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001 286866
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008 150903s2013 xxk| o |||| 0|eng d
020 _a9781447145134
_99781447145134
024 7 _a10.1007/9781447145134
_2doi
035 _avtls000339842
039 9 _a201509030319
_bVLOAD
_c201404300406
_dVLOAD
_y201402060945
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTJ212-225
100 1 _aGe, Zhiqiang.
_eautor
_9315781
245 1 0 _aMultivariate Statistical Process Control :
_bProcess Monitoring Methods and Applications /
_cby Zhiqiang Ge, Zhihuan Song.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _axviii, 193 páginas 90 ilustraciones, 25 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aAdvances in Industrial Control,
_x1430-9491
500 _aSpringer eBooks
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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aSong, Zhihuan.
_eautor
_9315782
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781447145127
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4471-4513-4
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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