01454nam 2200421 a 450 991070324380332120110921084023.0(CKB)4970000000041697(OCoLC)753901565(EXLCZ)99497000000004169720110921d2011 ua 0engurmn|||||||||txtrdacontentcrdamediacrrdacarrierMilitary readiness[electronic resource] Navy's report to Congress on the impact of training and crew size on surface force material readiness /[Sharon L. Pickup]Washington, DC :U.S. Govt. Accountability Office,[2011]1 online resource (9 pages)Title from PDF title screen (viewed Aug. 24, 2011)."July 7, 2011.""GAO-11-746R."Includes bibliographical references.Military ReadinessMilitary readinessOperational readiness (Military science)National securityUnited StatesMilitary readiness.Operational readiness (Military science)National securityPickup Sharon L1381254United States.Government Accountability Office.GPOGPODOCUMENT9910703243803321Military readiness3453186UNINA03673nam 2200685 a 450 991043792800332120200520144314.0978128391062012839106249781447145134144714513510.1007/978-1-4471-4513-4(CKB)2670000000308612(EBL)1081725(OCoLC)822977298(SSID)ssj0000811449(PQKBManifestationID)11510758(PQKBTitleCode)TC0000811449(PQKBWorkID)10850208(PQKB)11741325(DE-He213)978-1-4471-4513-4(MiAaPQ)EBC1081725(PPN)16829365X(EXLCZ)99267000000030861220120820d2013 uy 0engur|n|---|||||txtccrMultivariate statistical process control process monitoring methods and applications /Zhiqiang Ge, Zhihuan Song1st ed. 2013.London ;New York Springerc20131 online resource (203 p.)Advances in industrial control,1430-9491Description based upon print version of record.9781447159896 1447159896 9781447145127 1447145127 Includes bibliographical references and index.Introduction -- 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.  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.Advances in Industrial Control,1430-9491Process controlMultivariate analysisProcess control.Multivariate analysis.658.5/62658.562658.56201519535Ge Zhiqiang1064380Song Zhihuan1752837MiAaPQMiAaPQMiAaPQBOOK9910437928003321Multivariate statistical process control4188323UNINA