利用上記錄值樣本對雙參數指數分配之多重品質特性之整體績效評估

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Title:	利用上記錄值樣本對雙參數指數分配之多重品質特性之整體績效評估
Other Titles:	The evaluation of the performance index of multi-quality characteristic for the two-parameter exponential distribution based on the upper record values sample
Authors:	陳宛菁;Chen, Wan-Ching
Contributors:	淡江大學統計學系碩士班吳淑妃
Keywords:	上記錄值樣本;雙參數指數分配;均勻最小變異數不偏估計量;製程能力指標;多重績效指標;檢定演算程序;六標準差;Upper record values sample;Two-parameter exponential distribution;Uniformly minimum variance unbiased estimator;Process Capability Indices;Multi-process performance index (MPPI);Testing algorithmic procedure;Six Sigma.
Date:	2011
Issue Date:	2011-12-28 18:24:45 (UTC+8)
Abstract:	在工業製程裡，產品大多有多個品質特性變數，本研究考慮的產品有t個望大型品質特性(如壽命時間)，在獨立和相依的情形下，分別提出多重績效指標（Multi-process performance index, MPPI）CT* 和CT 。假設每個品質特性皆服從雙參數指數分配，利用第i個望大型品質特性之上記錄值樣本，i=1,...,t，我們可推導出CT的均勻最小變異數不偏估計量及CT的最大概似估計量。在給定整體良品率下，可求得對應的CT和CT 目標值，當產品的多重品質特性為互相獨立和相依兩種情況時，在顯著水準alpha下，我們分別發展出一個檢定演算程序來檢定多重績效指標值是否大於CT和CT之目標值。此外，六標準差的概念也會應用於本文中。最後，本文使用兩個數值實例來示範本文提出的檢定演算程序，以評估產品的整體績效是否達到所要求的水準。 In industries, a product usually has multiple quality characteristics. To evaluate the performance of production process for products with t larger-the-better type quality characteristics (such as lifetime ), we propose a multi-process performance index (MPPI) CT for independence case and CT for dependence case. Suppose that each quality characteristic follows a two-parameter exponential distribution. Based on the upper record values samples from the ith larger-the-better type quality characteristic, i=1,...,t , we derive the uniformly minimum variance unbiased estimator for CT* and the maximum likelihood estimator for CT. Given the specified overall conforming rate, we can find the target value for CT* and CT. To test if CT* or CT exceeds the target value, a testing algorithm is developed at level alpha. The concept of Six sigma is also applied in this paper. At last, two numerical examples are used to illustrate the proposed testing procedure to assess if the multi-processes reach the required level for independence case and dependence case respectively.
Appears in Collections:	[Graduate Institute & Department of Statistics] Thesis

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