A Multivariate Methodology for Controlling Industrial Processes

The combination of tree multivariate techniques (Principal Component Analysis, Cluster Analysis and Discriminant Analysis) may be used to isolate and determine bounds for the critical control variable in a ``black box'' type industrial process. If input samples can be grouped into homogene...

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Bibliographic Details
Published inIEEE transactions on industrial electronics and control instrumentation Vol. IECI-22; no. 2; pp. 175 - 178
Main Authors Chiattello, Marion L., Pecenka, Joseph O.
Format Journal Article
LanguageEnglish
Published IEEE 01.05.1975
Subjects
Electric variables control
Electrical equipment industry
Industrial control
Industrial relations
Parameter estimation
Process control
Scattering
Silicon
Temperature dependence
Testing
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Summary:The combination of tree multivariate techniques (Principal Component Analysis, Cluster Analysis and Discriminant Analysis) may be used to isolate and determine bounds for the critical control variable in a ``black box'' type industrial process. If input samples can be grouped into homogeneous quality categories, then it may be possibie to use input and operating data to estimate discriminant functions which will differentiate between various quality categories. These functions could then be used to predict quality levels based upon input and operating characteristics. In addition, the coefficents of te discriminant functions would provide information as to the critical control variables and their bounds.
ISSN:0018-9421
2375-0502
DOI:10.1109/TIECI.1975.351248