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

Jun Wang

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)389-392
Number of pages4
JournalComputers and Industrial Engineering
Volume25
Issue number1-4
DOIs
Publication statusPublished - Sep 1993
Externally publishedYes

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