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Methods for monitoring fractionally ...

Lanning, Jeffrey Wayne.

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Methods for monitoring fractionally sampled multiple stream processes.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Methods for monitoring fractionally sampled multiple stream processes./
Author:	Lanning, Jeffrey Wayne.
Description:	197 p.
Notes:	Adviser: Douglas C. Montgomery.
Contained By:	Dissertation Abstracts International59-06B.
Subject:	Engineering, Industrial. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9837682
ISBN:	0591913259

Methods for monitoring fractionally sampled multiple stream processes.
Lanning, Jeffrey Wayne.

Methods for monitoring fractionally sampled multiple stream processes. - 197 p.

Adviser: Douglas C. Montgomery.

Thesis (Ph.D.)--Arizona State University, 1998.

This study considers multiple stream systems where it is possible to monitor only a fraction of the total streams at a given time. This situation is of interest in those processes where the speed of production is great and includes a large number of streams, but the ability to monitor the process is not fully automated and unable to keep up with the speed of production.

ISBN: 0591913259Subjects--Topical Terms:

626639
Engineering, Industrial.

Methods for monitoring fractionally sampled multiple stream processes.
LDR:02874nam 2200313 a 45 001 937786
005 20110511
008 110511s1998 eng d
020 $a 0591913259
035 $a (UnM)AAI9837682
035 $a AAI9837682
040 $a UnM $c UnM
100 1 $a Lanning, Jeffrey Wayne. $3 1261641
245 1 0 $a Methods for monitoring fractionally sampled multiple stream processes.
300 $a 197 p.
500 $a Adviser: Douglas C. Montgomery.
500 $a Source: Dissertation Abstracts International, Volume: 59-06, Section: B, page: 2975.
502 $a Thesis (Ph.D.)--Arizona State University, 1998.
520 $a This study considers multiple stream systems where it is possible to monitor only a fraction of the total streams at a given time. This situation is of interest in those processes where the speed of production is great and includes a large number of streams, but the ability to monitor the process is not fully automated and unable to keep up with the speed of production.
520 $a A method for determining the probability of detecting a shift from target of any fraction of the streams (including none of the streams) is presented. In addition to the mathematics involved in computing this detection probability, a computer program is given which automates the process and quickly gives a result for any number of streams allowing an infinite number of combinations of stream shift scenarios to be examined Results from several of these scenarios are tabulated and graphed.
520 $a Adaptive approaches to system monitoring are applied to multiple stream processes in general and the fractional sampling problem specifically. This represents the first application of adaptive techniques to multiple stream processes. The average time to signal for an adaptively-monitored, fractionally-sampled multiple stream process is developed using a Markov chain procedure. The average time-to-signal results are used to identify promising adaptive sampling schemes for monitoring multiple stream processes using fractional samples. The adaptive fraction approach is shown to give superior results to the fixed fraction scheme and often yields satisfactory results compared with those obtained by sampling all the streams involved in a process.
520 $a Monitoring the variance of the fractionally sampled stream average is shown to provide protection against situations where only one, or just a few streams shift, rather than all the streams in the system. Finally an in depth example is provided by means of a case study where the methods described in this study are applied.
590 $a School code: 0010.
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Engineering, System Science. $3 1018128
690 $a 0546
690 $a 0790
710 2 0 $a Arizona State University. $3 1017445
773 0 $t Dissertation Abstracts International $g 59-06B.
790 $a 0010
790 1 0 $a Montgomery, Douglas C., $e advisor
791 $a Ph.D.
792 $a 1998
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9837682