Computational Intelligence (CI) models are established from biological paradigms and purpose to address complex challenges. Probabilistic methodologies and soft computing, which incorporate various models of CI, are typically employed in the domain of CI. Ontologies are fundamental in product design engineering process since they provide a common basis for incorporating various information sources. This research reviews five major models of CI: artificial intelligence, artificial neural networks, artificial immune systems, swarm intelligence, and evolutionary computation. The paper discusses the origins and applications of every paradigm, as well as its application in product design engineering. The study also reviews the functions of ontologies in the incorporation of information sources and facilitation of smart algorithms and techniques in the domain of product design engineering. In addition, it assesses the application of data mining, case-based reasoning, decision-making algorithms, hybrid techniques, qualitative reasoning, and process modeling in product design engineering. This article ends with an examination of modification, differentiation, customization, development, and building of process models within the field of product design engineering. It also reviews how CI approaches may be employed in addressing unique process challenges.
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Atuha Digina Simon
Mbarara University of Science and Technology, Mbarara, Uganda.
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Atuha Digina Simon, “Computational Intelligence Paradigms in Product Design Engineering: A Comprehensive Review”, Journal of Computational Intelligence in Materials Science, vol.2, pp. 047-058, 2024. doi: 10.53759/832X/JCIMS202402005.
