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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Performance deterioration modeling and optimal preventive maintenance strategy under scheduled servicing subject to mission time

Servicing is applied periodically in practice with the aim of restoring the system state and prolonging the lifetime. It is generally seen as an imperfect maintenance action which has a chief influence on the maintenance strategy. In order to model the maintenance effect of servicing, this study analyzes the deterioration characteristics of system under scheduled servicing. And then the deterioration model is established from the failure mechanism by compound Poisson process. On the basis of the system damage value and failure mechanism, the failure rate refresh factor is proposed to describe the maintenance effect of servicing. A maintenance strategy is developed which combines the benefits of scheduled servicing and preventive maintenance. Then the optimization model is given to determine the optimal servicing period and preventive maintenance time, with an objective to minimize the system expected life-cycle cost per unit time and a constraint on system survival probability for the duration of mission time. Subject to mission time, it can control the ability of accomplishing the mission at any time so as to ensure the high dependability. An example of water pump rotor relating to scheduled servicing is introduced to illustrate the failure rate refresh factor and the proposed maintenance strategy. Compared with traditional methods, the numerical results show that the failure rate refresh factor can describe the maintenance effect of servicing more intuitively and objectively. It also demonstrates that this maintenance strategy can prolong the lifetime, reduce the total lifetime maintenance cost and guarantee the dependability of system.

Opportunistic Preventive Maintenance Optimization for Multi-Unit Series Systems with Combing Multi-Preventive Maintenance Techniques

This paper proposes a dynamic opportunistic preventive maintenance (PM) optimization policy for multi-unit series systems by integrating multi PM techniques. Two PM techniques, periodic PM and sequential PM, are considered. Whenever one of the units reaches its reliability threshold, a PM action has to be performed on that unit. At that time the whole system has to be stopped and PM opportunities arise for the other unitsof the system. An optimal PM practice is determined by maximizing the short-term cumulative opportunistic maintenance (OM) cost savings for the whole system. Numerical examples are given to show how this approach works. Finally, a comparison between the proposed PM policy and the other policies is given.

Single-machine scheduling with preventive periodic maintenance and resumable jobs in remanufacturing system

A single-machine scheduling with preventive periodic maintenance activities in a remanufacturing system including resumable and non-resumable jobs is studied.The objective is to find a schedule to minimize the makespan and an LPT-LS algorithm is proposed.Non-resumable jobs are first scheduled in a machine by the longest processing time（LPT） rule,and then resumable jobs are scheduled by the list scheduling（LS） rule.And the worst-case ratios of this algorithm in three different cases in terms of the value of the total processing time of the resumable jobs（denoted as S2） are discussed.When S2 is longer than the spare time of the machine after the non-resumable jobs are assigned by the LPT rule,it is equal to 1.When S2 falls in between the spare time of the machine by the LPT rule and the optimal schedule rule,it is less than 2.When S2 is less than the spare time of the machine by the optimal schedule rule,it is less than 2.Finally,numerical examples are presented for verification.

Periodic Preventive Maintenance Policy with Infinite Time and Limit of Reliability Based on Health Index

The aging of machine can be slowed and the life of machine can be increased by implementing periodic predictive maintenance. In this article,an improvement factor considering maintenance cost,age of machine and learning effect in the process of maintaining is constructed to describe the effect of periodic preventive maintenance. The model of improvement factor can be fitted through health index. Based on improvement factor with infinite time,cost function including preventive maintenance cost,minimal repair cost and replacement cost is explored. The unit cost and the optimized maintenance time interval based on limit of reliability are deduced. The process of optimization and an example are given.

Transient outage model considering corrective and preventive maintenance

Traditional outage model for the power equipment usually focus on the behavior of the equipment under random factors,and the availability of the power equipment in system analysis is usually confined to the steady value.However,this model may be inaccurate in the short term analysis,where the transient process of availability has not ended yet.Furthermore,the power equipment in the short term analysis might be influenced by both random factors and deterministic factors,yet the impact of deterministic factors cannot be completely reflected in the traditional outage model.Based on the above issues,a Markov-based transient outage model is proposed in this paper,which describes the deterioration and repair process of an equipment.Both the corrective maintenance and preventive maintenance are concerned in the model.The preventive maintenance in the model is considered as deterministic event,in which the start time and duration are both scheduled.Meanwhile the corrective maintenance and the unexpected failure are modeled as random events.The transient state probability and availability of equipment under preventive maintenance is derived.The effect of deterministic events on the availability of equipment is analyzed on numerical tests.The proposed model can be used in the short-term reliability assessment and maintenance scheduling in actual systems.

Optimal Burn-in and Preventive Maintenance Modeling with Competing Failure Processes

In this article, we assume that the product in the burn-in procedure only experiences continuous smooth degradation process, while in the field operation period the product experiences both continuous smooth degradation process and shock process. The shock process can cause the product not only traumatic failure,but also additional abrupt degradation damage. After the system reliability model and maintenance model have been proposed, the optimal burn-in setting and age replacement duration are obtained under the considering of minimizing the long run average cost rate. A numerical example with the real data is analyzed to illustrate the application of the model.