4.6 Article

Process synthesis prospective

期刊

COMPUTERS & CHEMICAL ENGINEERING
卷 28, 期 4, 页码 441-446

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2003.09.030

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process synthesis; systematic generation; artificial intelligence; representations; superstructure optimization; sustainability; multi-criteria optimization

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Chemical process synthesis methods and tools developed over the last several decades have reached a level of maturity that have provided advantage to practitioners in an environment of increased costs and shrinking margins. Future growth within the chemical process industries is likely to involve even keener competition with greater impact from factors such as raw material and energy availability, climate change mitigation, sustainability, and inherent security. The future will probably see an expanded role for the systematic generation process synthesis paradigm, including an increased interdependency with process and catalytic chemistry on one hand and operability and control expertise on the other. Advances from artificial intelligence may inspire new process synthesis paradigms incorporating more effective representations of the underlying physical sciences and engineering art, new social concerns, new design strategies, and new computerized implementations. The future may also see a collaboration of the systematic generation and superstructure optimization process synthesis paradigms in which systematic generation is used to create the superstructure for simultaneous discrete and continuous variable optimization. As the resulting process designs will certainly be evaluated from additional points of view including social considerations, superstructure optimization will need to produce families of good designs for multi-criteria Pareto optimization. There are many challenges, but continued progress will be made and these challenges will be met. (C) 2003 Elsevier Ltd. All rights reserved.

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