Abstract
AbstractAn 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
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