.

Application of cluster analysis to preventive maintenance scheme design of pavement

To quantitatively identify the maintenance demand for each highway segments in the pavement maintenance scheme design,a mathematical model of uniform segment division was established and an approach of applying cluster analysis theory to the uniform segment division and evaluation of pavement maintenance demand was proposed.The actual maintenance project of a highway carried out in Guangdong province was cited as an example to demonstrate the validity of the proposed method.It is proved that the cluster analysis can eliminate human factors in classification without being constrained by the quantities of samples,considering multiple pavement distress indexes and the continuity of samples.Thus it is evident that cluster analysis is an efficient analytical tool in uniform segment division and evaluation of maintenance demand.

Imperfect preventive maintenance for numerical control machine tools with log-linear virtual age process

Based on the log-linear virtual age process, an imperfect preventive maintenance policy for numerical control(NC)machine tools with random maintenance quality is proposed. The proposed model is a combination of the Kijima type virtual age model and the failure intensity adjustment model. Maintenance intervals of the proposed hybrid model are derived when the failure intensity increase factor and the restoration factor are both random variables with uniform distribution. The optimal maintenance policy in infinite time horizon is presented. A numerical example is given when the failures of NC machine tools are described by the log-linear process. Finally, a discussion is presented to show how the optimal results depend on the different cost parameters.

Research on Selection of Equipment Maintenance Modes

The development of equipment maintenance management is introduced, and equipment maintenance concept is defined. Equipment maintenance modes are classified, analyzed and compared, which merits and demerits are pointed out. At last, a decision-making frame to select equipment maintenance modes is advanced, and steps to select and implement equipment maintenance are given.

Warranty Cost Model Based on Optimal Preventive Maintenance Operations for Repairable Products

Most warranty cost models based on preventive maintenance operations are assumed that products improve at each preventive maintenance(PM)operation and the failure rate is reduced to the failure rate of new products or to some specified level.To make warranty cost models more suitable to real operations,a modeling method of the PM warranty cost was proposed with the situation where each PM operation slowed the rate of product degradation.A warranty cost model was built on PM operations.On the basis of the cost model,both without and with reliability limit PM warranty policy,algorithms were presented to derive the optimal PM number and the optimal PM interval with an objective of minimizing expected total warranty cost over a finite warranty period.Finally,to demonstrate the feasibility of the presented modeling method,Weibull distribution cases were tested by numerical simulations.The simulation results indicate that the proposed modeling method is feasible and valid for resolving the optimal solution of the product warranty cost.

Modeling preventive maintenance using subjective data

Presents the optimal preventive maintenance model established with the target function given through technical economic analysis, and failure rate and delay time distribution estimated from subjective data, which describes the relationship between the total downtime and the preventive maintenance and can be used to determine the rational inspection interval and to minimize the total expected downtime per unit time.

A Study of Implementation of Preventive Maintenance Programme in Nigeria Power Industry – Egbin Thermal Power Plant, Case Study

Preventive Maintenance Programme consists of actions that improve the condition of system elements for performance optimization and aversion of unintended system failure or collapse. It involves inspection, servicing, repairing or replacing physical components of machineries, plant and equipment by following the prescribed schedule. It is commonly agreed nowadays that preventive maintenance programme can be very successful in improving equipment reliability while minimizing maintenance related costs. The availability of a complex system, such as steam turbine power plant is strongly associated with its parts reliability and maintenance policy. That policy not only has influence on the parts’ repair time but also on the parts’ reliability affecting the system integrity, degradation and availability. The objective of this paper is to study the effects of Preventive Maintenance Programme (PMP) implementation on the performance of the Egbin 1320 MW thermal power plant in Nigeria. This paper considers the reliability and availability of the 6 x 220 MW steam turbine units installed in the power station. The reliability and availability of the turbines are computed based on a five-year failure database. The availability analysis of available data from 2005 to 2009 shows different results for each unit and variation in availability for different year: availability of unit1 varies between 59.11 to 91.76%;unit 2, 64.02 to 94.53%;unit 3, 28.79 to 91.57%;unit 4, 80.31 to 92.76% and unit 5, 73.38 to 87.76%. Unit 6 was out of service for the past 2 to 3 years. This indicates differences in their systems installation maintenance and operation.

