Robust chemical product design via fuzzy optimisation approach

Lik Yin Ng, Nishanth G. Chemmangattuvalappil, Denny K. S. Ng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Product superiority is usually the only factor considered while designing optimal products using molecular design techniques for specific applications. It is to be noted that the accuracy of property prediction model can affect the effectiveness of this approach. Thus, the effect of property prediction uncertainty has to be addressed while designing optimal products. This paper presents a systematic methodology for the design of optimum molecules used in chemical processes by considering both product superiority and robustness. Product superiority is quantified by property optimality while product robustness is measured by the deviation of product property from the expected property prediction range. Standard deviation of a property prediction model is used to address the uncertainty of the model. Fuzzy optimisation approach is applied into the molecular design techniques in this work. To illustrate the proposed method, a case study is presented where optimal solution is selected based on how much the solution satisfied the criteria of product superiority and robustness.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Foundations of Computer-Aided Process Design
EditorsMario R. Eden, John D. Siirola, Gavin P. Towler
Pages387-392
Number of pages6
Volume34
DOIs
Publication statusPublished - 2014

Publication series

NameComputer Aided Chemical Engineering
Volume34
ISSN (Print)1570-7946

Keywords

  • Fuzzy optimisation
  • Inverse design techniques
  • Product design
  • Property prediction uncertainties

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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