• 산업기술연구
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• 제28권A호
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• pp.43-49
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• 2008

The track of high-speed railway get deteriorated according as using it. In that case, the maintenance jobs are needed for improvement of track quality. A scheduling problem for the track maintenance of high-speed railway is to determine the jobs should be performed daily. In the problem, the set of jobs for maintenance is given. Each job has it's parameters such as due date, emergency level, and processing time. In addition, jobs can be worked during a certain fixed time when the train doesn't move. In this study, we developed a mathematical model of the scheduling problem for the maintenance of high-speed railway and solved the problem using the ILOG CPLEX library.

• 한국신뢰성학회지:신뢰성응용연구
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• 제1권1호
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• pp.47-54
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• 2001

This paper considers the parameter estimation problem of the failure intensity function and maintenance effect in a repairable system. We propose estimation procedures for repairable systems on which preventive maintenance is performed. The failure process is modeled by a proportional age reduction model [Brown, Mahoney and Sivazlian(1983)] which is useful to model the imperfect effect of preventive maintenance. When failure and maintenance (preventive) times are given, the maximum likelihood method is used to estimate the maintenance effect and the parameters of intensity function, simultaneously We obtain the maximum likelihood estimators using a genetic algorithm. A numerical example is also presented.

• Tribology and Lubricants
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• 제18권4호
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• pp.285-290
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• 2002

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 2001년도 제34회 추계학술대회 개최
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• pp.252-259
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• 2001

Integrated condition monitoring is required to monitor effectively the machine conditions since machine failures could not be monitored accurately by any single measurement parameter. Application of various condition monitoring techniques is therefore preferred in many cases in order to diagnosis the machine condition. However it inevitably requires lots of maintenance cost and sometimes it could be proved to over-maintenance unnecessarily. This could happen especially when one measurement parameter closely correlates to another. Therefore correlation analysis of various monitoring parameters has to be performed to improve the reliability of diagnosis. In this work, Pearson correlation coefficient was used to analyze the correlation between condition monitoring parameters of an over-loaded machine system where the vibration, wear and temperature were monitored simultaneously. The result showed that Pearson correlation coefficient could be regarded as a good measure for evaluating the availability of condition monitoring technology.

• Journal of Periodontal and Implant Science
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• 제48권4호
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• pp.251-260
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• 2018

Purpose: The aim of this retrospective cross-sectional study was to evaluate whether salivary findings of active matrix-metalloproteinase 8 (aMMP-8) chairside (point of care; POC) tests were associated with periodontal risk assessment parameters in patients receiving supportive periodontal therapy (SPT). Methods: A total of 125 patients receiving regular SPT were included, and their records were examined. The following inclusion criteria were used: a diagnosis of chronic periodontitis, at least 1 non-surgical periodontal treatment (scaling and root planning) with following regular SPT (minimum once a year), at least 6 remaining teeth, and clinical and aMMP-8 findings that were obtained at the same appointment. In addition to anamnestic factors (e.g., smoking and diabetes), oral hygiene indices (modified sulcus bleeding index [mSBI] and approximal plaque index), periodontal probing depth simultaneously with bleeding on probing, and dental findings (number of decayed, missing, and filled teeth) were recorded. Salivary aMMP-8 levels were tested using a commercial POC test system (Periomarker, Hager & Werken, Duisburg, Germany). Statistical analysis was performed using the t-test, Mann-Whitney U test, Fisher's exact test, and ${\chi}^2$ test, as appropriate (P<0.05). Results: Only the mSBI was significantly associated with positive salivary aMMP-8 findings (aMMP-8 positive: $27.8%{\pm}20.9%$ vs. aMMP-8 negative: $18.0%{\pm}14.5%$; P=0.017). No significant associations were found between aMMP-8 and smoking, diabetes, periodontal parameters, or parameters related to the maintenance interval (P>0.05). Conclusions: Salivary aMMP-8 chairside findings were not associated with common parameters used for periodontal risk assessment in patients receiving SPT. The diagnostic benefit of POC salivary aMMP-8 testing in risk assessment and maintenance interval adjustment during SPT remains unclear.

