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.

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.

An estimation method for direct maintenance cost of aircraft components based on particle swarm optimization with immunity algorithm

A particle swarm optimization (PSO) algorithm improved by immunity algorithm (IA) was presented. Memory and self-regulation mechanisms of IA were used to avoid PSO plunging into local optima. Vaccination and immune selection mechanisms were used to prevent the undulate phenomenon during the evolutionary process. The algorithm was introduced through an application in the direct maintenance cost (DMC) estimation of aircraft components. Experiments results show that the algorithm can compute simply and run quickly. It resolves the combinatorial optimization problem of component DMC estimation with simple and available parameters. And it has higher accuracy than individual methods, such as PLS, BP and v-SVM, and also has better performance than other combined methods, such as basic PSO and BP neural network.

Real-world cost-effectiveness associated with infliximab maintenance therapy for moderate to severe Crohn's disease in China

BACKGROUND Infliximab was the first approved biologic treatment for moderate to severe Crohn's disease(MS-CD) in China. However, the cost-effectiveness of infliximab maintenance therapy(IMT) for MS-CD relative to conventional maintenance therapy remained unclarified.AIM To assess the cost-effectiveness of IMT for MS-CD in Chinese patients from the perspective of Chinese public insurance payer.METHODS A cohort of MS-CD patients managed in a Chinese tertiary care hospital was created to compare IMT with conventional maintenance therapy(CMT) for clinical outcomes and direct medical costs over a 1-year observation time using conventional regression analyses. A decision-analytic model with the generated evidence was constructed to assess the cost-effectiveness of IMT relative to CMT using reimbursed medical costs.RESULTS Based on the included 389 patients, IMT was associated with significantly higher disease remission chance [odds ratio: 4.060, P = 0.003], lower risk of developing new complications(odds ratio: 0.527, P = 0.010), higher utility value for quality of life(coefficient 0.822, P = 0.008), and lower total hospital costs related to disease management(coefficient-0.378, P = 0.008) than CMT. Base-case cost-effectiveness analysis estimated that IMT could cost Chinese health insurance payers $55260 to gain one quality-adjusted life year(QALY). The cost-effectiveness of IMT was mainly driven by the estimate of quality of life, treatment efficacy of maintenance therapy, mortality risk associated with active disease, and unit price of infliximab. The probability that IMT was cost-effective at a willingness-to-pay threshold of three times gross domestic product [2018 Chinese gross domestic product per capita(GDPPC)] was 86.4%.CONCLUSION IMT significantly improved real-world health outcomes and cost the Chinese public health insurance payers less than one GDPPC to gain one QALY in Chinese MS-CD patients.

Statistical approach to determination of overhaul and maintenance cost of loading equipment in surface mining

The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.

On the Relationship between Software Complexity and Maintenance Costs

As software becomes more and more complex due to increased number of module size, procedure size, and branching complexity, software maintenance costs are often on the increase. Consider a software such as Windows 2000 operating systems with over 29 million lines of code (LOC), 480,000 pages if printed, a stack of paper 161 feet high, estimate of 63,000 bugs in the software when it was first released [1] and with over 1000 developers, there is no doubt that such a large and complex software will require large amount of money (in US Dollars), social and environmental factors to maintain it. It has been estimated that over 70% of the total costs of software development process is expended on maintenance after the software has been delivered. This paper studies the relationship between software complexity and maintenance cost, the factors responsible for software complexity and why maintenance costs increase with software complexity. Some data collected on Windows, Debian Linux, and Linux Kernel operating systems were used. The results of our findings show that there is a strong correlation between software complexity and maintenance costs. That is, as lines of code increase, the software becomes more complex and more bugs may be introduced, and hence the cost of maintaining software increases.

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 t＇mite warranty period. Finally, to demonstrate the feasibility of the presented modeling method, Weibuil 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.

Multicomponent opportunistic maintenance model based on cost-effectiveness

With difficulties in maintaining multicomponent systems of wind turbines and formulating economical and reasonable maintenance strategies,a dynamic opportunistic maintenance strategy of multicomponent systems is applied in terms of economic relevance and opportunistic maintenance among various components.A preventive maintenance model based on cost-effectiveness is proposed by incorporating cost-effectiveness analysis into the multicomponent preventive maintenance strategy.The failure rate recovery degree is used to describe the effects of imperfect maintenance and replacement.When the reliability of the component reaches the threshold of preventive or opportunistic maintenance,a reasonable maintenance method is selected on the basis of the cost-effectiveness ratio of the failure rate.A case study is conducted by taking four components of a wind turbine as the research object and comparing them with the opportunistic maintenance model without considering cost-effectiveness.Results show that the total maintenance cost is reduced by 373600 yuan,indicating that the preventive opportunistic maintenance based on cost-effectiveness is more economical and can provide a theoretical basis for formulating a preventive maintenance plan.

