• Title/Summary/Keyword: Distribution of sample quality

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Model Classification of Quality Statistics Using Block Repeated Measures (블록 반복측정을 이용한 품질통계 모형의 유형화)

  • Choi, Sung-Woon
    • Journal of the Korea Safety Management & Science
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    • v.9 no.3
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    • pp.165-171
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    • 2007
  • Dependent models in quality statistics are classified as serially autocorrelated model, multivariate model and dependent sample model. Dependent sample model is most efficient in time and cost to obtain samples among the above models. This paper proposes to implement parametric and nonparametric models into production system depended on demand pattern. Nonparametric models have distribution free and asymptotic distribution free techniques. Quality statistical models are classified into two categories ; the number of dependent sample and the type of data. The type of data consists of nominal, ordinal, interval and ratio data. The number of dependent sample divides into 2 samples and more than 3 samples.

Cusum Control Chart for Monitoring Process Variance (공정분산 관리를 위한 누적합 관리도)

  • Lee, Yoon-Dong;Kim, Sang-Ik
    • Journal of Korean Society for Quality Management
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    • v.33 no.3
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    • pp.149-155
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    • 2005
  • Cusum control chart is used for the purpose of controling the process mean. We consider the problem related to cusum chart for controling process variance. Previous researches have considered the same problem. The main difficulty shown in the related researches was to derive the ARL function which characterizes the properties of the chart. Sample variance, differently with sample mean, follows chi-squared type distribution, even when the quality characteristics are assumed to be normally distributed. The ARL function of cusum is described by a type of integral equation. Since the solution of the integral equation for non-normal distribution is not known well, people used simulation method instead of solving the integral equation directly, or approximation method by taking logarithm of the sample variance. Recently a new method to solve the integral equation for Erlang distribution was published. Here we consider the steps to apply the solution to the problem of controling process variance.

Cusum control chart for monitoring process variance (공정분산 관리를 위한 누적합 관리도)

  • Lee, Yoon-Dong;Kim, Sang-Ik
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2006.04a
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    • pp.135-141
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    • 2006
  • Cusum control chart is used for the purpose of controling the process mean. We consider the problem related to cusum chart for controling process variance. Previous researches have considered the same problem. The main difficulty shown in the related researches was to derive the ARL function which characterizes the properties of the chart. Sample variance, differently with sample mean, follows chi-squared type distribution, even when the quality characteristics are assumed to be normally distributed. The ARL function of cusum is described by a type of integral equation. Since the solution of the integral equation for non-normal distribution is not known well, people used simulation method instead of solving the integral equation directly, or approximation method by taking logarithm of the sample variance. Recently a new method to solve the integral equation for Erlang distribution was published. Here we consider the steps to apply the solution to the problem of controling process variance.

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A Study on Small-Sample Inspection Plan for New Product Quality Evaluation of Finite Population (유한모집단의 신제품 품질평가를 위한 소표본 샘플링검사 방법에 대한 소고)

  • Byun, Jai-Hyun;Shin, Byung-Cheol;Lee, Chang-Woo
    • Journal of Korean Institute of Industrial Engineers
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    • v.41 no.1
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    • pp.115-120
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    • 2015
  • Evaluating product quality level is necessary before the manufactured items are delivered to the customer. When the amount of the items to be manufactured is limited and the product is of high price and should be evaluated by destructive testing, the number of samples to be tested should be as small as possible. This paper presents a small-sample inspection method using hyper-geometric distribution and Bayesian approach for finite small-sized population. A method of determining the minimum sample size is presented for given population size, allowable number of defectives, warranteed defective level, and confidence level which is the degree of confidence on the product quality level recognized by both the producer and the customer.

Measuring Level of Difficulty of Fingerprint Database based on Sample Quality (영상 품질 기반의 지문 데이터베이스의 난이도 정량화)

  • Ryu, Ji-Eun;Jang, Ji-Hyeon;Kim, Hak-Il
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.5
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    • pp.59-69
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    • 2008
  • The purpose of this paper is to measure the level of difficulty of fingerprint database based on sample quality. This paper proposes distribution of a sample quality analyzer and a difference of sample quality analyzer to measure the level of difficulty. Experimental results demonstrate that there are stronger correlation between matching performance and level of difficulty based on difference of sample quality than other measure. Especially, level of difficulty based on OQ Block of MPQ co-occurrence matrix shows highest correlation with matching performance, and moreover it can predict the matching performance of unknown databases.

A New Test for New Better than Used Class (NBU에 대한 지수성 검정법에 관한 연구)

  • Kim, Hwan-Joong
    • Journal of Korean Society for Quality Management
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    • v.27 no.2
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    • pp.143-151
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    • 1999
  • In this thesis, a new test statistic is proposed for testing exponentiality against New Better than Used (NBU) alternatives. Our test statistic, which is based on a quadratic function of the order statistics from the sample, is readily applied in the case of small sample. Also, Our test statistic is more simple than the test statistic of Hollander and Proschan(1972).

