• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.44-53
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• 1996

This paper deals with the problem of selecting optimal wear limit and initial process mean in a wear-out process. Consider a material removal processing machinery where 1)there are deffective items by linear shift in the mean of the diameter of to be processed with varing process variance and 2)there can be any failure in the machine tools or to be processed. In the previous studies, the one is analyzed by 'Model of Producing Goods' in quality control area and the other, any failure, is analyzed by 'Model of Producing Services' in reliability area. We propose a new integrated maintenance model, considering the percent defective and the failure rate. A numerical example for the model is given.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.137-140
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• 2011

A systemic building maintenance management is necessary to supply an convenience and safety environment by maintain the origin features for a building's life. However, the exist maintenance management system has some problems such as interoperability of information or standardization of data. In those reasons, a critical information for maintenance a building may be lost and changed. In addition, the data could be crashed or lost on a process of re-input or re-produce. This paper purpose the interoperability in exchanging data between design/construction and operation phases. In addition, this model will enhance the efficiency of building maintenance tasks through information quality improvement and data reproduction prevention.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.51-56
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• 2008

With growing demand for zero defects, predicting reliability of software systems is gaining importance. Software reliability models are used to estimate the reliability or the number of latent defects in a software product. Most reliability models to estimate the reliability of software in the literature are based on the development lifecycle stages. However, in the maintenance phase, the software needs to be corrected for errors and to be enhanced for the requests from users. These decrease the reliability of software. Software Reliability Growth Models (SRGMs) have been applied successfully to model software reliability in development phase. The software reliability in maintenance phase exhibits many types of systematic or irregular behaviors. These may include cyclic behavior as well as long-term evolutionary trends. The cyclic behavior may involve multiple periodicities and may be asymmetric in nature. In this paper, SGRM has been adapted to develop a reliability prediction model for the software in maintenance phase. The model is established using maintenance data from a commercial shop floor control system. The model is accepted to be used for resource planning and assuring the quality of the maintenance work to the user.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.703-712
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• 2017

The composite blades of offshore wind turbines accumulate structural damage such as fatigue cracking due to harsh operation environments during their service time, leading to premature structural failures. This paper investigates various fatigue crack models for reproducing crack development in composite blades and proposes a stochastic approach to predict fatigue crack evolution and to analyse failure probability for the composite blades. Three typical fatigue models for the propagation of fatigue cracks, i.e., Miner model, Paris model and Reifsnider model, are discussed to reproduce the fatigue crack evolution in composite blades subjected to cyclical loadings. The lifetime probability of fatigue failure of the composite blades is estimated by stochastic deterioration modelling such as gamma process. Based on time-dependent reliability analysis and lifecycle cost analysis, an optimised maintenance policy is determined to make the optimal decision for the composite blades during the service time. A numerical example is employed to investigate the effectiveness of predicting fatigue crack growth, estimating the probability of fatigue failure and evaluating an optimal maintenance policy. The results from the numerical study show that the stochastic gamma process together with the proper fatigue models can provide a useful tool for remaining useful life predictions and optimum maintenance strategies of the composite blades of offshore wind turbines.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.279-289
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• 1998

This study deals with the schemes of design, plan and operate maintenance management support systems and with the engineering approach for the solutions to build the maintenance management for the production efficiency. Maintenance Management Information System(MMIS) is the task that must focus on machinery historical data and planned maintenance action. Also the efficient supporting system in a maintenance management is achieved by database which is based on process of machinery's failure history. Designing method of maintenance management information system, maintenance modules are consisted of six factors ; machinery's historical data, lubrication control, check sheet, repair work, availability report, and performance report(control board and detailed reports), and then operators can rapidly utilize data in work place. In the implementation of designed model, program coding has been developed by Visual Basic 3.0. Data insertion, deletion and updating which perform menu screen is implemented by reading data from database. Implementation model based on LAN environment and related data is stored in Microsoft DBMS.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.63-70
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• 2003

In this study, we employed an arithmetic process (AP) approach to resolve gearbox maintenance problems. The approach is realistic and direct in modelling the characteristics of a deteriorating system such as a gearbox since a decreasing AP can model a gearbox's successive operating times and an increasing AP can model the corresponding consecutive repair times. First of all, two test statistics were used to check whether the process is arithmetic or not. Next, model parameters of the AP were estimated using the simple linear regression method. Finally, the optimal replacement policy based on minimising the long-run average cost per day was determined for each type of gearbox.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.61 no.2
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• pp.67-73
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• 2012

This paper proposes optimal maintenance strategies for power distribution systems that involve the use of the reliability-centered maintenance (RCM) method. We developed an improved decision model based on the Markov process. This model can obtain the optimal inspection interval and maintenance method based on the total expected cost. We used ordinal optimization for solving the optimal problem. Optimal maintenance strategies were presented by applying the developed method to the RBTS model. A B/C analysis proved that these strategies offer maximum benefit-to-cost.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.1-5
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• 2009

Recently, as a method of green-development and reduction of carbon dioxide emission, increased interest has been focused on a railway. Furthermore, an intensive study has been processed on capabilities of maintenance activities, economic efficiency of maintenance on rail structure and a design of railway structure as well as the development of materials. The purpose of this paper is to develop a deteriorated model of PC Beam Bridge due to timely changes and maintenance activities. Typically, there is definite difference between maintained bridges and non-maintained bridges. As a result of proper maintenance activity, a life time of a structure can be enhanced. In this study, we will research and analyze structures with ongoing maintenance. We will also process same procedures on structures without maintenance. Therefore, we can establish the significant role in a conditional change of a structure. Based on a study, we accomplish the development of a condition-deteriorated model. To develop deteriorated model of PC Beam Bridge, We apply Marcov Theory and develop a transition probability to show the life time of bridge. This study will provide a great benefit to decision making for maintenance activities on the railway bridges for future.