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.

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.

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.

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.

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.

Benefits of Dielectric Oil Regeneration Systems in Power Transmission Networks: A Case Study

The criticality of transformers and reactors in the power transmission network and the paramount importance of ensuring their reliability through maintenance of the insulating oil is known. This paper presents a comprehensive examination of the efficacy and economic viability of a dielectric oil regeneration system, as implemented by the Transmission System Maintenance Department (TSMD) of the Independent Power Transmission Operator (IPTO), Greece’s sole transmission operator. Through a detailed chemical analysis and performance evaluation, we assess the impact of the regeneration system on treated insulating oil quality over multiple cycles. The study reveals that the electrical properties of the insulating oil are fully restored after regeneration, negating the need to fully replace it, while the investment becomes cost-neutral within weeks from the commissioning of the regeneration system. This economic analysis, coupled with the system’s environmental benefits of reducing waste oil generation, positions the dielectric oil regeneration system as a compelling solution for the maintenance of power transmission assets.

On Problems of Multicomponent System Maintenance Modelling

We present an overview of some recent developments in the area of mathematical modeling of maintenance decisions for multi-unit systems. The emphasis is on three main groups of multicomponent maintenance optimization models： the block replacement models, group maintenance models, and opportunistic maintenance models. Moreover, an example of a two-unit system maintenance process is provided in order to compare various maintenance policies.

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.

A dynamic condition-based maintenance optimization model for mission-oriented system based on inverse Gaussian degradation process

An effective maintenance policy optimization model can reduce maintenance cost and system operation risk. For mission-oriented systems, the degradation process changes dynamically and is monotonous and irreversible. Meanwhile, the risk of early failure is high. Therefore, this paper proposes a dynamic condition-based maintenance(CBM) optimization model for mission-oriented system based on inverse Gaussian(IG) degradation process. Firstly, the IG process with random drift coefficient is used to describe the degradation process and the relevant probability distributions are obtained. Secondly, the dynamic preventive maintenance threshold(DPMT) function is used to control the early failure risk of the mission-oriented system, and the influence of imperfect preventive maintenance(PM)on the degradation amount and degradation rate is analysed comprehensively. Thirdly, according to the mission availability requirement, the probability formulas of different types of renewal policies are obtained, and the CBM optimization model is constructed. Finally, a numerical example is presented to verify the proposed model. The comparison with the fixed PM threshold model and the sensitivity analysis show the effectiveness and application value of the optimization model.

Optimal Extended Warranty Policies under Different Maintenance Options

Extended warranty has recently obtained increasing attention from both manufacturers and customers in China. In this paper,given the reality of China, two types of non-renewing extended warranty were proposed: one-dimensional extended warranty and two-dimensional extended warranty. And a combined warranty policy including pro-rata warranty policy and free-repair warranty policy was applied in these two types of warranty. Then the expected life-cycle cost models from the manufacturer and consumer's perspectives were developed considering different maintenance options. The optimal warranty policy, maintenance options,and warranty price were adopted in terms of a win-win interval which was determined by the maximum extra cost the consumer should pay and the minimum price the manufacture should sell at the extended warranty. Finally,a case study was given to prove the effectiveness and validity of the model.

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.

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.

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.

Recent Advances in Selective Maintenance from 1998 to 2014

The selective maintenance is a new branch and significant breakthrough of reliability and maintenance theory.In the original selective maintenance problem,a subset of maintenance activities is performed on selected components during the finite break so that the system is able to maximize the next mission reliability.It is a fast growing research field over the past ten years,in which a variety of mathematical models and solution methodology have been proposed for dealing with more complex and significant problems.An overview of some recent advances in selective maintenance modeling and treatment methods is provided in this paper.A number of challenges that can be undertaken to help move the field forward are also discussed according to the current state of the selective maintenance approach.

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.

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.

Deformation-based support design for highly stressed ground with a focus on rockburst damage mitigation

As mines go deeper,mine designs become more fragile and effective rock support becomes a strategic element for ground control to facilitate timely construction and cost-effective access for uninterrupted production.This article focuses on the design of integrated support systems for brittle ground when large displacements due to gradual bulking of stress-fractured rock or sudden violent bulking during rockbursts are induced by static and dynamic loading.It provides an overview of support design principles for a rational approach to ground control in deep mines when large deformations are anticipated near excavations.Such designs must not only account for load equilibrium but also for deformation compatibility.Most importantly,the design approach must account for the fact that the support’s displacement capacity is being consumed as it is deformed after support installation.It is therefore necessary to design for the remnant support capacity,i.e.the capacity remaining when the support is needed.Furthermore,if the support capacity can be consumed,it can also be restored by means of preventive support maintenance(PSM).The PSM concept for cost-effective ground control is introduced and illustrated by quantitative and operational evidence.Contrary to other design approaches,the deformation-based support design(DBSD)approach provides the capacity of an integrated support system as a function of imposed displacements.Reduction in this support capacity due to mininginduced deformation renders excavations increasingly more vulnerable if located within the influence of active mining and seismic activity.Because deformation measurements are robust indicators of the decay in support capacity,scanning and other displacement monitoring technologies enable measurements to verify the DBSD approach,to assess the remnant safety margin of the deformed support,and to make operational support maintenance decisions.