scholarly journals Optimal Condition-Based Maintenance Strategy for Multi-Component Systems under Degradation Failures

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4346
Author(s):  
Kui Wang ◽  
Chao Deng ◽  
Lili Ding

This paper proposes a condition-based maintenance strategy for multi-component systems under degradation failures. The maintenance decision is based on the minimum long-run average cost rate (LACR) and the maximum residual useful lifetime (RUL), respectively. The aim of this paper is to determine the optimal monitoring interval and critical level for multi-component systems under different optimization objectives. A preventive maintenance (PM) is triggered when the degradation of component exceeds the corresponding critical level. Afterwards, the paper discusses the relationship between the critical level and the monitoring interval with regards to the LACR and RUL. Methods are also proposed to determine the optimal monitoring interval and the critical level under two decision models. Finally, the impact of maintenance decision variables on the LACR and RUL is discussed through a case study. A comparison with conventional maintenance policy shows an outstanding performance of the new model.

2015 ◽  
Vol 52 (2) ◽  
pp. 558-573 ◽  
Author(s):  
Ji Hwan Cha ◽  
Inma T. Castro

In this paper a stochastic failure model for a system with stochastically dependent competing failures is analyzed. The system is subject to two types of failure: degradation failure and catastrophic failure. Both types of failure share an initial common source: an external shock process. This implies that they are stochastically dependent. In our developments of the model, the type of dependency between the two kinds of failure will be characterized. Conditional properties of the two competing risks are also investigated. These properties are the fundamental basis for the development of the maintenance strategy studied in this paper. Considering this maintenance strategy, the long-run average cost rate is derived and the optimal maintenance policy is discussed.


2015 ◽  
Vol 52 (02) ◽  
pp. 558-573 ◽  
Author(s):  
Ji Hwan Cha ◽  
Inma T. Castro

In this paper a stochastic failure model for a system with stochastically dependent competing failures is analyzed. The system is subject to two types of failure: degradation failure and catastrophic failure. Both types of failure share an initial common source: an external shock process. This implies that they are stochastically dependent. In our developments of the model, the type of dependency between the two kinds of failure will be characterized. Conditional properties of the two competing risks are also investigated. These properties are the fundamental basis for the development of the maintenance strategy studied in this paper. Considering this maintenance strategy, the long-run average cost rate is derived and the optimal maintenance policy is discussed.


2012 ◽  
Vol 201-202 ◽  
pp. 955-958
Author(s):  
En Shun Ge ◽  
Qing Min Li ◽  
Guang Yu Zhang

Condition-based Maintenance (CBM), which can efficiently improve the performance of the deteriorating system, would be influenced by imperfect inspection in practice. Aiming at this problem, a new CBM model under imperfect inspection is presented for deteriorating system, which described by Gamma process. The system is inspected periodically, and a preventive maintenance is performed if the degradation level exceeds a threhold. The inspection is imperfect, that means the measurements contain errors, and the CBM model should take these measure errors into account. The algorithm is shown to estimate the long run cost rate using Monte-Carlo method. Through numerical example, the influence of mesurement error over long run cost is analyzed. Therefore, the correctness and rationality of the model are proved.


2012 ◽  
Vol 544 ◽  
pp. 44-48 ◽  
Author(s):  
En Shun Ge ◽  
Qing Min Li ◽  
Ao Lin Huang

Condition-based Maintenance (CBM) can not only efficiently improve the performance of deteriorating system but also guarantee the system operation safety. This paper assumes that the system state is periodically inspected, and a preventive maintenance is performed if the degradation level exceeds a threshold. The effect of maintenance is imperfect, which means that maintenance can restore the system state to somewhere between as good as new and as bad as old. The algorithm is presented to get the solution of long run cost based on Monte-Carlo simulation, and the joint optimization of inspection rate, the threshold value and the number of preventive maintenance activities is investigated for the minimization of long run cost rate. A case study is given to show the procedure of the maintenance model and simulation. Therefore, the correctness and rationality of the model are proved.


Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.


Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.


Author(s):  
Ke Dong ◽  
Kehong Chen

We propose a maintenance policy for new equipment on a repair-refund maintenance strategy in this paper and derive the optimal lease period from the lessor’s perspective based on independent and identical distribution of historical failure data which obey power law process. The cost model of a full refund and a proportional refund is studied, and the corresponding optimal leasing period is determined by reducing the expected total cost rate to the largest extent. We use a numerical example to illustrate the proposed cost model and analyze the sensitivity of related parameters. Furthermore, we show that the proportional refund policy is preferable than a full refund to the lessor. Finally, according to the simulation outcome, the proposed methods are effective and instructions for lessor in regard to equipment lease are provided.


Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5948
Author(s):  
Renxi Gong ◽  
Siqiang Li ◽  
Weiyu Peng

Decision-making for the condition-based maintenance (CBM) of power transformers is critical to their sustainable operation. Existing research exhibits significant shortcomings; neither group decision-making nor maintenance intention is considered, which does not satisfy the needs of smart grids. Thus, a multivariate assessment system, which includes the consideration of technology, cost-effectiveness, and security, should be created, taking into account current research findings. In order to address the uncertainty of maintenance strategy selection, this paper proposes a maintenance decision-making model composed of cloud and vector space models. The optimal maintenance strategy is selected in a multivariate assessment system. Cloud models allow for the expression of natural language evaluation information and are used to transform qualitative concepts into quantitative expressions. The subjective and objective weights of the evaluation index are derived from the analytic hierarchy process and the grey relational analysis method, respectively. The kernel vector space model is then used to select the best maintenance strategy through the close degree calculation. Finally, an optimal maintenance strategy is determined. A comparison and analysis of three different representative maintenance strategies resulted in the following findings: The proposed model is effective; it provides a new decision-making method for power transformer maintenance decision-making; it is simple, practical, and easy to combine with the traditional state assessment method, and thus should play a role in transformer fault diagnosis.


2016 ◽  
Vol 22 (1) ◽  
pp. 35-50 ◽  
Author(s):  
Zied Hajej ◽  
Nidhal Rezg ◽  
Gharbi ali

Purpose – The purpose of this paper is to investigate the optimal production policy and maintenance strategy for leased equipment under a lease contract with warranty periods. In order to have steady revenue, the lessor (owner) of the equipment may provide guaranty periods to encourage the lessee to sign a lease contract with a longer lease period. Design/methodology/approach – Under this production/maintenance scheme, the mathematical model of the expected total cost is developed and the optimal production planning and the corresponding optimal maintenance policy are derived by choosing the optimal warranty periods for the lessee in order to minimize the total cost. Findings – The influence of the production rates variation in the equipment degradation is considered by an increased failure rate according to both time and production rates. The impact of warranty periods on optimal maintenance planning will be studied thereafter. Finally, numerical examples are given to illustrate the analytical study and the effects of the warranty periods variation during the lease periods on the maintenance policy and consequently on the total cost. Originality/value – The paper proposes a new idea of production and maintenance coupling in the leasing aspect. This study shows that it has a novelty and originality relative to this type of problem which considers and proposes a new maintenance strategy for leasing contract. This originality characterized by the influence of two factors on the equipment maintenance strategy. First factor is the influence of the production variation production rates on the machine degradation degree that is new in the literature charactering by analytical equation that shows the evolution of the machine failure rate according to its use (which is in our case the production rate for each period) respecting in the same time the continuity of the equipment reliability for a period to another.


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