• Title, Summary, Keyword: Sequential Sampling

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Sensitivity Approach of Sequential Sampling for Kriging Model (민감도법을 이용한 크리깅모델의 순차적 실험계획)

  • Lee, Tae-Hee;Jung, Jae-Jun;Hwang, In-Kyo;Lee, Chang-Seob
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.11
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    • pp.1760-1767
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    • 2004
  • Sequential sampling approaches of a metamodel that sampling points are updated sequentially become a significant consideration in metamodeling technique. Sequential sampling design is more effective than classical space filling design of all-at-once sampling because sequential sampling design is to add new sampling points by means of distance between sampling points or precdiction error obtained from metamodel. However, though the extremum points can strongly reflect the behaviors of responses, the existing sequential sampling designs are inefficient to approximate extremum points of original model. In this research, new sequential sampling approach using the sensitivity of Kriging model is proposed, so that new approach reflects the behaviors of response sequentially. Various sequential sampling designs are reviewed and the performances of the proposed approach are compared with those of existing sequential sampling approaches by using mean squared error. The accuracy of the proposed approach is investigated against optimization results of test problems so that superiority of the sensitivity approach is verified.

Stochastically Dependent Sequential Acceptance Sampling Plans

  • Kim, Won-Kyung
    • Journal of the Korean Society for Quality Management
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    • v.25 no.3
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    • pp.22-38
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    • 1997
  • In a traditional sequential acceptance sampling plan, it is assumed that the sampled items are independent each other. In this paper, stochastically dependent sequential acceptance sampling plans are dealt when there exists dependency between sampled items. Monte-Calro algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in probability ratio sequential test can be found by using these probabilities. The formula for measures of performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. This research can be a, pp.ied to sequential sampling procedures in place of control charts where there is a recognized and necessary dependency during the production processes. Also, dependent multiple acceptance sampling plans can be derived by extending this sequential sampling procedure. As a numerical example, a Markov dependent process model is given, and the characteristics of the sampling plans are examined according to the change of the dependency factor.

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Single and Sequential Dependent Sampling Plans for the Polya Process Model (폴랴 과정 모델에 대한 단일 및 축차 종속 샘플링 계획법)

  • Kim, Won Kyung
    • Journal of Korean Institute of Industrial Engineers
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    • v.28 no.4
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    • pp.351-359
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    • 2002
  • In this paper, stochastically dependent single and sequential acceptance sampling plans are dealt when the process follows a Polya process model. A Monte-Cairo algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in a probability ratio sequential test can be found by using these probabilities. The formula to measure performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. Dependent multiple acceptance sampling plans can be derived by extending the sequential sampling procedure. In numerical examples, single and sequential sampling plans of a Polya dependent process are examined and the characteristics are compared according to the change of the dependency factor.

Sensitivity Approach of Sequential Sampling Using Adaptive Distance Criterion (적응거리 조건을 이용한 순차적 실험계획의 민감도법)

  • Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9
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    • pp.1217-1224
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    • 2005
  • To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

Sampling Inspection Plans for Defect

  • Jeong, Jeong-Im;Cho, Gyo-Young
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.867-877
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    • 2004
  • The sequential sampling inspection method is an extension of the multiple-sampling methods, and its theory is based on the sequential probability ratio test (SPRT) of Wald. In this paper, the characteristics of SPRT for testing the number of defects are approximated by using the estimated excess over the boundaries. The use of the estimated excess shows good performances in estimating the operating characteristic function and the average sample number of SPRT compared to the method by neglecting the excess. It also makes it possible to determine the boundary values which satisfy the desired error probabilities.

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A Study of Dependent Nonstationary Multiple Sampling Plans (종속적 비평형 다중표본 계획법의 연구)

  • 김원경
    • Journal of the Korea Society for Simulation
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    • v.9 no.2
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    • pp.75-87
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    • 2000
  • In this paper, nonstationary multiple sampling plans are discussed which are difficult to solve by analytical method when there exists dependency between the sample data. The initial solution is found by the sequential sampling plan using the sequential probability ration test. The number of acceptance and rejection in each step of the multiple sampling plan are found by grouping the sequential sampling plan's solution initially. The optimal multiple sampling plans are found by simulation. Four search methods are developed U and the optimum sampling plans satisfying the Type I and Type ll error probabilities. The performance of the sampling plans is measured and their algorithms are also shown. To consider the nonstationary property of the dependent sampling plan, simulation method is used for finding the lot rejection and acceptance probability function. As a numerical example Markov chain model is inspected. Effects of the dependency factor and search methods are compared to analyze the sampling results by changing their parameters.

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Sequential Feasible Domain Sampling of Kriging Metamodel by Using Penalty Function (벌칙함수 기반 크리깅메타모델의 순차적 유용영역 실험계획)

  • Lee Tae-Hee;Seong Jun-Yeob;Jung Jae-Jun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.6
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    • pp.691-697
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    • 2006
  • Metamodel, model of model, has been widely used to improve an efficiency of optimization process in engineering fields. However, global metamodels of constraints in a constrained optimization problem are required good accuracy around neighborhood of optimum point. To satisfy this requirement, more sampling points must be located around the boundary and inside of feasible region. Therefore, a new sampling strategy that is capable of identifying feasible domain should be applied to select sampling points for metamodels of constraints. In this research, we suggeste sequential feasible domain sampling that can locate sampling points likely within feasible domain by using penalty function method. To validate the excellence of feasible domain sampling, we compare the optimum results from the proposed method with those form conventional global space-filling sampling for a variety of optimization problems. The advantages of the feasible domain sampling are discussed further.

Cumulative Sequential Control Charts with Sample Size Bound (표본크기에 제약이 있는 누적 축차관리도)

  • Chang, Young-Soon;Bai, Do-Sun
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.4
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    • pp.448-458
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    • 1999
  • This paper proposes sequential control charts with an upper bound on sample size. Existing sequential control charts have no restriction on the number of observations at a sampling point. For situations where sampling and testing an item is time-consuming or expensive, sequential control charts may not be directly applied. When the number of observations in a sampling point reaches the upper bound and there is no out-of-control signal, the proposed cumulative sequential control chart defers the decision to the next sampling point of which starting value is the value of the current statistic. Two Markov chains, inner and outer chains, are used to derive the formulas for evaluating the performance of the proposed chart. It is compared with $\bar{X}$ and cumulative sum control charts with fixed and variable sample sizes. The fast initial response (FIR) feature is studied. Guidelines for the design of the proposed charts are also given.

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Candidate Points and Representative Cross-Validation Approach for Sequential Sampling (후보점과 대표점 교차검증에 의한 순차적 실험계획)

  • Kim, Seung-Won;Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.1
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    • pp.55-61
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    • 2007
  • Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

An accelerated sequential sampling for estimating the reliability of N-parallel systems

  • Rekab, Kamel;Cheng, Yuan
    • International Journal of Reliability and Applications
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    • v.14 no.2
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    • pp.71-78
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    • 2013
  • The problem of designing an experiment to estimate the reliability of a system that has N subsystems connected in series where each subsystem n has n $T_n$ components connected in parallel is investigated both theoretically and by simulation. An accelerated sampling sheme is introduced. It is shown that the accelerated sampling scheme is asymptotically optimal as the total number of units goes to infinity. Numerical comparisons for a system that has two subsystems connected in series where each subsystem has two components connected in parallel are also given. They indicate that the accelerated sampling scheme performs better than the batch sequential sampling scheme and is nearly optimal.

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