Abstract
The chapter summarizes the current state of the art of applying soft computing solutions in the chemical industry, based on the experience of The Dow Chemical Company and projects the future trends in the field, based on the expected future industrial needs. Several examples of successful industrial applications of different soft computing techniques are given: automated operating discipline, based on fuzzy logic; empirical emulators of fundamental models, based on neural networks; accelerated new product development, based on genetic programming, and advanced process optimization, based on swarm intelligence. The impact of these applications is a significant improvement in process operation and in much faster modeling of new products.
The expected future needs of industry are defined as: predictive marketing, accelerated new products diffusion, high-throughput modeling, manufacturing at economic optimum, predictive optimal supply-chain, intelligent security, reduce virtual bureaucracy, emerging simplicity, and handling the curse of decentralization. The future trends that are expected from the soft computing technologies, which may satisfy these needs, are as follows: perception-based modeling, integrated systems, universal role of intelligent agents, models/rules with evolved structure, and swarm intelligence-based process control.
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Kordon, A. (2007). Soft Computing in the Chemical Industry: Current State of the Art and Future Trends. In: Nikravesh, M., Kacprzyk, J., Zadeh, L.A. (eds) Forging New Frontiers: Fuzzy Pioneers I. Studies in Fuzziness and Soft Computing, vol 217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73182-5_18
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DOI: https://doi.org/10.1007/978-3-540-73182-5_18
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