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Pattern recognition in chemical process flowsheets
Author(s) -
Zhang Tong,
Sahinidis Nikolaos V.,
Siirola Jeffrey J.
Publication year - 2019
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.16443
Subject(s) - process (computing) , heuristic , biochemical engineering , process engineering , process design , chemical process , computer science , engineering , artificial intelligence , process integration , chemical engineering , operating system
By recognizing similarities in flowsheets, engineers can understand ways in which to improve the design and efficiency of chemical processes. However, there is no prior literature on how to compare flowsheets and mine them for common patterns. To fill this gap, we propose the first systematic methodology to mine patterns in chemical process flowsheets. The proposed methodology consists of three major steps, each of which has a polynomial time complexity. We apply our methodology to several case studies that involve comparisons of up to 18 different flowsheets. The patterns identified by our methodology are consistent with engineering practice and heuristic rules in the process synthesis literature. © 2018 American Institute of Chemical Engineers AIChE J , 65: 592–603, 2019