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Advance warning for loss of separation in an industrial distillation column
Author(s) -
Van Impe Jan,
Augustinus Klaas,
De Prins Michiel,
Gins Geert
Publication year - 2018
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2222
Subject(s) - fractionating column , column (typography) , reliability (semiconductor) , principal component analysis , process (computing) , reliability engineering , distillation , computer science , warning system , process engineering , autocorrelation , component (thermodynamics) , separation (statistics) , engineering , statistics , artificial intelligence , machine learning , mathematics , chemistry , chromatography , telecommunications , power (physics) , physics , frame (networking) , quantum mechanics , thermodynamics , operating system
Abstract This paper describes the development of a data‐driven advance warning system for the onset of loss of separation in an industrial distillation column. The system would enable preventive actions to avoid several hours of bad operation and subsequent recovery of the process. Data of more than 2 years of process operation were used to identify and validate various monitoring systems based on both static principal component analysis (PCA) and dynamic PCA. Despite the presence of autocorrelation in the data, only minor differences in advance warning were observed between PCA and dynamic PCA. The developed system provides warnings for 35% to 45% of the observed periods of bad column operation, with respective advance warning times of 16 and 6 minutes. It proves a valuable additional tool to monitor the operation of the distillation column and avoid losses of product, with the potential of reducing bad operation (and the associated costs) by up to 45% and substantially improving overall process reliability.