• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 추계학술대회
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• pp.457-463
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• 2008

In this study, the mean time to failures of a system under shock models are derived. The system receives shocks according to a stochastic process. The expected system lifetime under homogeneous Poisson shock process, nonhomogeneous Poisson shock process, and a general renewal shock process are derived. Some numerical examples are presented.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.773-782
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• 2004

In this paper, a random shock model for a system is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arriving according to another Poisson process of rate $\lambda$ repairs the system only if the state of the system is below a threshold $\alpha$. After assigning various costs to the system, we calculate the long-run average cost and show that there exist a unique value of arrival rate $\lambda$ and a unique value of threshold $\alpha$ which minimize the long-run average cost per unit time.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 추계학술대회
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• pp.33-42
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• 2004

In this paper, a random shock model for a system is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arriving according to another Poisson process of rate $\lambda$ repairs the system only if the state of the system is below a threshold $\alpha$. After assigning various costs to the system, we calculate the long-run average cost and show that there exist a unique value of arrival rate $\lambda$ and a unique value of threshold $\alpha$ which minimize the long-run average cost per unit time.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.471-479
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• 1995

A random shock model for a linearly deteriorating system is introduced. The system deteriorating linearly with time is subject to random shocks which arrive according to a Poisson process and decrease the state of the system by a random amount. The system is repaired by a repairmen arriving according to another Poisson process if the state when he arrives is below a threshold. Explicit expressions are deduced for the characteristic function of the distribution function of X(t), the state of the system at time t, and for the distribution function of X(t) if X(t) is over the threshold. The stationary case is briefly discussed.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.725-733
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• 2005

A system subject to random shocks is considered. The shocks arrive according to a Poisson process and the amount of each shock is exponentially distributed. In this paper, a periodic inspection policy for the system is compared with a random inspection policy. After assigning several maintenance costs to the system, we calculate and compare the long-run average costs per unit time under two policies.

• 산업공학
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• 제15권1호
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• pp.64-72
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• 2002

Broaching machine is widely used for machining inner shaped slots in the work-pieces, and provides vertical motion (usually hydraulically powered) between tool and work-piece. In this study, we modelled the tool life process and investigated economic tool life of broaching machine. Tool life process is divided into wear-process and succeeding failure process. Wear process is defined as machining wear and failure process as 'chipping' occurred by random shock. We modelled wear process as linear regression function for products amounts and assumed failure process as Poisson process. Economic tool life is defined as the number of lots which minimizes average tool related cost per lot and analyzed by using age replacement policy technique. As tool-related cost factors, we consider tool replacement cost, tool maintenance cost and quality costs of products. The results of this study can be applied to analyze life process of general machining tools.

• 품질경영학회지
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• 제13권1호
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• pp.51-55
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• 1985

A replacement policy for a system subject to shocks where each shock increases the running cost is considered. The shocks arrive to the system according to a nonhomogeneous Poisson process. Optimal replacement policy to minimize the long-run expected cost rate is obtained and some numerical examples are given.

• 한국해안·해양공학회논문집
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• 제29권2호
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• pp.109-120
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• 2017

경사제 피복재를 예방적으로 유지관리할 수 있는 조건기반 할인비용모형을 제안하였다. 하중발생 사상을 이산시간 확률과정으로 고려하는 추계학적 누적 피해모형과 보수보강 비용에 대한 경제성 모형을 결합하여 수학적으로 유도하였다. 특히 본 논문에서 유도된 조건기반 유지관리의 할인비용모형은 시간에 따른 비용의 가치 뿐만 아니라 누적피해의 비선형성도 고려할 수 있다. 본 연구의 결과는 기존 모형들의 결과와 비교하여 만족스럽게 검증되었다. 또한 구조물의 중요도와 이자율 변화에 대한 민감도 분석도 수행하여, 구조물의 중요도가 높아질수록 예방적 보수보강의 최적시기는 빨라지나 이자율은 커질수록 반대의 경향이 나타난다는 것을 알았다. 한편 본 연구에서 유도된 추계학적 기대비용모형을 이용하여 여러 조건에 대하여 임의의 경사제 피복재 단면을 해석하였다. 표본경로기법을 적용하여 임의의 태풍 내습에 따른 경사제 피복재의 기대 누적피해수준을 예측하여 피해강도함수의 계수들을 추정할 수 있었다. 특히 하중발생 과정을 HPP(Homogeneous Poisson Process) 뿐만 아니라 DSPP(Doubly Stochastic Poisson Process)로도 해석하여 기대 누적피해수준에 미치는 하중발생의 불확실성에 대한 영향을 분석하여 하중발생사상을 이산시간 확률과정으로 고려해도 된다는 것을 확인하였다. 조건기반 할인비용모형의 해석 결과에 의하면 경사제 피복재의 설계조건에 따라 기대 누적피해수준의 거동특성이 크게 달라지고 이에 따라 예방적 보수보강을 수행하는 최적시기도 변한다는 것을 알 수 있었다. 마지막으로 파괴한계, 구조물의 중요도 그리고 이자율을 변화시키면서 예방적 유지관리를 가장 경제적으로 수행할 수 있는 최적시점과 피해규모를 결정할 수 있었다.

• 품질경영학회지
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• 제24권3호
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• pp.31-36
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• 1996

A Markovian stochastic model for a system subject to random shocks is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arrives at the system periodically for inspection and repairs the system only if the state is below a threshold. Costs are assigned to each inspection of the repairman, to each repair, and to the system being in bad states below the threshold. The expected long run average cost is obtained and compared with that of the random inspection introduced by Lee and Lee(1994).

• Korean Journal of Mathematics
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• 제22권3호
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• pp.529-552
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• 2014

As we know, some indices and data are strong influence to the price movement of some assets now, but not to another assets and in future. Thus we define some asset models for several time intervals; intraday, weekly, monthly, and yearly asset models. We define these asset models by using Brownian motion with volatility and Poisson process, and several deterministic functions(index function, twitter data function and big-jump simple function etc). In our asset models, these deterministic functions are the positive or negative levels of auxiliary indices, of analyzed data, and for imminent and extreme state(for example, financial shock or the highest popularity in the market). These functions determined by indices, twitter data and shocking news are a kind of one of speciality of our asset models. For reasonableness of our asset models, we introduce several real data, figurers and tables, and simulations. Perhaps from our asset models, for short-term or long-term investment, we can classify and reference many kinds of usual auxiliary indices, information and data.