• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.1025-1028
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• 2008

Using of maintenance system for gate bridge algorism, We made out algorism and engine for prediction of life cycle by neutralization, freezing-thawing and damage from sea wind. To objective of this system, user can use easily with maintenance system for gate bridge. Also, to improve of maintenance efficiency, web-program made out by superannuated evaluation and analysis of field exposure data. To develope web-program, we framing structure design of database, which is adapted to method of maintenance, repair, and reinforcing

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.271-275
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• 2009

본 연구에서는 상수관로의 잔존수명을 통계적 기법 중 하나인 비례위험모형(PHM)에 적용하여 평가하였다. 비례위험모형을 구축하기 위한 개별관로의 생존시간은 관로의 파손율이 한계파손율에 도달하는 시간으로 정의하였다. 즉, Park and Loganathan(2002)에서 제시한 GPBM을 적용하여 시간에 따른 개별관로의 파손율을 추정하고 추정된 파손율과 한계파손율의 상등관계를 통해 생존시간을 산정하였다. 또한, 본 연구대상관로에 대한 GPBM을 구축함에 있어, 매설시점에서 누적파손횟수를 0으로 한 파손기록을 입력자료에 추가하는 방법과 가중계수(WF)의 범위를 수정함으로써 기존의 GPBM을 보완하였다. 이로써 파손사건이 최소 1회 이상 기록된 강관 및 주철관에 대한 비례위험모형을 구축하였다. 이와 같이 수정된 방법론은 관로 파손사건 등의 자료의 축적이 미비한 국내 여건에서 비례위험모형 및 GPBM과 같은 통계적 모형을 구축할 때 유용할 것으로 사료된다. 본 연구대상관로의 비례위험모형에 포함된 유의한 공변수는 관종과 관경 그리고 길이이며 관종은 비례성 가정을 위배하여 시간종속형 변수로 모형화되었다. 최종 채택된 PHM모형을 통해 생존함수를 추정하였으며 추정된 생존함수를 이용하여 개별관로의 잔존수명 및 경제적 수명 그리고 각 수명에 대한 95% 신뢰구간을 산정하였다. 또한 개별관로의 경제적 수명에 영향을 미치는 공변수의 위험비율도 분석하였다. 분석결과 강관의 평균 경제적 수명은 약 25.1년이고 주철관은 약 21년으로 산정되었다. 또한 관종에 따른 경제적 수명에 도달할 상대적인 위험률은 전반적으로 주철관이 높으나 20년 이상 매설된 관로에서는 강관의 위험률이 높을 것으로 분석되었다. 관경과 길이는 크기에 비례하여 상대적 위험률도 증가하였다.

• Korean Journal of Environmental Biology
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• v.36 no.4
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• pp.550-553
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• 2018

The lifespan of bats is longer compared to that of other similarly sized mammals, and it is recorded that some bats' lifespan is more than 30 years. However, it is known that the lifespan of Pipistrellus abramus using human residential areas as their habitats is less than five years. We have put aluminum rings on the forearms of 284 P. abramus starting from 2008. Interestingly, in June 2018, a female adult bat was recaptured ten years after the aluminum ring was attached. The results of this study on the lifespan of P. abramus is new and it's likely to form the baseline for lifespan studies and habitat management of P. abramus in the future.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.735-744
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• 2021

Maintaining the lifetime of a product is one of the objectives of quality control. In real processes, most samples are constructed with censored data because, in many situations, we cannot measure the lifetime of all samples due to time or cost problems. In this paper, we propose two cumulative sum (CUSUM) control charting procedures to monitor the mean of type I right-censored lognormal lifetime data. One of them is based on the likelihood ratio, and the other is based on the binomial distribution. Through simulations, we evaluate the performance of the two proposed procedures by comparing the average run length (ARL). The overall performance of the likelihood ratio CUSUM chart is better, especially this chart performs better when the censoring rate is low and the shape parameter value is small. Conversely, the binomial CUSUM chart is shown to perform better when the censoring rate is high, the shape parameter value is large, and the change in the mean is small.

• 한국ITS학회:학술대회논문집
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• v.2007 no.10
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• pp.196-201
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• 2007

