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Robust Slow Feature Analysis for Statistical Process Monitoring
, 2020Slow feature analysis (SFA) is being adopted in the process monitoring and fault diagnosis as a new latent variable extraction and dimension reduction method.
Jiafeng Wang, Zhonggai Zhao, Fei Liu
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Statistical process control for electron beam monitoring
Physica Medica, 2015To assess the electron beam monitoring statistical process control (SPC) in linear accelerator (linac) daily quality control. We present a long-term record of our measurements and evaluate which SPC-led conditions are feasible for maintaining control.We retrieved our linac beam calibration, symmetry, and flatness daily records for all electron beam ...
Juan, López-Tarjuelo +8 more
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Batch Statistical Process Monitoring Approach to a Cocrystallization Process
Journal of Pharmaceutical Sciences, 2015Cocrystals are defined as crystalline structures composed of two or more compounds that are solid at room temperature held together by noncovalent bonds. Their main advantages are the increase of solubility, bioavailability, permeability, stability, and at the same time retaining active pharmaceutical ingredient bioactivity.
Mafalda C, Sarraguça +3 more
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Multivariate Statistical Process Control and Process Performance Monitoring
IFAC Proceedings Volumes, 1998Abstract Multivariate Statistical Process Performance Monitoring (MSPPM) provides a diagnostic tool for the monitoring and detection of process malfunctions for continuous and batch manufacturing processes. This paper initially reviews the concept of process performance monitoring through an industrial application to a fluidised bed-reactor and a ...
E.B. Martin +2 more
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A Review of Some Sampling and Aggregation Strategies for Basic Statistical Process Monitoring
Journal of QualityTechnology, 2019We review the long-established rational subgrouping principle for determining an effective sampling plan for process monitoring. We present some other general advice that has been given in the literature and discuss some issues related to sampling as it ...
I. Zwetsloot, W. Woodall
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Statistical batch process monitoring using gray models
AIChE Journal, 2005AbstractA complete strategy for monitoring industrial batches processes using gray models is presented including fault detection and fault diagnosis tools. The use of gray models is a novel concept in batch process modeling and monitoring. A gray model is a hybrid model, intermediate between hard (white) process models and soft (black) models ...
van Sprang, E.N.M. +4 more
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Monitoring biological processes using univariate statistical process control
The Canadian Journal of Chemical Engineering, 2018AbstractBiological modelling is a challenging task specifically when state variables are difficult or even impossible to be measured. Consequently, monitoring quality of biological process will be impacted negatively due to the lack of an accurate model capable of reflecting precisely the process dynamics. Moreover, the faults in such systems cannot be
Majdi Mansouri +5 more
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Distributed partial least squares based residual generation for statistical process monitoring
Journal of Process Control, 2019The main focus of the current work is to propose a purely data-based residual generation method for statistical process monitoring. The proposed approach utilizes but not limit to the partial least squares (PLS) algorithm to construct a specific ...
Chudong Tong +3 more
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PCA based statistical process monitoring of grinding process
IEEE ICCA 2010, 2010Multivariate statistical process monitoring (MSPM) has received increasing attention, which is applied to improve process operations by detecting when abnormal process operations exist and diagnosing the sources of the abnormalities. This paper presents a MSPM application method on grinding processes, including principal component analysis (PCA), fault
Zhang Lin +4 more
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Dissimilarity of Process Data for Statistical Process Monitoring
IFAC Proceedings Volumes, 2000Abstract For monitoring chemical processes, multivariate statistical process control (MSPC) has been widely used. In the present work, a new process monitoring method is proposed. The proposed method utilizes a change in distribution of process data, since the distribution reflects the corresponding operating condition.
Manabu Kano +4 more
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