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안선응,장재영,박창순 한국경영공학회 2010 한국경영공학회지 Vol.15 No.3
This research deals with the failure rate of the components of a complex system. The failure of a complex system is caused by the failure of one or more components. The exact estimating the failure rate of a component is important for efficient maintenance of a complex system. The lifetime data that can be obtained during the operation of the system is an important information representing the environment of system operation. Therefore, it is desirable to estimate the failure rate of components using the lifetime data. This research suggests the Bayesian estimation for the failure rate using lifetime data in competing risks model. We derive a likelihood function in both cases of which failures of components are independent and dependent. And then, Bayesian estimation process using the lifetime data is proposed with natural conjugate prior distribution. In case of independent components, the exponential distribution is used as a lifetime distribution of each components. In case of dependent components, Marshall and Olkin's bivariate exponential distribution is used as a lifetime distribution of the components. This research shows that it is possible to make use of a few of real-time lifetime data in estimating of the failure rate. Hence the result of this research can be used in determining relevant system maintenance policy. A basic complex system combined with series and parallel structure is studied in this research. Since the structure of this system is a basic one for a real complex system, the result of this research can be extended to the real complex system which consists of many components in a complex structure.
안선응,최현민 한국산업경영시스템학회 2006 한국산업경영시스템학회 학술대회 Vol.2006 No.추계
For leased equipments the lessor incurs penalty costs for failures occurring over the lease period and for not rectifying such failures within a specified time limit. Preventive maintenance action may reduce failures but increase preventive maintenance costs. This paper determines a periodic preventive maintenance policy for minimizing costs when repair time is proportional to the failure intensity function.
안선응,김우현 한국산업경영시스템학회 2008 한국산업경영시스템학회 학술대회 Vol.2008 No.추계
This paper is concerned with developing realistic models to determine preventive maintenance (PM) schedules for complex systems when data have been collected on failure times and PM interventions along with down times and man-hours expended on each. We propose the use of a proportional hazard model and consider the addition of Bayesian methods to incorporate prior knowledge about regression coefficients. The paper discusses further aspects of this approach, which include extending the model to cover time-dependent explanatory variables, and presents an application of the proportional hazard model to actual reliability data from major industrial plants.
안선응,김우현,양재철 한국경영학회 2007 한국경영학회 통합학술발표논문집 Vol.2007 No.8
This paper concerns the problem to determine the optimal agent disposition in a call center. We here assume that calling by customer is described by the Poisson distribution with the random parameter following a gamma distribution. This implies that the negative binomial distribution for agent disposition is obtained by mixing the mean of the Poisson distribution with a gamma distribution. This paper proposes an interpretation of the optimal agent disposition by considering the unknown Poisson parameter. In particular, the uncertainty of Poisson parameter comes from the irregularity of calling time interval.
안선응,박창순,장재영 한국경영학회 2007 한국경영학회 통합학술발표논문집 Vol.2007 No.8
투자를 희망하는 기업은 기술과 기업의 역량을 내세워 많은 투자와 적은 투자 보상을 희망하지만 투자자는 기술의 평가액과 기술사업의 역량을 기준으로 높은 수익과 회수위험을 낮추려고 하기 때문에 갈등의 요소와 협상의 문제가 존재한다. 투자를 희망하는 기업들의 권력(역량)에 따라서 투자량의 가치(회수위험)는 다르게 나타날 것이며 투자협상을 위한 기술기업 역량(권력)의 정량화 방법이 필요하다. 본 연구에서는 투자자가 여러 기술에 투자할 경우 기술기업의 역량을 고려한 권력지수와 이를 활용한 상대적 투자량 및 상대적 회수가치 추정방법을 제시하고 실제의 회수조건과 비교하여 기업의 역량에 따른 투자량 배분방법을 제안한다. 투자자와 투자를 받는 기업이 공감할 수 있고 투자의 회수위험을 작게 할 수 있는 기술투자 배분모형으로 활용되기를 기대한다.
안선응,양재철 한국산업경영시스템학회 2006 한국산업경영시스템학회 학술대회 Vol.2006 No.추계
Competing risks theory concerns the system of logical series structure consisted of several causes of failure. Based on competing risks theory, we derive the likelihood function of a combined of series and parallel structure using obtainable data such as times to failure, causes of failure, functioning or failed states of the system and its parts. A predictive model for the failure rate of each part is also built up by using the derived likelihood function. When additional data are available, it is shown that the failure rate can be updated by using the Bayesian approach.
안선응,박창순,남경훈,김택상 한국산업경영시스템학회 2004 한국산업경영시스템학회 학술대회 Vol.2004 No.춘계
Intrusion Detection System (IDS) is intended to detect anomalous usages or attacks on system and network. Even though many IDS models have been developed, they still may have problems, such as involvement of components contaminated by anomalous process, in detecting anomalous behavior patterns. To distinguish anomalous patterns from normal patterns, we propose a Bayesian approach which includes the presentation of the relations among normal pattern components.