淡江大學機構典藏:Item 987654321/87688
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    Title: 多重製程產品的新製程能力指標
    Other Titles: A new process capability index for a multi-process product
    Authors: 林靜幼;Lin, Ching-Yu
    Contributors: 淡江大學統計學系碩士班
    吳淑妃;Wu, Shu-Fei
    Keywords: 多重製程能力指標;製程能力指標;相依多重製程能力分析圖;相依非常態多重製程能力分析圖;常態分配;非常態分配;Multi-process capability index;Process Capability Index;Dependent multi-process capability analysis chart;Dependent non-normal multi-process capability analysis chart;Normal distribution;Non-normal distribution
    Date: 2012
    Issue Date: 2013-04-13 11:32:55 (UTC+8)
    Abstract: Chen et al. (2006) 提出在常態分配下的多重製程能力指標CT和非常態分配下的多重製程能力指標NT,而他們的指標是在多重製程或多個品質特性皆獨立的假設下導出的。然而,大部分產品的多重製程或多個品質特性是相依的,在此情形下,本研究提出在常態分配下的多重製程能力指標CT*和非常態分配下的多重製程能力指標NT*,對新的多重製程能力指標,我們發展出在常態分配下的相依多重製程能力分析圖( Dependent multi-process capability analysis chart;DMPCAC)和非常態分配下的相依非常態多重製程能力分析圖( Dependent non-normal multi-process capability analysis chart;DNMPCAC),使用者可藉由這些圖的分析去檢定整體製程能力是否達到預定的能力水準,若沒有達到,亦可判斷出哪些單一製程或單一品質特性需要做進一步的改善以提升整體製程能力。最後,我們舉出四個實例來示範如何使用本研究提出的檢定程序,去決定整體製程是否是有能力的。
    Chen et al. (2006) proposed a flow path to evaluate the process capability of an entire product composed of multiple independent process characteristics based on a multi-process capability index CT in a normal distribution and NT in a non-normal distribution. But, the multiple process characteristics or quality characteristics of most products are dependent. In this case, we propose a multi-process capability index CT* in a normal distribution and NT* in a non-normal distribution in this paper. We also develop the dependent multi-process capability analysis chart (DMPCAC) model to evaluate process capability in a normal distribution and the dependent non-normal multi-process capability analysis chart (DNMPCAC) to evaluate process capability in a non-normal distribution based on the proposed new multi-process capability indices. Based on the analysis of these charts, users can determine if the multi-process capability reaches a pre-assigned level. Users can also identify which quality characteristic is needed to be improved to upgrade the whole process. At last, four practical examples are given to illustrate the use of this testing algorithmic procedure to determine whether the process is capable.
    Appears in Collections:[Graduate Institute & Department of Statistics] Thesis

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