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BSI PD IEC TR 62829-1:2019

BSI PD IEC TR 62829-1:2019

$167.15

Chemometrics for process analytical technologies – General provisions, and methods for univariate statistics and chemometric processing of data

Published By Publication Date Number of Pages
BSI 2019 42
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This part of IEC 62829, which is a Technical Report, covers

  • a study into the pre-requisites of chemometric (exploratory) data analysis,

  • an overview of common data analysis procedures for univariate, bivariate and multivariate data analysis,

  • explanations of the basic principles and major application areas of the different methods),

  • some recommendations on the selection of an appropriate data analysis strategy.

These recommendations not covered earlier by other guidance documents on the topic are complemented by some advice on the validation of commercial (at the site of installation) and tailored software for process analytical purposes. Recommendations are given on available reference data sets (Annex B) for benchmarking of software implementing the data analysis methods covered (if available). An application example is given.

PDF Catalog

PDF Pages PDF Title
2 undefined
4 CONTENTS
6 FOREWORD
8 INTRODUCTION
10 1 Scope
2 Normative references
3 Terms and definitions
4 Fields of application
4.1 Process control and process analytical technologies (PAT)
11 4.2 Physical and chemical properties
12 4.3 PAT fields of application
4.3.1 Definition of chemometrics
4.3.2 Overview on PAT fields of applications
4.3.3 Chemometrics for sensors
Figures
Figure 1 – Different levels of chemometric applications
13 4.3.4 Chemometrics for production units
4.3.5 Chemometrics along a production chain
14 5 Pre-requisites of chemometric data analysis
5.1 Data has to be adequate and reliable
5.2 Data representativeness
15 5.3 Data acquisition
5.4 Data management
5.5 Databases versus spreadsheets
16 5.6 Data quality
5.7 Data validation
5.8 Data corruption
5.9 Data security and fraudulent data detection
17 5.10 Data management for data mining
6 Pre-requisites of chemometric data analysis
6.1 Technical requirements of chemometric data analysis
6.2 Data dimensionality
18 6.3 Method classification
19 6.4 Data pre-processing
6.4.1 Filtering
6.4.2 Smoothing
6.4.3 Data reduction
Tables
Table 1 – Data analysis techniques and data formats
21 Figure 2 – Influence of pre-processing techniques for classificationof the geographical origin of wine
22 7 Methods of chemometric data analysis
7.1 Univariate analysis
7.1.1 Descriptive statistics
23 7.1.2 Hypothesis testing
25 7.1.3 Analysis of variance (ANOVA)
27 7.1.4 General linear models
7.2 Bivariate analysis
7.2.1 Regression analysis
30 7.2.2 Time series analysis
33 Annex A (informative)Advice on software validation for processanalytical applications
A.1 General
A.2 Basic recommendations
34 Table A.1 – Categories of software
Table A.2 – Software validation levels
35 A.3 Software validation
Figure A.1 – Different paths for the introductionof new software in a laboratory
37 Annex B (informative)Reference data sets available for software benchmarking
38 Bibliography

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BSI PD IEC TR 62829-1:2019
$167.15