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Statistical monitoring of complex multivariate processes = with applications in industrial process control /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Statistical monitoring of complex multivariate processes/ Uwe Kruger and Lei Xie.
其他題名:	with applications in industrial process control /
作者:	Kruger, Uwe.
其他作者:	Xie, Lei.
出版者:	Chichester, West Sussex, U.K. :Wiley, : 2012.,
面頁冊數:	1 online resource (xxix, 437 p.) :ill. :
標題:	Multivariate analysis. -
電子資源:	http://onlinelibrary.wiley.com/book/10.1002/9780470517253
ISBN:	9780470517253 (electronic bk.)

Statistical monitoring of complex multivariate processes = with applications in industrial process control /
Kruger, Uwe.

Statistical monitoring of complex multivariate processeswith applications in industrial process control /[electronic resource] :Uwe Kruger and Lei Xie. - Chichester, West Sussex, U.K. :Wiley,2012. - 1 online resource (xxix, 437 p.) :ill. - Statistics in practice. - Statistics in practice..

Includes bibliographical references and index.

"The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statistical techniques lies in its simplicity and adaptability for developing monitoring applications. In contrast, competitive model, signal or knowledge based techniques showed their potential only whenever cost-benefit economics have justified the required effort in developing applications. Statistical Monitoring of Complex Multivariate Processes presents recent advances in statistics based process monitoring, explaining how these processes can now be used in areas such as mechanical and manufacturing engineering for example, in addition to the traditional chemical industry."--

ISBN: 9780470517253 (electronic bk.)

Standard No.: 9786613862228

LCCN: 2012023036Subjects--Topical Terms:

577402
Multivariate analysis.

LC Class. No.: QA278 / .K725 2012

Dewey Class. No.: 519.5/35

Statistical monitoring of complex multivariate processes = with applications in industrial process control /
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245 1 0 $a Statistical monitoring of complex multivariate processes $h [electronic resource] : $b with applications in industrial process control / $c Uwe Kruger and Lei Xie.
260 $a Chichester, West Sussex, U.K. : $b Wiley, $c 2012.
300 $a 1 online resource (xxix, 437 p.) : $b ill.
490 1 $a Statistics in practice
504 $a Includes bibliographical references and index.
520 $a "The development and application of multivariate statistical techniques in process monitoring has gained substantial interest over the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complex systems, such techniques have been refined and applied in various engineering areas, for example mechanical and manufacturing, chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statistical techniques lies in its simplicity and adaptability for developing monitoring applications. In contrast, competitive model, signal or knowledge based techniques showed their potential only whenever cost-benefit economics have justified the required effort in developing applications. Statistical Monitoring of Complex Multivariate Processes presents recent advances in statistics based process monitoring, explaining how these processes can now be used in areas such as mechanical and manufacturing engineering for example, in addition to the traditional chemical industry."-- $c Provided by publisher.
588 $a Description based on online resource; title from digital title page (viewed on Oct. 30, 2012).
650 0 $a Multivariate analysis. $3 577402
700 1 $a Xie, Lei. $3 1059604
830 0 $a Statistics in practice. $3 632422
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