Predictive condition monitoring of industrial systems for improved maintenance and operation [PDF]
, 2014 Maintenance strategies based on condition monitoring of the different machines and devices in an industrial process can minimize downtime, increase the safety of plant operations and help in the process of decision-taking for control and maintenance ...
Ruiz Cárcel, Cristóbal
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Sufficient reduction methods for multivariate health surveillance [PDF]
, 2013 Surveillance systems aim to detect sudden changes or aberrations in data series which might signal the possibility of disease outbreaks. Early detection with a low false alarm rate (FAR) is the main aim of outbreak detection as used in health ...
Siripanthana, Sawaporn
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A data-based approach for multivariate model predictive control performance monitoring [PDF]
, 2011 An intelligent statistical approach is proposed for monitoring the performance of multivariate model predictive control (MPC) controller, which systematically integrates both the assessment and diagnosis procedures.
Chen, Sheng +2 more
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Multivariate Monitoring Workflow for Formulation, Fill and Finish Processes
Bioengineering, 2020 Process monitoring is a critical task in ensuring the consistent quality of the final drug product in biopharmaceutical formulation, fill, and finish (FFF) processes. Data generated during FFF monitoring includes multiple time series and high-dimensional
Barbara Pretzner +5 more
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Robust kernel distance multivariate control chart using support vector principles [PDF]
, 2008 It is important to monitor manufacturing processes in order to improve product quality and reduce production cost. Statistical Process Control (SPC) is the most commonly used method for process monitoring, in particular making distinctions between ...
Chinnam, R. B. +5 more
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State-space independent component analysis for nonlinear dynamic process monitoring [PDF]
, 2010 The cost effective benefits of process monitoring will never be over emphasised. Amongst monitoring techniques, the Independent Component Analysis (ICA) is an efficient tool to reveal hidden factors from process measurements, which follow non-Gaussian
Odiowei, P. P., Cao, Yi
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Multivariate statistical analysis of parameters of surface water quality in Vojvodina
Zaštita Materijala, 2014 Monitoring of chemical and physical-chemical parameters of surface water is a very important factor in the quality control and management. Surface water quality is largely determined by atmospherics (natural process) and the discharge of industrial and ...
Borko Matijević +4 more
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Minimalist module analysis for fault detection and localization
Scientific Reports, 2021 Traditional multivariate statistical-based process monitoring (MSPM) methods are effective data-driven approaches for monitoring large-scale industrial processes, but have a shortcoming in handling the redundant correlations between process variables. To
Zhijiang Lou +3 more
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PCA Based Data Reconciliation in Soft Sensor Development
Chemical Engineering Transactions, 2015 Melt flow index (MFI) is a very important property of thermoplastic polymers. Laboratory measurements follow standard methods (ASTM D1238 or ISO 1133) to determine MFI and give accurate values, but these measurements are available only in 2-4 hour ...
B. Farsang +4 more
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Monitoring the mean with least-squares support vector data description
Gestão & Produção, 2021 : Multivariate control charts are essential tools in multivariate statistical process control (MSPC). “Shewhart-type” charts are control charts using rational subgroupings which are effective in the detection of large shifts.
Edgard M. Maboudou-Tchao
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