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|Title:||Practical challenges in developing data-driven soft sensors for quality prediction|
|Citation:||Liu, J.,Srinivasan, R.,SelvaGuru, PN. (2008). Practical challenges in developing data-driven soft sensors for quality prediction. Computer Aided Chemical Engineering 25 : 961-966. ScholarBank@NUS Repository. https://doi.org/10.1016/S1570-7946(08)80166-6|
|Abstract:||With improved quality control, a refinery plant can operate closer to optimum values. However, real-time measurement of product quality is generally difficult. On-line prediction of quality using frequent process measurements would therefore be beneficial. In this paper, our learnings from developing and deploying a data-driven soft sensor for a refinery unit are presented. Key challenges in developing a practicable soft sensor for actual use in a plant are discussed and our solutions to these presented. Finally, this paper reports results from the online deployment and demonstrates their value for the plant personnel. © 2008 Elsevier B.V. All rights reserved.|
|Source Title:||Computer Aided Chemical Engineering|
|Appears in Collections:||Staff Publications|
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