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Moving horizon closed‐loop production scheduling using dynamic process models
Author(s) -
Pattison Richard C.,
Touretzky Cara R.,
Harjunkoski Iiro,
Baldea Michael
Publication year - 2017
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.15408
Subject(s) - scheduling (production processes) , computer science , production schedule , profit (economics) , mathematical optimization , industrial engineering , closed loop , raw material , time horizon , dynamic priority scheduling , operations research , schedule , engineering , control engineering , economics , mathematics , chemistry , organic chemistry , microeconomics , operating system
The economic circumstances that define the operation of chemical processes (e.g., product demand, feedstock and energy prices) are increasingly variable. To maximize profit, changes in production rate and product grade must be scheduled with increased frequency. To do so, process dynamics must be considered in production scheduling calculations, and schedules should be recomputed when updated economic information becomes available. In this article, this need is addressed by introducing a novel moving horizon closed‐loop scheduling approach. Process dynamics are represented explicitly in the scheduling calculation via low‐order models of the closed‐loop dynamics of scheduling‐relevant variables, and a feedback connection is built based on these variables using an observer structure to update model states. The feedback rescheduling mechanism consists of, (a) periodic schedule updates that reflect updated price and demand forecasts, and, (b) event‐driven updates that account for process and market disturbances. The theoretical developments are demonstrated on the model of an industrial‐scale air separation unit. © 2016 American Institute of Chemical Engineers AIChE J , 63: 639–651, 2017