Component reallocation and system replacement maintenance based on availability and cost in series systems

Component reallocation(CR)is receiving increasing attention in many engineering systems with functionally interchangeable and unbalanced degradation components.This paper studies a CR and system replacement maintenance policy of series repairable systems,which undergoes minimal repairs for each emergency failure of components,and considers constant downtime and cost of minimal repair,CR and system replacement.Two binary mixed integer nonlinear programming models are respectively established to determine the assignment of CR,and the uptime right before CR and system replacement with the objective of minimizing the system average maintenance cost and maximizing the system availability.Further,we derive the optimal uptime right before system replacement with maximization of the system availability,and then give the relationship between the system availability and the component failure rate.Finally,numerical examples show that the CR and system replacement maintenance policy can effectively reduce the system average maintenance cost and improve the system availability,and further give the sensitivity analysis and insights of the CR and system replacement maintenance policy.

Comparison of Economic Life of Tractors in Iran Using Condition Monitoring （CM） and Breakdown Maintenance （BM） Methods

Repair and maintenance costs are the most important factors affecting decision making about substituting agricultural machineries. This decision is made based on the economic life （time） of machineries. In this research, condition monitoring of MF285 and MF399 tractors was performed using engine oil analysis to find the optimum life time of tractor substitution in comparison with the breakdown maintenance method in Iran. All recorded information about fixed and variable costs were selected as data base and analyzed. Data were divided （classified） based on period of annual working time. Using power regression analysis led to find mathematical models for the optimum time life definition. Cumulative working time （X） was selected as independent and cumulative costs based on definite percent of initial price （Y） was considered as dependent variable and a power law equation was found to express the costs of both MF399 and MF285 tractors as a function of working time. Results showed that in CM method, average of economic life was 13 and 11 years for MF399 and MF285, respectively. It was also found that in BM method, economic life wasl0 and 8.5 years for MF399 and MF285, respectively.

Prediction of Repair and Maintenance Costs of Two-wheel Drive Tractors in Iran

Predicting of repair and maintenance （R＆M） costs of tractors in any mechanized farm is necessary for owners and managers to obtain information on overall costs and to control financial balance and production economy. In this context a study was conducted to predict accumulated R＆M costs （Y） of two-wheel drive （2WD） tractors based on accumulated usage hours （X） in Misagh-e-Sabz Agribusiness Company in Iran. Recorded data of the company were used to determine regression models for predicting accumulated R＆M costs （as percentage of initial purchase price） based on accumulated usage hours. The statistical results of the study indicated that in order to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or less the power regression model Y=0.013 （X/100）1.677 with R2=0.976, and to predict accumulated R＆M costs of 2WD tractors with accumulated usage hours of 2260 h or more the polynomial regression model Y=0.004 （X/100）2-0.181 （X/1 00）＋4.373 with R2=0.998 can be strongly suggested.

Evaluating and Improving the Effectiveness of Vehicle Inspection and Maintenance Programs: A Cost-Benefit Analysis Framework

Motor vehicle inspection and maintenance (I/M) programs are designed to identify high-emitting vehicles and mitigate their impacts on air quality and climate. I/M programs have been traditionally ranked superior among various vehicle emission control measures by the results of cost-benefit analysis, based on the assumption that these programs will achieve the targeted emission reduction outcomes. However, the actual effects of I/M programs may be greatly uncertain and when this uncertainty is taken into account, these programs may become suboptimal. This study develops a new a cost-benefit analysis framework that links various program design consideration, such as program participation rate, identification rate and effective repair rate, to the public health benefits as well as costs of the programs. This framework helps decision makers to investigate minimum implementation requirements that at least ensure the benefits are greater than the costs of implementing the programs in order to improve the overall effectiveness of the I/M programs. To illustrate the applications of the framework, it was applied to a particulate matter oriented I/M program targeting all diesel-fueled vehicles in the city of Bangkok, Thailand, a large metropolitan area that has been suffering from severe ambient PM pollution mainly attributable to its wide use of diesel-fueled vehicles and motorcycles. It was found that the health benefits achieved from the program are sensitive to several key program design elements, including participation rate and problem vehicle identification rate, fraction of effective repairs and illegal operation rate. Other variables, such as the testing cut-points and vehicle population growth rate, only have modest effects on the overall emission reduction and consequent health benefits. Overall, the performance of multiple variables associated with I/M program design needs to be improved simultaneous in order to achieve the targeted benefits of the program.

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs

With the large-scale integration of renewable energy,the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy generation.Simultaneously,in a market-oriented operation mode,the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power system.Therefore,a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed herein.This model is built on double-layer optimization framework,where the upper-layer model is used for maintenance and generation planning,and the lowerlayer model is primarily used to address the operational security risk arising from the random prediction error and N-1 transmission failure.Correspondingly,a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution efficiency.Generation cost is determined using long-term security-constrained unit commitment,and the operational risk cost is obtained using a double-layer N-1 risk assessment model.An electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously,thereby improving model convergence efficiency.The IEEE 118-bus system is used as a test case for illustration,and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.

