Continuous manufacturing: Is the process mean stationary?

被引：5

作者：

Simon, Levente L. ^{[1
,2
]}

机构：

[1] IIT, Dep Chem Engn, Chicago, IL 60616 USA

[2] Syngenta Crop Protect AG, New Act Ingredients Proc Technol, Munchwilen, Switzerland

来源：

AICHE JOURNAL | 2018年 / 64卷 / 07期

关键词：

continuous manufacturing; steady-state; unit-root test; stationarity test; plug-flow crystallizer; process analytical technologies; PAT; CONTINUOUS MIXED-SUSPENSION; STEADY-STATE IDENTIFICATION; TIME-SERIES; CONTINUOUS CRYSTALLIZATION; UNIT-ROOT; ISOELECTRIC PRECIPITATION; DATA RECONCILIATION; SUNFLOWER PROTEIN; NULL HYPOTHESIS; CONTROL-CHART;

D O I：

10.1002/aic.16125

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The statistical framework to systematically detect mean stationarity in the context of continuous manufacturing is described in this article. The methods presented in this article use econometric and financial time-series analysis concepts in the form of unit-root and stationarity hypothesis tests. The tests under discussion are the augmented Dickey-Fuller, Philips-Perron, Leybourne-McCabe, and Kwiatkowski-Phillips-Schmidt-Shin. These hypothesis tests are evaluated on data generated by a focused-beam reflectance measurement sensor implemented on-line in a continuous plug-flow crystallizer. This contribution has shown that the hypothesis tests can be used to detect steady-state conditions on-line in a plug-flow crystallizer. Furthermore, this econometric framework can be used as a mean stationarity certificate of collected samples to document that the process was mean stationary during the sampling. The statistical framework described in this article can be applied to any continuously operated unit operation or sensor measurement. (c) 2018 American Institute of Chemical Engineers AIChE J, 64: 2426-2437, 2018

引用

页码：2426 / 2437

页数：12

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