Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.compchemeng.2010.08.004
Title: A knowledge-based simulation-optimization framework and system for sustainable process operations
Authors: Halim, I.
Srinivasan, R. 
Keywords: Knowledge-based system
Multi-objective decision-making
Process graph
Process synthesis
Simulation-optimization
Waste minimization
Issue Date: 10-Jan-2011
Source: Halim, I., Srinivasan, R. (2011-01-10). A knowledge-based simulation-optimization framework and system for sustainable process operations. Computers and Chemical Engineering 35 (1) : 92-105. ScholarBank@NUS Repository. https://doi.org/10.1016/j.compchemeng.2010.08.004
Abstract: Design and operation of chemical plants involves a combination of synthesis, analysis and evaluation of alternatives. Such activities have traditionally been driven by economic factors first, followed by engineering, safety and environmental considerations. Recently, chemical companies have embraced the concept of sustainable development, entailing renewable feed materials and energy, non-toxic and biodegradable products, and waste minimization or even elimination at source. In this paper, we introduce a knowledge-based simulation-optimization framework for generating sustainable alternatives to chemical processes. The framework has been developed by combining different process systems engineering methodologies - the knowledge-based approach for identifying the root cause of waste generation, the hierarchical design method for generating alternative designs, sustainability metrics, and multi-objective optimization - into one coherent simulation-optimization framework. This is implemented as a decision-support system using Gensym's G2 and the HYSYS process simulator. We illustrate the framework and system using the HDA and biodiesel production case studies. © 2010 Elsevier Ltd.
Source Title: Computers and Chemical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/54292
ISSN: 00981354
DOI: 10.1016/j.compchemeng.2010.08.004
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