Statistical process monitoring of time-dependent data
نویسندگان
چکیده
منابع مشابه
A review of PCA-based statistical process monitoring methods for time-dependent, high-dimensional data
High-dimensional and time-dependent data pose significant challenges to Statistical Process Monitoring. Dynamic Principal Component Analysis, Recursive PCA and Moving Window PCA have been proposed to cope with high-dimensional and time-dependent features. We present a comprehensive review of this literature for the practitioner encountering this topic for the first time. We detail the implement...
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QUALITY CONTROL CHARTS are a widely used tool, developed in the field of statistical process monitoring (SPM) to identify when a system is deviating from typical behavior. High-dimensional, timedependent data frequently arise in applications ranging from health care, industry, and IT to the economy. These data features challenge many canonical SPM methods, which lose precision as the dimensiona...
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In this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. Then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (ARL). The results of these simulation experiments show that the EWMA and EWMS methods ...
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Process safety and environment pollution demands are continuously increasing in the process industry. Apart from that, requirements regarding final product quality and production efficiency are higher and higher [1]. This can be achieved by applying advanced process monitoring and control techniques. Process control is heavily dependent on the quality of the data, so it is crucial to measure as...
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ژورنال
عنوان ژورنال: Quality Engineering
سال: 2016
ISSN: 0898-2112,1532-4222
DOI: 10.1080/08982112.2015.1100474