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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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Statistical process monitoring by using process mining
IEEE Conference Anthology, 2013There is well known: whether the advantage of using a normal process model to monitor the stability of a manufacturing process can be gained lies in the model's ability used to realize its conformance to the manufacturing process trend. In other words, whether a manufacturing process can be stabilized depends on how much is about the conformance level ...
null Ze-Crong Haung +2 more
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Multivariate statistical monitoring of the aluminium smelting process
Computers & Chemical Engineering, 2011Abstract This paper describes the development of a new ‘cascade’ monitoring system for the aluminium smelting process that uses latent variable models. This system is based on the changes of variability patterns within a feeding cycle which are used to provide indications of faults and their possible causes.
Nazatul Aini Abd Majid +3 more
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User-friendly statistical concepts for process monitoring
Journal of the Operational Research Society, 1998Summary: Many standard statistical process control techniques involve sophisticated mathematical concepts, which are frequently misunderstood and misused by their users. This means, as this paper argues, that the techniques, and the terminology and concepts underlying them, are inappropriate for their intended uses and users.
Wood, Michael, Capon, Nick, Kaye, Mike
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Statistical process monitoring in the era of smart manufacturing
2017 American Control Conference (ACC), 2017One of the focuses of smart manufacturing is to create manufacturing intelligence from real-time data to support accurate and timely decision-making. Therefore, data-driven statistical process monitoring is expected to contribute significantly to the advancement of smart manufacturing.
Q. Peter He, Jin Wang 0030
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Overview of statistical methods of process monitoring
Safety and Reliability of Power Industry, 2022At present, process monitoring by comparing the current parameters against a specified setpoint is widespread at thermal power plants. This approach does not allow diagnosing the emergence of a trend leading to an emergency mode at early stages. On the other hand, the analysis of time series of parameters by means of methods of statistical process ...
M. M. Sultanov +2 more
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Statistical Process Monitoring and Feedback Adjustment: A Discussion
Technometrics, 1992Rationales for process monitoring using some of the techniques of statistical process control and for feedback adjustment using some techniques associated with automatic process control are explored, and issues that sometimes arise are discussed. The importance of some often unstated assumptions are illustrated.
George Box, Tim Kramer
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Multi-Scale Statistical Process Monitoring in Machining
IEEE Transactions on Industrial Electronics, 2005Most practical industrial process data contain contributions at multiple scales in time and frequency. Unfortunately, conventional statistical process control approaches often detect events at only one scale. This paper addresses a new method, called multiscale statistical process monitoring, for tool condition monitoring in a machining process, which ...
Xiaoli Li 0002, Xin Yao 0001
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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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Statistical Process Monitoring and Disturbance Isolation in Multivariate Continuous Processes
IFAC Proceedings Volumes, 1994Abstract Quick detection of out-of-control status and diagnosis of disturbances leading to the abnormal process operation are crucial in minimizing product quality variation. Multivariate statistical techniques are used in developing methodology for detection of abnormal process behavior and diagnosis of disturbances causing poor process performance.
Anne Raich, Ali Cinar
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