Abstract
| Original language | English |
|---|---|
| Title of host publication | 23rd European Symposium on Computer Aided Process Engineering |
| Editors | Andrzej Kraslawski, Ilkka Turunen |
| Publisher | Elsevier |
| Pages | 625-630 |
| ISBN (Print) | 978-0-444-63234-0 |
| DOIs | |
| Publication status | Published - 2013 |
| MoE publication type | A4 Article in a conference publication |
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Keywords
- mutual information
- operating window
- process management
- transfer entropy
- uncertainty
Cite this
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Reliability of operating window identified from process data. / Ihalainen, Heimo; Ritala, Risto; Saarela, Olli.
23rd European Symposium on Computer Aided Process Engineering. ed. / Andrzej Kraslawski; Ilkka Turunen. Elsevier, 2013. p. 625-630 (Computer Aided Chemical Engineering, Vol. 32).Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Reliability of operating window identified from process data
AU - Ihalainen, Heimo
AU - Ritala, Risto
AU - Saarela, Olli
PY - 2013
Y1 - 2013
N2 - This paper discusses data-based operating windows as a tool for process management and development. In particular identification of the operating window and its uncertainty are analyzed. The operating window is determined by maximizing either the mutual information (static) or entropy transfer (dynamic). An industrial example shows that the entropy of the indicator variable is reduced to half by an operating window specified with only few variables, selected amongst over 3000 candidates. Test model based simulations suggest that such few-variable operating windows can be reliably identified from datasets having lengths of a few thousand observations.
AB - This paper discusses data-based operating windows as a tool for process management and development. In particular identification of the operating window and its uncertainty are analyzed. The operating window is determined by maximizing either the mutual information (static) or entropy transfer (dynamic). An industrial example shows that the entropy of the indicator variable is reduced to half by an operating window specified with only few variables, selected amongst over 3000 candidates. Test model based simulations suggest that such few-variable operating windows can be reliably identified from datasets having lengths of a few thousand observations.
KW - mutual information
KW - operating window
KW - process management
KW - transfer entropy
KW - uncertainty
UR - https://www.sciencedirect.com/bookseries/computer-aided-chemical-engineering/vol/32/suppl/C
U2 - 10.1016/B978-0-444-63234-0.50105-6
DO - 10.1016/B978-0-444-63234-0.50105-6
M3 - Conference article in proceedings
SN - 978-0-444-63234-0
SP - 625
EP - 630
BT - 23rd European Symposium on Computer Aided Process Engineering
A2 - Kraslawski, Andrzej
A2 - Turunen, Ilkka
PB - Elsevier
ER -