• 한국신뢰성학회지:신뢰성응용연구
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• 제7권1호
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• pp.13-22
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• 2007

A preventive maintenance model, caller FNBM (${\alpha},{\delta},{\gamma}$) model, is proposed to decide an optimal repair number under achieved availability requirements (r) along with taking two types of failures (repairable or irrepairable) into account. In this model, the current system is replaced by a new one in case when it doesn't meet the achieved availability requirement, even though it is repairable failure; Othewise it is replaced in time of the first irrepairable failure. Assumed that the j-th failure is repairable with probability ${\alpha}_j$ minimal repairs are allowed for repairable failure between replacements. Expected cost rate for preventive maintenance model is developed using NHPP (Non - Homogeneous Poisson Process) in order to de term in the optimal number $n^*$, also numerical examples are shown in order to explain the proposed model. Since the proposed FNBM (${\alpha},{\delta},{\gamma}$) model includes Park FNBM model (1979) and Nakagawa FNBM (p) model (1983) m this proposed model is thought to be better than previous model, especially for weapon system which requires availability as primary parameter.

• 산업경영시스템학회지
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• 제30권3호
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• pp.89-93
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• 2007

In this study, we consider an assembly line operated under a base-stock policy. A product consists of two parts, and a finished product transfers to a warehouse in which demands are satisfied. Assume that demands arrive according to a Poisson process and processing times at each production line are exponentially distributed. Whenever a demand arrives, it is satisfied immediately from an inventory in the warehouse if available; otherwise, it is backlogged and satisfied later by the next product exiting from production lines. In either case, an arriving demand automatically triggers the production of a part at both production lines. These two parts will be assembled into a product that eventually transfers to the warehouse. We obtain a closed form formula of approximation for delay time or lead time distribution of a demand when a base- stock level is s. Moreover, it can be applied to the optimal base-stock level which minimizes the total inventory cost. Numerical examples are presented to show our optimal base-stock level's quality.

• 한국시뮬레이션학회논문지
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• 제17권4호
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• pp.241-247
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• 2008

본 연구에서는 하나의 포아송 도착과정(Poisson Arrival Process)과 상수(constant) 서비스 시간을 갖는 유한 버퍼(finite buffer) 대기행렬을 분석 대상으로 한다. 유한 버퍼로 인한 차단현상으로 도착하는 고객이 시스템에 진입하지 못하고 시스템을 떠나게 된다. 이러한 M/D/1/K 대기행렬에서 차단확률(blocking probability)의 계산방법은 이미 연구되어있지만, 계산과정이 매우 복잡하다. 본 연구에서는(max,+)-대수를 이용하여 차단확률을 도출하는 새로운 방법을 제안하고자 한다. 제안된 방법은 기존 연구결과보다 쉽게 차단확률을 계산할 수 있을 뿐만 아니라 보다 복잡한 대기행렬 망에서의 차단확률을 구하는데도 응용 될 수 있을 것이다.

• 한국경영과학회지
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• 제31권1호
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• pp.15-24
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• 2006

In simulation input modeling, it is important to identify a probability distribution to represent the input process of interest. In this paper, an appropriate sample size is determined for parameter estimation associated with some typical probability distributions frequently encountered in simulation input modeling. For this purpose, a statistical measure is proposed to evaluate the effect of sample size on the precision as well as the accuracy related to the parameter estimation, square rooted mean square error to parameter ratio. Based on this evaluation measure, this sample size effect can be not only analyzed dimensionlessly against parameter's unit but also scaled regardless of parameter's magnitude. In the Monte Carlo simulation experiments, three continuous and one discrete probability distributions are investigated such as ; 1) exponential ; 2) gamma ; 3) normal ; and 4) poisson. The parameter's magnitudes tested are designed in order to represent distinct skewness respectively. Results show that ; 1) the evaluation measure drastically improves until the sample size approaches around 200 ; 2) up to the sample size about 400, the improvement continues but becomes ineffective ; and 3) plots of the evaluation measure have a similar plateau pattern beyond the sample size of 400. A case study with real datasets presents for verifying the experimental results.

