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- W1496030390 abstract "This paper addresses a class of problems typically faced by process engineers and operators: the detection of assignable variation causes in retrospective data series corresponding to quality or process variables. The detection of average and/or variance changes is dealt as a classical change-point problem analysis where the two main questions raised are: 1) “Did a change really occur?” and 2) “When did it occur?”. The approach adopted for achieving such a goal is based upon Change-Point Analysis (CPA) performed over CUSUM operators. To handle any type of data structure, the detection step is performed by a nonparametric bootstrapping procedure that estimates a probability distribution, according to which the existence of process shifts is determined. We tested the above approach through its application to typical chemical engineering case studies, covering a simulated CSTR and industrial data collected from a Portuguese pulp plant." @default.
- W1496030390 created "2016-06-24" @default.
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- W1496030390 date "2003-01-01" @default.
- W1496030390 modified "2023-09-24" @default.
- W1496030390 title "Change point detection for quality monitoring of chemical processes" @default.
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- W1496030390 doi "https://doi.org/10.1016/s1570-7946(03)80148-7" @default.
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