• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.403-411
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• 2011

This paper deals with a group acceptance sampling plan for time truncated tests which are based on the total number of failures from the whole group assuming that the life time of an item follows the Dagum (inverse Burr) distribution. This study is developed when a multiple number of items as a group can be tested simultaneously in a tester. The minimum number of groups required for a given group size and acceptance number is determined such that the producer and consumer risks are satisfied simultaneously at the specified quality level, while the termination time and the number of testers are specified. Comparisons are made between the proposed plan and the existing plan on the basis of size of the groups. Two real examples are provided.

• Journal of Electrical Engineering and Technology
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• v.10 no.2
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• pp.641-646
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• 2015

In this paper, a zinc electrowinning cell is fully optimized to achieve a uniform current distribution at electrode surfaces. To effectively deal with an electromagnetically coupled problem with multi-dimensional design variables, a sampling-based sensitivity approach is combined with a highly tuned multiphysics simulation model. The model involves the interrelation between electrochemical reactions and electromagnetic phenomena so as to predict accurate current distributions in the electrowinning cell. In the sampling-based sensitivity approach, Kriging-based surrogate models are generated in a local window, and accordingly their sensitivity values are extracted. Such unique design strategy facilitates optimizing very complicated multiphysics and multi-dimensional design problems. Finally, ten design variables deciding the electrolytic cell structure are optimized, and then the uniformity of current distribution in the optimized cell is examined through the comparison with existing cell designs.

• Journal of Applied Reliability
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• v.4 no.1
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• pp.15-26
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• 2004

Life test is performed to set a confidence (lower) limit on the mean or median life of items if the number of failures at the end of the fixed time t does not exceed a given number c. Gupta(1962) propose a sampling plan for truncated life tests when the life distribution of an item is normal or lognormal distribution. In this paper, based on the result of Gupta(1962), we propose a sampling plan for failure rate test when an item has normal or lognormal life distribution. We assume that the shape parameter is known while the location parameter is unknown.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• Journal of the Korea Safety Management & Science
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• v.9 no.2
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• pp.123-134
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• 2007

This paper focuses on the in-house reliability assurance plan for the bulk materials of each company. The reliability assurance needs in essence a long time and high cost for testing the materials. In order to reduce the time and cost, accelerated life test is adopted. The bulk sampling technique was used for acceptance. Design parameters might be total sample size(segments and increments}, stress level and so on. We focus on deciding the sample size by minimizing the asymptotic variance of test statistics as well as satisfying the consumer's risk. In bulk sampling, we also induce the sample size by adapting the normal life time distribution model when the variable of the lognormal life time distribution is transformed and adapted to the model. In addition, the sample size for both the segments and increments can be induced by minimizing the asymptotic variance of test statistics of the segments and increments with consumer's risk met. We can assure the reliability of the mean life and B100p life time of the bulk materials by using the calculated minimum sample size.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.18 no.3
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• pp.177-184
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• 2008

The purpose of this study was to compare the performance characteristics of Andersen and total suspended particulate (TSP) samplers in terms of particle size distribution (PSD) and mass sampling efficiency. In the present study, two Andersen and four TSP samplers were selected and tested to quantitatively estimate human exposure to fly ash representing industrial particulate matter (PM) in a carefully controlled chamber. The PSD characteristics, a mass median aerodynamic diameter and a geometric standard deviation, were found from the sampled PM of airborne samplers in the chamber. An Andersen sampler was compared with a TSP sampler quantified by a coulter counter multisizer, as a reference sampler, to describe the correlation of mass sampling efficiencies between two types of samplers. Overall results indicate that Andersen samplers overestimated small PM due to particle bounce phenomena between impaction stages. There was reasonably good correlation ($R^2$ = 0.89 and 0.91) between the mass sampling efficiencies of Andersen and TSP samplers during the two tests. However, the lower values of slope (0.71 and 0.72) in two tests showed that the Andersen sampler underestimated PM (> AD $10.1\;{\mu}m$) with sufficient inertia due to a relatively lower Andersen inlet velocity at 0.8 m/s comparing with the operating air velocity at 2.1 m/s in the sampling zone of a chamber.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.546-558
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• 2015

Chord length sampling method in Monte Carlo simulations is a method used to model spherical particles with random sampling technique in a stochastic media. It has received attention due to the high calculation efficiency as well as user convenience; however, a technical issue regarding boundary effect has been noted. In this study, after analyzing the distribution characteristics of spherical particles using an explicit method, an alternative chord length sampling method is proposed. In addition, for modeling in finite media, a correction method of the boundary effect is proposed. Using the proposed method, sample probability distributions and relative errors were estimated and compared with those calculated by the explicit method. The results show that the reconstruction ability and modeling accuracy of the particle probability distribution with the proposed method were considerably high. Also, from the local packing fraction results, the proposed method can successfully solve the boundary effect problem. It is expected that the proposed method can contribute to the increasing of the modeling accuracy in stochastic media.

• Journal of the Korean Statistical Society
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• v.23 no.2
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• pp.421-444
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• 1994

Reliability acceptance sampling is concerned with whether to accept or reject a collection of items based upon the information obtained from life testing. Although various reliability acceptance sampling plans have been developed, little is known about their relatvie performances. This paper compares reliability acceptance sampling plans under Type II censoring, Hybrid censoring, and Time-Truncated Type II censoring assuming that the lifetimes of items in a lot follow an exponential distribution. The three plans are compared in terms of the power, the expected number of failures, and the expected time required to reach a decision. Computational experiments are conducted and the results are tabulated to provide guidelines for selecting an appropriate plan for a given situation.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.135-140
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• 2000

베이지안 신경망 모형(Bayesian Neural Networks Models)에서 주어진 입력값(input)은 블랙 박스(Black-Box)와 같은 신경망 구조의 각 층(layer)을 거쳐서 출력값(output)으로 계산된다. 새로운 입력 데이터에 대한 예측값은 사후분포(posterior distribution)의 기대값(mean)에 의해 계산된다. 주어진 사전분포(prior distribution)와 학습데이터에 의한 가능도함수(likelihood functions)를 통해 계산되어진 사후분포는 매우 복잡한 구조를 갖게 됨으로서 기대값의 적분계산에 대한 어려움이 발생한다. 이때 확률적 추정에 의한 근사 방법인 몬테칼로 적분을 이용한다. 이러한 방법으로서 Hybrid Monte Carlo 알고리즘은 우수한 결과를 제공하여준다(Neal 1996). 본 논문에서는 Hybrid Monte Carlo 알고리즘과 기존에 많이 사용되고 있는 Gibbs sampling, Metropolis algorithm, 그리고 Slice Sampling등의 몬테칼로 방법들을 비교한다.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.115-129
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• 1996

A reliability Acceptance Sampling Plan (RASP) is developed for testing the exponential mean lifetime under the periodic (i. e., equally-spaced) inspection and Type I censoring. Under the periodic inspection, the exact sampling distribution of maximum likelihood (ML) estimator of mean can not be derived. Hence sample size and acceptance criterion are determined by the algorithm proposed on the basis of Monte Carlo simulation such that the producer's and consumer's risks are satisfied for given censoring time and number of inspections. In addition, the developed RASP is compared in terms of sampling size, OC curve, and expected completion time. The effects for the RASP by the chosen inspection scheme are also discussed.