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사용현장 데이터를 이용한 군 운용 환경에서의 상용품목 신뢰도 예측
임태진,박준수,고병성,성인철,조문수,김성철,Lim, Tae-Jin,Park, Joon-Soo,Ko, Byoung-Sung,Sung, In-Chul,Cho, Moon-Soo,Kim, Sung-Chul 한국국방경영분석학회 2010 한국국방경영분석학회지 Vol.36 No.1
상용품목을 군용환경에서 적용하면 저비용, 빠른 조달시간, 기술적 발전 등 여러 가지 이점이 있다. 반면에 상용 제품, 표준, 관행 등이 군용 요구조건에 미달됨으로 인하여 신뢰도 및 병참 상의 문제가 발생할 수도 있다. 또한 상용 공급자들은 군용 병참을 지원하는데 필요한 기술적 자료를 제공한 경험이 거의 없을 수도 있다. 보다 많은 회사들이 제품 관련 데이터 수집 시스템을 구축하고 있어 상당한 분량의 사용현장 보증 데이터가 수집되었다. 사용현장 데이터는 전형적으로 주기별 판매량과 클레임 건수로 구성된다. 본 연구에서는 군용환경에서 작동하는 군용설비, 군용환경에서 작동하는 상용설비, 상용환경에서 작동하는 상용설비 등 세 가지 유형의 데이터를 고려하였다. 최대우도 기준 및 최소제곱 기준에 기초한 제품 신뢰도 추정 방법을 제안하고, 각 유형의 데이터에 대한 추정 모형을 구축하고 상용환경에서 군용환경으로 전환하는 신뢰도 변환방법을 제안하였다. 사례연구를 통하여 제안된 방법의 적용 가능성을 검증하였다. Adapting commercial equipments to military operations may provide the advantage of low cost, reduced acquisition time, and technology advancement. On the other hand, it may also offer the opportunity for a reliability and logistics risk because commercial products, standards, and practices may not meet military requirements. In addition to this, commercial vendors have little experience in providing the technical data required to support military deployment logistics. As more companies are equipped with data aquisition systems for their products, considerable amount of field warranty data has been accumulated. Typically, the field data for a given product comprise with the sales volume and the number of the claims for each period. Three types of product data are considered in this study: military designed equipment operating in a military environment, commercial equipment operating in a military environment, and commercial equipment operating in a commercial environment. We construct a estimation model for each type of data and propose an reliability transform method from a commercial environment to a military environment. Parametric methods for estimating the product reliability are proposed based on maximum likelihood criteria and least square criteria. Then a reliability transform procedure for handling different types of data is proposed in a consistent fashion. A case study is investigated to characterize our model based on a real field warranty data set.
임태진 ( Tae Jin Lim ) 한국품질경영학회 2004 품질경영학회지 Vol.32 No.4
The synthetic control chart (SCC) proposed by Wu and Spedding (2000) is to detect shifts in the process mean. The performance was re-evaluated by Davis and Woodall (2002), and the steady-state average run length (ARL) performance was shown to be inferior to cumulative sum (CUSUM) or exponentially weighted moving average (EWMA) chart. This paper proposes a simple adaptive scheme to improve the performance of the synthetic control chart. That is, once a non-conforming (NC) sample occurs, we investigate the next L-consecutive samples with larger sample sizes and shorter sampling intervals. We employ a Markov chain model to derive the ARL and the average time to signal (ATS). We also propose a statistical design procedure for determining decision variables. Comprehensive comparative study shows that the proposed control chart is uniformly superior to the original SCC or double sampling (DS) X ̄ chart and comparable to the EWMA chart in ATS performance.
임태진 ( Tae Jin Lim ) 한국품질경영학회 2007 품질경영학회지 Vol.35 No.1
This paper investigates the average run length (ARL) of a selectively moving average (S-MA) control chart. The S-MA chart is designed to detect shifts in the process mean. The basic idea of the S-MA chart is to accumulate previous samples selectively in order to increase the sensitivity. The ARL of the S-MA chart was shown to be monotone decreasing with respect to the decision length in a previous research[3]. This paper derives the steady-state ARL in a closed-form and shows that the monotone property is resulted from head-start assumption. The steady-state ARL is shown to be a sum of head-start ARL and an additional term. The statistical design procedure for the S-MA chart is revised according to this result. Sensitivity study shows that the steady-state ARL performance is still better than the CUSUM chart or the Exponentially Weighted Moving Average (EWMA) chart.
포괄적 누적 충격 공통원인고장 모형 및 시스템 신뢰도 평가
임태진 ( Tae Jin Lim ) 한국품질경영학회 2011 품질경영학회지 Vol.39 No.2
This research proposes comprehensive models for analyzing common cause failures (CCF) due to cumulative shocks and to assess system reliability under the CCF. The proposed cumulative shock models are based on the binomial failure rate (BFR) model. Six kinds of models are proposed so as to explain diverse cumulative shock phenomena. The models are composed of the initial failure probability, shape parameter, and the total shock number. Some parameters of the proposed models can not be explicitly estimated, so we adopt the Expectation-maximization (EM) algorithm in order to obtain the maximum likelihood estimator (MLE) for the parameters. By estimating the parameters for the cumulative shock models, the system reliability with CCF can be assessed sequentially according to the number of cumulative shocks. The result can be utilizes in dynamic probabilistic safety assessment (PSA), aging studies, or risk management for nuclear power plants. Replacement or maintenance policies can also he developed based on the proposed model.
적응형 이동평균(A-MA) 관리도의 경제적-통계적 설계
임태진(Tae-Jin Lim) 대한산업공학회 2008 대한산업공학회지 Vol.34 No.3
This research proposes a method for economic-statistical design of adaptive moving average (A-MA) charts. The basic idea of the A-MA chart is to accumulate previous samples selectively in order to increase the sensitivity. The A-MA chart is a kind of adaptive chart such as the variable sampling size (VSS) chart. A major advantage of the A-MA chart over the VSS chart is that it is easy to maintain rational subgroups by using the fixed sampling size. A steady state cost rate function is constructed based on Lorenzen and Vance (1986) model. The cost rate function is optimized with respect to five design parameters. Computational experiments show that the A-MA chart is superior to the VSS chart as well as to the Shewhart chart in the economic-statistical sense.