東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

The performance of multivariate qual...

Wu, Chen-Hsiang.

FindBook

Google Book

Amazon

博客來

The performance of multivariate quality-control charts for autocorrelated bivariate data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The performance of multivariate quality-control charts for autocorrelated bivariate data./
作者:	Wu, Chen-Hsiang.
面頁冊數:	35 p.
附註:	Source: Masters Abstracts International, Volume: 44-06, page: 2830.
Contained By:	Masters Abstracts International44-06.
標題:	Applied Mechanics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1436361
ISBN:	9780542728471

The performance of multivariate quality-control charts for autocorrelated bivariate data.
Wu, Chen-Hsiang.

The performance of multivariate quality-control charts for autocorrelated bivariate data. - 35 p.

Source: Masters Abstracts International, Volume: 44-06, page: 2830.

Thesis (M.S.)--University of Maryland, College Park, 2006.

To monitor the mass production process, several quality control charts are constructed. Two of the most recognized schemes are the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) schemes. Originally, we assume that the observations from the production process are independent. However, sometimes the observations are autocorrelated. In this article, a vector autoregressive model VAR (m) is applied. Here we want to study the impact of autocorrelations on both schemes. We also want to know about which scheme is more efficient when the observations are autocorrelated.

ISBN: 9780542728471Subjects--Topical Terms:

1018410
Applied Mechanics.

The performance of multivariate quality-control charts for autocorrelated bivariate data.
LDR:01482nmm 2200265 4500 001 1834625
005 20071127114957.5
008 130610s2006 eng d
020 $a 9780542728471
035 $a (UMI)AAI1436361
035 $a AAI1436361
040 $a UMI $c UMI
100 1 $a Wu, Chen-Hsiang. $3 1923265
245 1 4 $a The performance of multivariate quality-control charts for autocorrelated bivariate data.
300 $a 35 p.
500 $a Source: Masters Abstracts International, Volume: 44-06, page: 2830.
500 $a Adviser: Paul Zantek.
502 $a Thesis (M.S.)--University of Maryland, College Park, 2006.
520 $a To monitor the mass production process, several quality control charts are constructed. Two of the most recognized schemes are the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) schemes. Originally, we assume that the observations from the production process are independent. However, sometimes the observations are autocorrelated. In this article, a vector autoregressive model VAR (m) is applied. Here we want to study the impact of autocorrelations on both schemes. We also want to know about which scheme is more efficient when the observations are autocorrelated.
590 $a School code: 0117.
650 4 $a Applied Mechanics. $3 1018410
690 $a 0346
710 2 0 $a University of Maryland, College Park. $3 657686
773 0 $t Masters Abstracts International $g 44-06.
790 1 0 $a Zantek, Paul, $e advisor
790 $a 0117
791 $a M.S.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1436361