Reliability-based Maintenance Optimization under Imperfect Predictive Maintenance

The reliability-based maintenance optimization model has been focused by the engineers and scholars but it has never been solved effectively to formulate the effect of a maintenance action on the optimization model. In existing works, the system reliability was assumed to be increased to 1 after a predictive maintenance. However, it is very difficult in the most practical systems. Therefore, a new reliability-based maintenance optimization model under imperfect predictive maintenance (PM) is proposed in this paper. In the model, the system reliability is only restored to R i (0<R i <1, i∈N, N is natural number set) after the ith PM. The system uptimes and the corresponding probability in two cases whether there is an unexpected fault in one cycle are derived respectively and the system expected uptime model is given. To formulate the system expected downtime, the probability of each imperfect PM number in one cycle is calculated. Then, the system expected total time model is obtained. The total expected long-term operation cost is composed of the expected maintenance cost, the expected loss due to the downtime and the expected additional cost due to the occurrence of an unexpected failure. They are modeled respectively in this work. Jointing the system expected total time and long-term operation cost in one cycle, the expected long-term operation cost per time could be computed. Then, the proposed maintenance optimization model is formulated where the objective function is to minimize the expected long-term operation cost per time. The results of numerical example show that the proposed model could scheme the optimal maintenance actions for the considered system when the required parameters are given and the optimal solution of the proposed model is sensitive to the parameters of effective age model and insensitive to other parameters. The proposed model effectively solves the problem of evaluating the effect of an imperfect PM on the system reliability and presents a more practical optimization method for the reliability-based maintenance strategy than the existing works.

Opportunistic maintenance for multi-component systems considering structural dependence and economic dependence

Although opportunistic maintenance strategies are widely used for multi-component systems, all opportunistic mainte- nance strategies only consider economic dependence and do not take structural dependence into account. An opportunistic main- tenance strategy is presented for a multi-component system that considers both structural dependence and economic dependence. The cost relation and time relation among components based on structural dependence are developed. The maintenance strategy for each component of a multi-component system involves one of five maintenance actions, namely, no-maintenance, a minimal maintenance action, an imperfect maintenance action, a perfect maintenance action, and a replacement action. The maintenance action is determined by the virtual age of the component, the life expectancy of the component, and the age threshold values. Monte Carlo simulation is designed to obtain the optimal oppor- tunistic maintenance strategy of the system over its lifetime. The simulation result reveals that the minimum maintenance cost with a strategy that considers structural dependence is less than that with a strategy that does not consider structural dependence. The availability with a strategy that considers structural dependence is greater than that with a strategy that does not consider structural dependence under the same conditions.

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.

Application of reliability-centered maintenance for productivity improvement of open pit mining equipment:Case study of Sungun Copper Mine

Equipment plays an important role in open pit mining industry and its cost competence at efficient operation and maintenance techniques centered on reliability can lead to significant cost reduction.The application of optimal maintenance process was investigated for minimizing the equipment breakdowns and downtimes in Sungun Copper Mine.It results in the improved efficiency and productivity of the equipment and lowered expenses as well as the increased profit margin.The field operating data of 10 trucks are used to estimate the failure and maintenance profile for each component,and modeling and simulation are accomplished by using reliability block diagram method.Trend analysis was then conducted to select proper probabilistic model for maintenance profile.Then reliability of the system was evaluated and importance of each component was computed by weighted importance measure method.This analysis led to identify the items with critical impact on availability of overall equipment in order to prioritize improvement decisions.Later,the availability of trucks was evaluated using Monte Carlo simulation and it is revealed that the uptime of the trucks is around 11000 h at 12000 operation hours.Finally,uncertainty analysis was performed to account for the uncertainty sources in data and models.

A Fuzzy Logic-Based Modeling Method of Deciding Maintenance Policies

To make equipment maintenance policies more suitable to real operations, a fuzzy logic-based modeling method of deciding maintenance policies was proposed in this paper. Five maintenance policies which are built with downtime and breakdown frequency as decision criteria are discussed. To decide efficiently maintenance policies, the decision criteria are divided into low, medium, and high levels. On the basis of the levels, fuzzy sets and membership functions of the decision criteria are established with a fuzzy logic theory. A fuzzy logic algorithm of solving overall degree of satisfaction is presented to select the most efficient maintenance policy for equipment. Finally, the modeling method is tested. Experiment results show that the proposed method can solve efficiently problems of the traditional decision-making bias, and it is more valid and practical than the method of traditional decision-making grid (DMG).

Energy Systems Maintenance

The subject of maintenance is of much importance in the implementation of projects in today’s industries. Maintenance is carried on energy systems to keep their performance within acceptable standards and to maintain their average life expectancy. The cost associated with maintenance work is largely dependent on how often maintenance routines are carried out and the extent the work are done. Current maintenance work are usually carried out in accordance with the equipment manufacturer’s guide line and modified by experts as maintenance experience is gained. This paper discusses the various maintenance schemes and the impact of maintenance on the life cycle costs of a system.