Industrial applications of soft computing: a review

• Published in: Proceedings of the IEEE Vol. 89; no. 9; pp. 1243 - 1265
• Main Authors: Dote, Y., Ovaska, S.J.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-09-2001; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Analogies; Computer applications; Computer industry; Computer networks; Construction industry; Costs; Evolutionary computation; Fuzzy logic; Intelligent systems; Knowledge acquisition; Knowledge representation; Low cost; Mathematical analysis; Neural networks; Soft computing
• ISSN: 0018-9219; 1558-2256
• DOI: 10.1109/5.949483

Fuzzy logic, neural networks, and evolutionary computation are the core methodologies of soft computing (SC). SC is causing a paradigm shift in engineering and science fields since it can solve problems that have not been able to be solved by traditional analytic methods. In addition, SC yields rich knowledge representation, flexible knowledge acquisition, and flexible knowledge processing, which enable intelligent systems to be constructed at low cost. This paper reviews applications of SC in several industrial fields to show the various innovations by TR, HMIQ, and low cost in industries that have been made possible by the use of SC. Our paper intends to remove the gap between theory and practice and attempts to learn how to apply soft computing practically to industrial systems from examples/analogy, reviewing many application papers.