현재 국내 ITS는 현장장비 유지관리에 대한 연구 및 고장관련 DB가 부족하여 예비부품수 및 교체시기 산정에 대한 규정이 없는 실정이다. 이에 본 연구는 실제 고장이력자료를 갖고 신뢰성 분석을 실시하여 단거리전용통신(DSRC)방식 노변기지국(RSE)의 예비부품수 및 교체시기를 산정하였다. 전체 수집기간동안의 고장자료는 욕조곡선의 형상을 나타내어 우발고장기간의 자료로 신뢰성 분석을 실시하였으나 고장 수명 분포 중 적합되는 분포가 없었다. 따라서, i)장비가동률과 ii)경험적(empirical) 누적분포함수(CDF) 곡선을 이용한 장비의 고장률(건/일)을 감안하여 예비부품수를 산정한 결과 16.22개 이상의 노변기지국(완제품)을 확보하여야 하는 것으로 분석되었다. 하자보수기간(2년)이 지난후 일정기간($2{\sim}3$년)이 지난 시점에서 향후 10년간에 대하여 수리하면서 사용하는 경우와 신품구입시의 총비용을 비교하여 산정한 교체시기는 10.67건/40개월 이상이다. 본 연구 수행결과 첫째, 비모수적 방법으로 적합도 검정을 실시하지 못하였다는 한계와, 둘째, 초기에 고장이 많이 발생하는 장비는 향후에도 고장이 많이 발생한다는 가정에 기반하여 향후 10년의 운영비용을 분석하였으나 이러한 가정을 입증하지는 못하였다. 따라서, 향후엔 본 연구에 사용된 자료가 고장 수명분포도 적합 되지 않은 원인을 분석하는 것과 분석대상 기간 이후의 자료를 추가하여 적합도 검정 및 신뢰성 분석을 실시하는 것이 필요하다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.453-461
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• 2012

Life analysis is conducted for economic analysis of equipment or facilities. The purpose of life analysis is to predict future indicators for scrapping construction equipment, and establish and utilize a wide variety of business strategies according to data predictions. First, this study shows the methods to figure out average life, life expectancy and life prediction of construction equipment and the analysis of life making methods, using survival curves. Second, the study proposes and examines the life expectancy making model depending on revenues and expenses. The result of the study reveals that the economic life of the same equipment varies with expenses, revenues and the initial cost. The life expectancy making model for construction equipment reflects respective management status for equipment and will help efficient management for companies.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1329-1346
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• 2016

Korea Health Panel (KHP) data and Korea National Health and Nutrition Examination Survey (KNHANES) data are collected by self-assess and self-report for individual's health status and medical use. Previous studies have claimed that the reliability for prevalence rates and health life expectancies obtained from these data should be validated. National Health Insurance Services in Korea recently released a sample cohort DB that contain all data related to the use of medical facilities for all entire Korea citizens. It has been shown that disease-specific prevalence rates calculated from these data are representative and reliable for the entire population. In this paper, we evaluate the reliability of prevalence rates derived from self-reported data such as KHP and KNHANES by comparing to the prevalence rates from the sample cohort DB. We found that both KHP and KNHANES underestimate prevalence rates and in turn overestimate health life expectancies. Moreover, the general trends of health life expectancies might be distorted (except for the sample cohort DB) because of sampling and non-sampling errors.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.21-30
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• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level, and based on the time the performances of items are investigated at the normal stress level. In this paper, when the mean of the prior of a failure rate is known in the exponential lifetime distribution with censored accelerated failure time data, we utilize the empirical Bayesian method by using the moment estimators in order to estimate the parameters of the prior distribution and obtain the empirical Bayesian predictive density and predictive intervals for a future observation under the normal stress level.

• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.687-696
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• 2011

Customer Lifetime or Customer Lifetime Value is a essential metric of differentiated CRM marketing and differentiated marketing strategy as a company core competency. However, customer lifetime used in companies is easily obtained from a confined simple customer attrition rate at some specific time point regardless of customer characteristics. In this study, in order to overcome the constraints of previous simple methods and to make practical use of it in industries, we suggest a method that estimates a customer lifetime using a customer segment based survival analysis with the censored data of customers; in addition, we apply this method to A mobile telecom company data. A method using customer segment based survival analysis is suggested in this study 1) includes all customers having different subscription dates, 2) reduces individual error, 3) can reflect trends after the observed time point and is more realistic.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.89-100
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• 2020

The smart factory is an important axis of the 4th industrial revolution. Smart factory is a system that induces the maximum efficiency and effectiveness of production using the IoT and intelligent sensing systems. The product lifecycle management technique is a method that can actively reflect the consumer's requirements in the smart factory and manage the entire process from the consumer to the post management. There have been many studies on product lifecycle management, but studies on how to organize product lifecycle management knowledge domains in preparation for the era of the 4th industrial revolution were insufficient. This study analyzed the opinions of a group of experts preparing for the 4th industrial revolution in terms of product lifecycle management. The impact of the 4th industrial revolution on the detailed knowledge areas of product lifecycle management was investigated. The changes in product lifecycle management were summarized using a qualitative data analysis technique for a group of experts. Based on the opinions of experts, the product lifecycle management, which consists of a total of 30 detailed knowledge areas, was prepared to supplement or prepare for the 4th industrial revolution. This study investigates changes in product lifecycle management in preparation for the 4th industrial revolution in the knowledge domain of the existing defined product life cycle management. In future research, it is necessary to redefine the knowledge domain of product life cycle management suitable for the era of the 4th industrial revolution and investigate the perception of experts. Considering the social culture and technological change factors of the 4th industrial revolution, the scope and scope of product life cycle management can be newly defined.