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Input analysis, process data univariate methods

The overall objective of the system is to map from three types of numeric input process data into, generally, one to three root causes out of the possible 300. The data available include numeric information from sensors, product-specific numeric information such as molecular weight and area under peak from gel permeation chromatography (GPC) analysis of the product, and additional information from the GPC in the form of variances in expected shapes of traces. The plant also uses univariate statistical methods for data analysis of numeric product information. [Pg.91]


See other pages where Input analysis, process data univariate methods is mentioned: [Pg.13]    [Pg.14]    [Pg.13]    [Pg.14]    [Pg.46]    [Pg.46]   
See also in sourсe #XX -- [ Pg.4 , Pg.13 , Pg.14 , Pg.15 , Pg.16 , Pg.17 , Pg.18 ]

See also in sourсe #XX -- [ Pg.4 , Pg.13 , Pg.14 , Pg.15 , Pg.16 , Pg.17 , Pg.18 ]




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Data Method

Data analysis methods

Data processing

Data processing methods

Input analysis, process data

Input data

Input processing

Method process

Process analysis

Process analysis processes

Process data

Process data analysis

Processed method

Processing analysis

Processing methods

Univariant

Univariate analysis

Univariate data

Univariate data analysis

Univariate methods

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