000 03158nam a22004575i 4500
001 978-1-4471-4513-4
003 DE-He213
005 20200420221252.0
007 cr nn 008mamaa
008 121205s2013 xxk| s |||| 0|eng d
020 _a9781447145134
_9978-1-4471-4513-4
024 7 _a10.1007/978-1-4471-4513-4
_2doi
050 4 _aTJ212-225
072 7 _aTJFM
_2bicssc
072 7 _aTEC004000
_2bisacsh
082 0 4 _a629.8
_223
100 1 _aGe, Zhiqiang.
_eauthor.
245 1 0 _aMultivariate Statistical Process Control
_h[electronic resource] :
_bProcess Monitoring Methods and Applications /
_cby Zhiqiang Ge, Zhihuan Song.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _aXVIII, 194 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Industrial Control,
_x1430-9491
505 0 _aIntroduction -- An Overview of Conventional MSPC Methods -- Non-Gaussian Process Monitoring -- Fault Reconstruction and Identification -- Nonlinear Process Monitoring: Part I -- Nonlinear Process Monitoring: Part 2 -- Time-varying Process Monitoring -- Multimode Process Monitoring: Part 1 -- Multimode Process Monitoring: Part 2 -- Dynamic Process Monitoring -- Probabilistic Process Monitoring -- Plant-wide Process Monitoring: Multiblock Method -- Reference -- Index.
520 _a  Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality. Multivariate Statistical Process Control reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas.   Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers.
650 0 _aEngineering.
650 0 _aControl engineering.
650 1 4 _aEngineering.
650 2 4 _aControl.
700 1 _aSong, Zhihuan.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447145127
830 0 _aAdvances in Industrial Control,
_x1430-9491
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-4513-4
912 _aZDB-2-ENG
942 _cEBK
999 _c52635
_d52635