使用個別誤判誤差之單邊循序篩選程序之研究

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Title:	使用個別誤判誤差之單邊循序篩選程序之研究
Other Titles:	A Study on the One-Sided Screening Procedure Based on the Individual Misclassification Error
Authors:	吳淑妃
Contributors:	淡江大學統計學系
Date:	2011
Issue Date:	2012-05-07 13:41:08 (UTC+8)
Abstract:	有些產品的品質特性並不容易檢查，常因測量費用昂貴、檢驗耗時，或是產品具有破壞性、退化性等問題，因此往往不直接觀察表現變數，而是藉由觀察數個和表現變數有關的篩選變數，由它們來判定產品是否被接受，而此方法稱之為篩選程序，但也為了節省檢驗成本和檢驗時間，多站的循序篩選程序方法便因應而生。本研究第一年使用個別誤判誤差的概念，提出一修正的單邊循序篩選程序方法，和(Wu and Tsau (2002))舊的篩選程序不同的地方在於不需要先決定每個篩選變數之權數，所以將原來加權兩次的程序簡化成只需加權一次，且將和舊的程序做模擬比較. 我們同時考慮消費者成本及總檢查成本, 以其和提出一成本函數, 作為最佳篩選變數組合之選擇準則。我們將完成一Fortran程式語言算出每一種配置組合的AOQ值和TIC值和ETC值，以選出最佳的配置組合。最後，我們會舉出一實例，示範如何求出修正後循序篩選程序之最佳的配置組合。第二年則考慮三種品質成本函數針對單邊多站篩選程序，推導出一般化的公式並求其期望總成本，作為最佳篩選變數配置組合之選擇準則。最後, 我们會舉出一實例，示範如何對三種期望成本函數，分別求出修正後循序篩選程序之最佳的配置組合。. In many emerging markets, the problem of saving time effort and inspection cost for promoting competition ability without influencing their product quality has become a very important issue these days. In many practical cases, the manufacturers would not like to measure the performance variable Y directly. The screening problem to select items within a given specification based on the observed screening variables which are correlated with performance variable Y is thus arisen. In the first year, we want to propose a one-sided modified screening procedure to simplify the procedure of Tsai and Wu (2002) by only weighting the screening variables once instead of weighting twice. The numerical comparison of the modified procedure with the old procedure will be done in this study. A software program is developed to search the optimal allocation combination based on the criterion of minimum expected cost function. At last, a real-life example is given to illustrate the modified screening procedure. In the second year, we will consider three quality cost functions of Y and use them to construct three expected total costs as the criteria for selecting the optimal allocation combination. One real-life example will be given to demonstrate the proposed economic design.
Appears in Collections:	[Graduate Institute & Department of Statistics] Research Paper

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