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Optimal Design of Laboratory and Pilot‐Plant Experiments Using Multiobjective Optimization
Author(s) -
Forte Esther,
Harbou Erik,
Burger Jakob,
Asprion Norbert,
Bortz Michael
Publication year - 2017
Publication title -
chemie ingenieur technik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 36
eISSN - 1522-2640
pISSN - 0009-286X
DOI - 10.1002/cite.201600104
Subject(s) - pareto principle , design of experiments , multi objective optimization , factorial experiment , pareto analysis , optimal design , focus (optics) , range (aeronautics) , computer science , mathematical optimization , fractional factorial design , pareto optimal , work (physics) , experimental data , biochemical engineering , engineering , mathematics , machine learning , statistics , mechanical engineering , physics , optics , aerospace engineering
Performing an experimental design prior to the collection of data is in most circumstances important to ensure efficiency. The focus of this work is the combination of model‐based and statistical approaches to optimal design of experiments. The knowledge encoded in the model is used to identify the most interesting range for the experiments via a Pareto optimization of the most important conflicting objectives. Analysis of the trade‐offs found is in itself useful to design an experimental plan. This can be complemented using a factorial design in the most interesting part of the Pareto frontier.