• Journal of Information Technology Applications and Management
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• 제24권2호
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• pp.71-80
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• 2017

Software reliability is one of the most elementary and important problems in software development In order to find the software failure occurrence, the instantaneous failure rate function in the Poisson process can have a constant, incremental or decreasing tendency independently of the failure time. In this study, we compared the reliability performance of the software reliability model using the parameters of Pareto life distribution with the intensity decreasing pattern and the shape parameter of Erlang life distribution with the intensity increasing and decreasing pattern in the software product testing. In order to identify the software failure environment, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, we compare and evaluate software reliability by applying software failure time data. The reliability of the Erlang and Pareto life models is shown to be higher than that of the Pareto lifetime distribution model when the shape parameter is higher and the Erlang model is more reliable when the shape parameter is higher. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing basic knowledge using software failure analysis.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 1998년도 추계 학술발표회 논문집 Proceedings of EESK Conference-Spring 1998
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• pp.413-420
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• 1998

In this paper, two methods, Stepp's and EQHAZARD, are introduced and applied to a recent earthquake catalog for the entire Korean Peninsula that can estimate the seismicity by incorporating the incompleteness of the earthquake catalog. EQHAZARD method, different from Stepp's method in that it used priori information besides the assumption of stationary Poisson process of the earthquakes, produces the higher seismicity rate for the smaller earthquakes. EQHAZARD method are also used to estimated the incompleteness of the recent earthquake catalog for the southern part of the Korean Peninsula in terms of the Probability of Activity for the specified earthquke magnitude classes and time periods. It is believed that the Probability of Activity thus obtained can be used as a strong priori information in estimating the seismicity for a seismic source within the region where there are not enough earthquakes detected. Finally, it is demonstrated that the arbitrary selection of the methods. of incompleteness analysis brings quite different seismic hazard results, which suggests the need to employ a rigid quantitative method for incompleteness analysis in estimating the seismicity parameters in order to reduce the uncertainty in the Seismic Hazard Results with the EQHAZARD method being one of the competent practical alternatives.

• Journal of Information Technology Applications and Management
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• 제12권2호
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied. SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull curve as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing-effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Industrial Engineering and Management Systems
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• 제7권1호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.818-822
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• 2003

We propose a software-reliability growth model incoporating the amount of uniform and Weibull testing efforts during the software testing phase in this paper. The time-dependent behavior of testing effort is described by uniform and Weibull curves. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, the model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. The optimum release time is determined by considering how the initial reliability R(x|0) would be. The conditions are $R(x|0)>R_o$, $R_o>R(x|0)>R_o^d$ and $R(x|0)<R_o^d$ for uniform testing efforts. Ideal case is $R_o>R(x|0)>R_o^d$. Likewise, it is $R(x|0){\geq}R_o$, $R_o>R(x|0)>R_o^{\frac{1}{g}$ and $R(x\mid0)<R_o^{\frac{1}{g}}$ for Weibull testing efforts. Ideal case is $R_o>R(x|0)>R_o^{\frac{1}{g}}$.

• 한국산업정보학회논문지
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• 제7권4호
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• pp.46-52
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• 2002

기업의 경영범위가 확대되고 경영패러다임이 글로벌 경영으로 전환되면서 기업의 가치평가도 제품 및 서비스 위주 평가뿐만 아니라 작업장내에서 발생하는 각종 사고에 대한 평가까지도 포함시키는 포괄적인 기업경영평가로 확대되고 있다. 그래서 기업들도 안전보건에 대한 관리에서 실패할 경우, 기업의 이미지 저하는 물론 사고처리비용이 많이 들기 때문에 각 기업은 안전보건에 대해 지속적인 투자와 많은 관심을 가져야 한다. 따라서 본 연구에서는 산업현장에서 안전관리를 하는데 있어서 문제점을 살펴보고, 그리고 재해예방전문기관의 설립 전과 설립 후에 대한 재해통계자료를 Duane의 신뢰성 성장모델을 이용하여 분석해 보고, 모델의 적합성을 검증해 보고자 한다. 이러한 분석을 위해서 재해발생 수는 포아송 분포로, 그리고 분포의 평균값은 시간에 따라 변화하는 NHPP로 가정하였다.