Abstract
This chapter presents various techniques using the combination of fuzzy logic and genetic algorithm (GA) to construct model of a physical process including manufacturing process. First, an overview on the fundamentals of fuzzy logic and fuzzy inferences systems toward formulating a rule-based model (called fuzzy rule based model, FRBM) is presented. After that, the working principle of a GA is discussed and later, how GA can be combined with fuzzy logic to design the optimal knowledge base of FRBM of a process is presented. Results of few case studies of modeling various manufacturing processes using GA-fuzzy approaches conducted by the author are presented.
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© 2012 Springer-Verlag Berlin Heidelberg
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Nandi, A.K. (2012). GA-Fuzzy Approaches: Application to Modeling of Manufacturing Process. In: Davim, J.P. (eds) Statistical and Computational Techniques in Manufacturing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25859-6_4
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DOI: https://doi.org/10.1007/978-3-642-25859-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25858-9
Online ISBN: 978-3-642-25859-6
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