Title of article
Reliability of analytical systems: use of control charts, time series models and recurrent neural networks (RNN)
Author/Authors
Rius، نويسنده , , A. and Ruisلnchez، نويسنده , , I. and Callao، نويسنده , , M.P. and Rius، نويسنده , , F.X.، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 1998
Pages
18
From page
1
To page
18
Abstract
In this tutorial, the techniques used to study the reliability of analytical systems over time are discussed. The most classical approach is to use statistical process control (SPC) with control charts, and its principal characteristics, benefits and limitations are shown. The advanced process control (APC) approach, developed and mainly used in the field of engineering, is also studied and its possibilities for monitoring chemical measurement processes evaluated. The fundamentals and potentialities of recurrent neural networks (RNN) in this field are also presented. The bases of these three approaches are described, and their advantages and drawbacks discussed. They are applied to a simulated time series and to real process analytical data, and the results obtained for these data are compared.
Keywords
control charts , advanced process control , recurrent neural networks , time series models , STATISTICAL PROCESS CONTROL
Journal title
Chemometrics and Intelligent Laboratory Systems
Serial Year
1998
Journal title
Chemometrics and Intelligent Laboratory Systems
Record number
1459805
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