Preventive Maintenance Characteristics towards Optimal Maintenance Performance: A Case Study of Office Buildings

Lack of preventive measure is currently the problem that implicates poor building maintenance performance and issue on sustainability of buildings in Malaysia. Whereby, preventive maintenance is an effective approach to enhance the reliability and quality of a system and its components. This study seeks to investigate the characteristics of preventive maintenance towards the overall performance in building maintenance. Case study approach is adopted to identify the maintenance characteristics and aspects that lead to good performance. The research findings demonstrate that the most significant maintenance characteristics towards overall performance are skill and knowledge of maintenance labour, quality of spare parts and materials, length of predetermined maintenance interval, skill and knowledge of maintenance manager, capability to adopt maintenance equipment and technique, budget allocation for acquisition of maintenance data, reliability of maintenance data, as well as frequency of monitoring and inspection. As a conclusion, the significant maintenance characteristics must be taken into consideration to achieve optimal maintenance performance. In order to improve the effectiveness of maintenance strategy and the maintenance performance, the study recommends practice and provision of communication platform such as meeting and customer satisfaction survey that involves all the key participants from clients to customers.

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.

Application of Stochastic Optimization to Optimal Preventive Maintenance Problem

The contribution deals with the optimization of a sequential preventive maintenance schedule of a technical device. We are given an initial time-to-failure probability distribution, model of changes of this distribution after maintenance actions, as well as the costs of maintenance, of a device acquisition, and of the impact of failure. The maintenance timing and, eventually, its extent, are the matter of optimization. The objective of the contribution is two-fold: first, to formulate a proper (random) objective function evaluating the lifetime of the maintained device relatively to maintenance costs;second, to propose a numerical method searching for a maintenance policy optimizing selected characteristics of this objective function. The method is based on the MCMC random search combined with simulated annealing. It is also shown that such a method is rather universal for different problem specifications. The approach will be illustrated on an artificial example dealing with accelerated lifetime after each maintenance action.

Determination of Preventive Maintenance Intervals for Items

A quick and valid method to determine preventive maintenance intervals is introduced in this paper.It applies the theory established by Barlow R.E.and Proschan F.in 1975,and It is based on the operation of actual age-to-failure data and cost data for items to determine the optimum preventive maintenance interval by the technique of computer digital simulation on reliability.In comparison with the traditional methods,such as age-exploration,it can improve the rate of utilization and reduce the maintenance cost of the items.A longer period is needed to determine the maintenance interval by the traditional methods,while by the method introduced here it may shorten the time for the operational state to determine the maintenance interval.We can timely calibrate the interval by the computer in accordance with the statistics,and the application may be easily spreaded to the field of maintenance base.

The Optimization of Preventive Maintenance Scheduling for Production Machine of Production System in Finite Time Horizon

The recursion relation of preventive maintenance (PM) cycle is built up concerning the concept of effective age and age setback factor proposed in this paper, which illustrates the dynamic relationship between failure rate and preventive maintenance activity. And the nonlinear optimal PM policy model satisfying the reliability constraints in finite time horizon following Weibull distribution is proposed. The model built in this paper avoids the shortcoming of steady analytical PM model in infinite time horizon and can be used to aid scheduling the maintenance plan and providing decision supporting for job shop scheduling.

Maintenance Optimization for EMU Trains Considering Environmental Impacts and Correlations

The complexity of the actual operating environment of EMU trains and the interaction between the reliability of system components have become a huge challenge for the maintenance scheduling of EMU trains. In response to these problems, the evolution of reliability and failure rate under the influence of environmental factors, failure correlations and economy correlations is analyzed. We assume bogie systems form the EMU train in series. The failure correlation matrix of the bogie systems is modeled. With the lowest total maintenance cost as the optimization objective, a decision-making model for EMU train maintenance is established. A dynamic maintenance strategy is proposed for the model, which can improve maintenance plans efficiently. Artificial bee colony algorithm is applied to further iteratively optimize the threshold parameters in the strategy. The results are calculated and verified by a numerical example. The results show the effectiveness of the maintenance decision model. The dynamic maintenance strategy in this paper is compared with the traditional opportunistic maintenance strategy. The proposed maintenance strategy outperforms the traditional opportunistic maintenance strategy in the numerical example.