Prediction of stable cutting depths in turning operation using soft computing methods

SOFUOĞLU M. A., ORAK S.

APPLIED SOFT COMPUTING, cilt.38, ss.907-921, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 38
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.asoc.2015.10.031
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.907-921
  • Anahtar Kelimeler: Chatter vibration, ANN, Heuristic optimization, Regression models, CHATTER STABILITY, IDENTIFICATION
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

This article suggests soft computing methods to predict stable cutting depths in turning operations without chatter vibrations. Chatter vibrations cause poor surface finish. Therefore, preventing these vibrations is an important area of research. Predicting stable cutting depths is vital to determine the stable cutting region. In this study, a set of cutting experiments has been used and the stable cutting depths are predicted as a function of cutting, modal and tool-working material parameters. Regression analyses, artificial neural networks (ANN) decision trees and heuristic optimization models are used to develop the generalization models. The purpose of the models is to estimate stable cutting depths with minimum error. ANN produces better results compared to the other models. This study helps operators and engineers to perform turning operations in an appropriate cutting region without chatter vibrations. It also helps to take precautions against chatter. (C) 2015 Elsevier B.V. All rights reserved.