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An Accelerated Test Acceptance Control Chart for Process Quality Assurance (공정보증을 위한 가속시험 합격판정 관리도)

  • Kim Jong Gurl
    • Journal of the Korea Safety Management & Science
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    • v.1 no.1
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    • pp.123-134
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    • 1999
  • There are several models for process quality assurance by quality system (ISO 9000), process capability analysis, acceptance control chart and so on. When a high level process capability has been achieved, it takes a long time to monitor the process shift, so it is sometimes necessary to develop a quicker monitoring system. To achieve a quicker quality assurance model for high-reliability process, this paper presents a model for process quality assurance when the fraction nonconforming is very small. We design an acceptance control chart based on variable quality characteristic and time-censored accelerated testing. The distribution of the characteristics is assumed to be normal or lognormal with a location parameter of the distribution that is a linear function of a stress. The design parameters are sample size, control limits and sample proportions allocated to low stress. These paramaters are obtained under minimization of the relative variance of the MLE of location parameter subject to APL and RPL constraints.

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Model for Process Quality Assurance When the Fraction Nonconforming is Very Small (극소불량 공정보증을 위한 모형연구)

  • Jong-Gurl Kim
    • Proceedings of the Safety Management and Science Conference
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    • 1999.11a
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    • pp.247-257
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    • 1999
  • There are several models for process quality assurance by quality system(ISO 9000), process capability analysis, acceptance control chart and so on. When a high level process capability has been achieved, it takes a long time to monitor the process shift, so it is sometimes necessary to develop a quicker monitoring system. To achieve a quicker quality assurance model for high-reliability process, this paper presents a model for process quality assurance when the fraction nonconforming is very small. We design an acceptance control chart based on variable quality characteristic and time-censored accelerated testing. The distribution of the characteristics is assumed to be normal of lognormal with a location parameter of the distribution that is a linear function of a stress. The design parameters are sample size, control limits and sample proportions allocated to low stress. These parameters are obtained under minimization of the relative variance of the MLE of location parameter subject to APL and RPL constraints.

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Website Quality, E-satisfaction, and E-loyalty of Users Based on The Virtual Distribution Channel

  • PANDJAITAN, Dorothy R.H.;Mahrinasari, MS.;HADIANTO, Bram
    • Journal of Distribution Science
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    • v.19 no.7
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    • pp.113-121
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    • 2021
  • Purpose: Technology induces the virtual distribution channel to exist, especially for booking a room online. This situation, indeed, provides an alternative for the customers to book based on their budget through digital platforms. One platform offering competitive prices is virtual hotel operators, such as Airbnb, OYO, RedDoorz, and Airy Rooms. Preferably, after using their platform, the user should be satisfied and loyal. Hence, this investigation aims to prove some associations. The first is between e-satisfaction and e-loyalty. The second is between website quality and e-satisfaction. The final is between website quality and e-loyalty. Research design, data, and methodology: This study is quantitatively designed with the sample of 350 users of the virtual hotel operator applications in Bandar Lampung: Airbnb, OYO, RedDoorz, and Airy, as the samples. Therefore, by denoting this sample size, the structural equation model based on covariance is utilized to examine the three hypotheses proposed. Also, to get the responses, this study uses a survey through a questionnaire. Result: This investigation demonstrates the positive relationship between e-satisfaction and e-loyalty. Additionally, website quality positively associates with e-satisfaction and e-loyalty. Conclusion: The virtual hotel operators must have the superiority on their website-based application to update the information based on the room availability and price, ensure online transaction safety, and facilitate its utilization to maintain long-term satisfaction and loyalty virtually.

A Heuristic Methodology for Fault Diagnosis using Statistical Patterns

  • Kwon, Young-il;Song, Suh-ill
    • Journal of Korean Society for Quality Management
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    • v.21 no.2
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    • pp.17-26
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    • 1993
  • Process fault diagnosis is a complicated matter because quality control problems can result from a variety of causes. These causes include problems with electrical components, mechanical components, human errors, job justification errors, and air conditioning influences. In order to make the system run smoothly with minimum delay, it is necessary to suggest heuristic remedies for the detected faults. Hence, this paper describes a heuristic methodology of fault diagnosis that is performed using statistical patterns generated by quality characteristics The proposed methodology is described briefly as follows: If a sample pattern generated by random variables is similar to the number of prototype patterns, the sample pattern may be matched by any prototype pattern among them to be resembled. This concept is based on the similarity between a sample pattern and the matched prototype pattern. The similarity is calculated as the weighted average of squared deviation, which is expressed as the difference between the relative values of standard normal distribution to be transformed by the observed values of quality characteristics in a sample pattern and the critical values of the corresponding ones in a matched prototype pattern.

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