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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Now showing 1 - 4 of 4
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    Making decisions in assessing process capability index C-pk
    (1999-07-01)
    Pearn, WL
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    Chen, KS
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    工業工程與管理學系
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    Department of Industrial Engineering and Management
    Process capability indices C-p, C-pk and C-pm have been used in manufacturing industries to provide a quantitative measure of process potential and performance. The formulae for these indices are easy to understand and straightforward to apply. However, since sample data must be collected in order to calculate these indices, a great degree of uncertainty may be introduced into capability assessments owing to sampling errors. Currently, most practitioners simply look at the value of the index calculated from the sample data and then make a conclusion on whether the given process meets the capability (quality) requirement. This approach is not reliable, since sampling errors are ignored. Cheng (Qual. Engng., 7, 239-259 (1994)) has developed a procedure involving estimators of C-p and C-pm for practitioners to use to determine whether a process meets the capability requirement or not. However, no procedure for C-pk was given, because difficulties were encountered in calculating the sampling distribution of the estimator of C-pk. In this paper we use a newly proposed estimator of C-pk to develop a procedure for practitioners to use so that decisions made in assessing process capability are more reliable. Copyright (C) 1999 John Wiley & Sons, Ltd.
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    A Note on "Capability Assessment for Processes with Multiple Characteristics: A Generalization of the Popular Index Cpk"
    (2013-03-01)
    Pearn, W. L.
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    Wu, C. H.
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    Tsai, M. C.
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    工業工程與管理學系
    ;
    Department of Industrial Engineering and Management
    The generalized yield index C-pk(T) establishes the relationship between the manufacturing specifications and the actual process performance, which provides a lower bound on process yield for two-sided processes with multiple characteristics. The results attended are very practical for industrial application. In this article, we extended the results in cases with one-sided specification and multiple characteristics. The generalized index C-PU(T) was considered, and the asymptotic distribution of the natural estimator (C)over-cap(PU)(T) was developed. Then, we derived the lower confidence bounds as well as the critical values of index C-PU(T). We not only provided some tables but also presented an application example. Copyright (c) 2012 John Wiley & Sons, Ltd.
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    An Extension of the Product Acceptance Determination for One-Sided Process with Multiple Characteristics
    (2013-03-01)
    Pearn, W. L.
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    Wu, C. H.
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    Hung, H. N.
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    Kao, C. M.
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    統計學研究所
    In statistical quality control, product acceptance determination is an important problem for producer and consumer. In practical, particularly more than one quality characteristic must be simultaneously considered to improve the product quality because of the product design. In this article, we investigate the lot sentencing problem for normally distributed process with one-sided specification and multiple characteristics. We not only provide a simple procedure to help practitioners make reliable decision easily but also tabulate the required sample size and the corresponding critical acceptance value for various producer's and consumer's risks with the capability requirements AQL (acceptable quality level) and LTPD (lot tolerance percent defective). Copyright (c) 2012 John Wiley & Sons, Ltd.
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    On the distribution of the inverted linear compound of dependent F-variates and its application to the combination of forecasts
    (2006-11-01)
    Liang, Kuo-Yuan
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    Lee, Jack C.
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    Shao, Kurt S. H.
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    交大名義發表
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    資訊管理與財務金融系 註：原資管所+財金所
    This paper establishes a sampling theory for an inverted linear combination of two dependent F-variates. It is found that the random variable is approximately expressible in terms of a mixture of weighted beta distributions. Operational results, including rth-order raw moments and critical values of the density are subsequently obtained by using the Pearson Type I approximation technique. As a contribution to the probability theory, our findings extend Lee & Hu's (1996) recent investigation on the distribution of the linear compound of two independent F-variates. In terms of relevant applied works, our results refine Dickinson's (1973) inquiry on the distribution of the optimal combining weights estimates based on combining two independent rival forecasts, and provide a further advancement to the general case of combining three independent competing forecasts. Accordingly, our conclusions give a new perception of constructing the confidence intervals for the optimal combining weights estimates studied in the literature of the linear combination of forecasts.