• 한국구조물진단유지관리공학회 논문집
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• 제16권5호
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• pp.29-39
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• 2012

상관관계가 높은 복합열화의 완벽한 개별예측모델의 개발은 매우 어려운 문제로, 본 논문에서는 현수교 시스템의 미래열화와 유지 예산을 예측하기 위하여, 10년간의 유지 데이터가 주어진 매개변수(파손지표와 사용성)의 사후 확률 밀도함수를 찾기 위해 베이지언 추론을 적용하였다. 마르코프 연쇄 몬테카를로법을 이용하여 매개변수의 사후 분포를 조사하였다. 감소한 사용성의 모의위험예측은 사전분포와 연간유지 업무에서 업데이트한 데이터의 가능성에 따라 작성한 사후 분포이다. 기존의 선형 예측 모델과 비교하면, 제안된 2차 모델은 교량부품의 사용성, 위험요소, 그리고 유지 예산의 측정 데이터에 대하여 매우 개선된 수렴성과 근접성을 제공한다. 따라서 제안된 2차 추계학적 회귀 모델을 기반으로 복잡한 사회간접설비의 미래 성능과 유지관리예산을 예측하고 제어할 수 있는 기회를 제공할 것으로 기대한다.

• 산업공학
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• 제19권3호
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• pp.245-254
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• 2006

Equipments in container terminal have a lot of parts, and an equipment breakdown affects the productivity of terminal. In this paper, we develop a maintenance management system for improving reliability, availability and maintainability of equipments in container terminals. The developed system consists of five modules : equipment structure module, equipment operation management module, maintenance control module, spare part control module and data analysis module. The system supports reliability engineers to manage and improve RAM of equipments in container terminals. For example, FMEA, failure state analysis and life distribution parameters estimation are easily or automatically done by the system. This system also provides optimal preventive maintenance intervals by simulation and optimal yearly PM schedules for equipments in container terminal are recommended.

• 한국철도학회논문집
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• 제13권2호
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• pp.222-228
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• 2010

전기 기관차 중수선 시설과 같이 복잡한 시스템의 설계 변수와 중요 변수 최적화는 수리적인 형태로 분석하는 것이 매우 어려운 작업이 된다. 본 논문에서는 메타 모델의 개념을 시뮬레이션 근사 모델에 적용하여 설계 변수와 중요 변수의 최적화를 수행하였다. 시뮬레이션 설계를 위하여 Critical Path 분석과 민감도 분석 수행하여 설계 변수와 실험 횟수를 줄이기 위하여 노력을 하였다. 시뮬레이션 분석은 다 목적 비선형 계획법을 구성한 후 파레토 최적해 집합을 산출하여 설계자에게 다중 대안의 해 집합을 제시하여 실제 시스템의 적용에 대한 유동성을 제공하려고 노력하였다. 본 논문에서 제시 된 기법은 열차 중수선 시설의 설계 및 분석에 있어서 시뮬레이션과 메타 모델을 이용한 하나의 방법으로 이용이 가능 할 것이다.

• Structural Monitoring and Maintenance
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• 제2권1호
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• pp.1-18
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• 2015

Traditionally, it is not easy to carry out tests to identify modal parameters from existing railway bridges because of the testing conditions and complicated nature of civil structures. A six year (2007-2012) research program was conducted to monitor a group of 25 railway bridges. One of the tasks was to devise guidelines for identifying their modal parameters. This paper presents the experience acquired from such identification. The modal analysis of four representative bridges of this group is reported, which include B5, B15, B20 and B58A, crossing the Caraj$\acute{a}$s railway in northern Brazil using three different excitations sources: drop weight, free vibration after train passage, and ambient conditions. To extract the dynamic parameters from the recorded data, Stochastic Subspace Identification and Frequency Domain Decomposition methods were used. Finite-element models were constructed to facilitate the dynamic measurements. The results show good agreement between the measured and computed natural frequencies and mode shapes. The findings provide some guidelines on methods of excitation, record length of time, methods of modal analysis including the use of projected channel and harmonic detection, helping researchers and maintenance teams obtain good dynamic characteristics from measurement data.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1997년도 추계학술대회발표논문집; 홍익대학교, 서울; 1 Nov. 1997
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• pp.193-196
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• 1997

In this paper we consider a Bayesian theoretic approach to periodic incomplete preventive maintenance with minimal repair at failure. We assume that the system failure rate is increasing as the frequency of PM increases and that the system is replaced at the K-th PM under this maintenance strategy. The optimal policies which minimize the expected cost rates are discussed. We seek the optimal periodic PM interval x and replacement time K under a Weibull failure intensity. Assuming suitable prior distribution for the Weibull parameters, we derive the posterior distribution incorporating failure data and obtain the updated optimal replacement strategies.