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Process similarity and developing new process models through migration
Author(s) -
Lu Junde,
Yao Ke,
Gao Furong
Publication year - 2009
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.11822
Subject(s) - process (computing) , similarity (geometry) , representation (politics) , process modeling , computer science , work in process , product (mathematics) , industrial engineering , data mining , process engineering , engineering , artificial intelligence , mathematics , operations management , image (mathematics) , operating system , geometry , politics , political science , law
An industrial process may operate over a range of conditions to produce different grades of product. With a data‐based model, as conditions change, a different process model must be developed. Adapting existing process models can allow using fewer experiments for the development of a new process model, resulting in a saving of time, cost, and effort. Process similarity is defined and classified based on process representation. A model migration strategy is proposed for one type of process similarity, family similarity, which involves developing a new process model by taking advantage of an existing base model, and process attribute information. A model predicting melt‐flow‐length in injection molding is developed and tested as an example and shown to give satisfactory results. © 2009 American Institute of Chemical Engineers AIChE J, 2009