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A neural network approach to multiple-objective cutting parameter optimization based on fuzzy preference information

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This paper presents a neural network approach to multiple-objective cutting parameter optimization for planning turning operations. Productivity, operation cost, and cutting quality are considered as criteria for optimizing machining operations. A feedforward neural network and a dynamic training procedure are proposed for modeling manufacturers' preferences using sampled fuzzy preferential data. Optimum cutting parameters are determined based on neural network representations of manufacturers' fuzzy preference structures. © 1993.
Original languageEnglish
Pages (from-to)389-392
JournalComputers and Industrial Engineering
Volume25
Issue number1-4
DOIs
Publication statusPublished - Sept 1993
Externally publishedYes

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