Premium
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
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom