• Journal of the military operations research society of Korea
• /
• v.24 no.1
• /
• pp.98-109
• /
• 1998

This study develops a maintenance strategy for a reparable 2-unit standby system. The maintenance strategy implies the waiting time to call the repair facility when the unit-1 fails. Almeida and Souza set up the multi-attribute utility function consisting of system availability and repair cost for several maintenance strategies and decide the optimal maintenance strategy that maximize the expected value of the utility function. We decide the optimal maintenance strategy satisfying the following two criteria about the utility function : maximum variance using Almeida and Souza's utility function. It both criteria are not satisfied at the same time for every strategies, the strategy maximizing the lower confidence limit for expected utility function is regarded as an optimal one.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.1
• /
• pp.60-66
• /
• 2021

The importance of maintenance is leading the application of the maintenance strategy in various industries. The maritime industry is also a part of them, with changes in selecting and applying the maintenance strategy, but rather slowly, by retaining the old strategy. In particular, the ship is maintaining a previously used strategy. In the circumstance of the sea, ship requires a new suggestion for maintenance strategy. A ship predictive maintenance model predicts the breakdown or malfunction of machineries to secure maintenance time with preventive actions and treatments, thereby avoiding maintenance-related dangerous factors. This study focused on applying text analysis to an Liquefied Natural Gas Carriers dock indent document, and the analysis results were interpreted from the original document. The inter-relational patterns observed from the frequency of common maintenance combinations among different parts and equipment in ships will be applied to the development of ship predictive maintenance.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.1
• /
• pp.25-31
• /
• 2011

The purpose of power system maintenance is to prevent equipment failure. The maintenance strategy should be designed to balance costs and benefits because frequent maintenance increases cost while infrequent maintenance can also be costly due to electricity outages. This paper proposes maintenance modeling of a power distribution system using reliability centered maintenance (RCM). The proposed method includes comprehensive equipment modeling and impact analysis to evaluate the effect of equipment faults. The problem of finding the optimum maintenance strategy is formulated in terms of dynamic programming. The applied power system is based on the RBTS Bus 2 model, and the results demonstrate the potential for designing a maintenance strategy using the proposed model.

• International Journal of Reliability and Applications
• /
• v.18 no.1
• /
• pp.9-20
• /
• 2017

In this paper, we consider a renewable repair-replacement warranty strategy with age-dependent minimal repair service and propose an optimal maintenance model during post-warranty period. Such model implements the repair time limit under warranty and follows with a certain form of system maintenance strategy when the warranty expires. The expected cost rate is investigated per unit time during the life period of the system as for the standard for optimality. Based on the cost design defined for each failure of the system, the expected cost rate is derived during the life period of the system, considering that a renewable minimal repair-replacement warranty strategy with the repair time limit is provided to the customer under warranty. When the warranty is finished, the maintenance of the system is the customer's responsibility. The life period of the system is defined and the expected cost rate is developed from the viewpoint of the customer's perspective. We obtain the optimal maintenance strategy during the maintenance period by minimizing such a cost rate after a warranty expires. Numerical examples using field data are shown to exemplify the application of the methodologies proposed in this paper.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.4
• /
• pp.1248-1257
• /
• 2014

Overhead transmission lines are crucial components in power transmission systems. Well-designed maintenance strategy for overhead lines is required for power utilities to minimize operating costs, while improving the reliability of the power system. This paper presents a maintenance priority index (MPI) of overhead lines for a reliability centered approach. Proposed maintenance strategy is composed of a state index and importance indices, taking into account a transmission condition and importance in system reliability, respectively. The state index is used to determine the condition of overhead lines. On the other hand, the proposed importance indices indicate their criticality analysis in transmission system, by using a load effect index (LEI) and failure effect index (FEI). The proposed maintenance method using the MPI has been tested on an IEEE 9-bus system, and a numerical result demonstrates that our strategy is more cost effective than traditional maintenance strategies.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.11 no.4
• /
• pp.109-120
• /
• 2007

In this study, a bridge maintenance system is developed to generate performance-based optimum maintenance strategy by considering the life-cycle cost. A multi-objective combinatorial optimization problem is formulated to generate a tradeoff maintenance scenarios which satisfies the balance among the conflicting objectives such as the performance and cost during the bridge lifetime and a genetic algorithm is applied to the system. By using the developed program, this study proposes a process of optimum maintenance scenario applying to the steel girder bridge of national road. The developed system improves the current methods of establishing the bridge maintenance strategy and can be utilized as an efficient tool to provide the optimum bridge maintenance scenario corresponding to the various constraints and requirements of bridge agency.

• Smart Structures and Systems
• /
• v.18 no.3
• /
• pp.569-584
• /
• 2016

This paper presents a method for stochastic modelling of fatigue crack growth and optimising inspection and maintenance strategy for the structural members of steel bridges. The fatigue crack evolution is considered as a stochastic process with uncertainties, and the Gamma process is adopted to simulate the propagation of fatigue crack in steel bridge members. From the stochastic modelling for fatigue crack growth, the probability of failure caused by fatigue is predicted over the service life of steel bridge members. The remaining fatigue life of steel bridge members is determined by comparing the fatigue crack length with its predetermined threshold. Furthermore, the probability of detection is adopted to consider the uncertainties in detecting fatigue crack by using existing damage detection techniques. A multi-objective optimisation problem is proposed and solved by a genetic algorithm to determine the optimised inspection and maintenance strategy for the fatigue affected steel bridge members. The optimised strategy is achieved by minimizing the life-cycle cost, including the inspection, maintenance and failure costs, and maximizing the service life after necessary intervention. The number of intervention during the service life is also taken into account to investigate the relationship between the service life and the cost for maintenance. The results from numerical examples show that the proposed method can provide a useful approach for cost-effective inspection and maintenance strategy for fatigue affected steel bridges.

• Journal of Korean Society of Steel Construction
• /
• v.14 no.5 s.60
• /
• pp.627-639
• /
• 2002

Bridge construction is almost complete in many countries. Thus, the government and highway agencies change their focus from constructing to maintaining. Effectively maintaining bridges require predicting their lifespan using a system reliability viewpoint. Likewise, maintenance models based on the system reliability concept should be developed. Thus, this study developed maintenance models for preventive maintenance and essential maintenance using system reliability and lifetime distributions. The optimal maintenance strategy for an existing bridge was obtained using the developed maintenance models.

• Journal of the Korean Society for Railway
• /
• v.8 no.6 s.31
• /
• pp.544-549
• /
• 2005

Nowadays, most of bridge networks are complete or close to completion. The biggest challenge railroad./highway agencies and departments of transportation face is the maintenance of these networks, keeping them safe and serviceable, with limited funds. To maintain the bridges effectively, there is an urgent need to predict their remaining life from a system reliability viewpoint. And, it is necessary to develop the maintenance models based on system reliability concept. In this paper, maintenance models are developed for preventive maintenance and essential maintenance by using system reliability and lifetime distributions. The proposed model is applied to an existing railroad bridge. The optimal maintenance strategy of this bridge is obtained in terms of services life extension and cumulative maintenance cost.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.1
• /
• pp.118-127
• /
• 2014

The configuration such as series, parallel and k-out-of-n of a repairable system directly affects its reliability. The maintenance strategy can also affect the overall performance of the system. The objective of this work is to investigate the possible trade-off between the configuration of a repairable k-out-of-n system and its maintenance strategy. The redundancy is considered to be the design decision variables, whereas the preventive maintenance period is considered to be the maintenance decision variables. The optimization model is used to minimize the overall life cycle cost associated with the system, considering constraint on reliability. Finally, genetic algorithm is used to find the optimal values for the decision variables. The result is compared with optimal values for considering redundancy and maintenance respectively.