The role of stepover ratio in prediction of surface roughness in flat end milling

Topal E. S.

INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, cilt.51, sa.11-12, ss.782-789, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 11-12
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.ijmecsci.2009.09.003
  • Dergi Adı: INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.782-789
  • Anahtar Kelimeler: Surface roughness, End milling, Neural networks, NEURAL-NETWORK, GENERATION, MODEL, RECOGNITION, SYSTEM, CNC
  • Akdeniz Üniversitesi Adresli: Hayır

Özet

Surface roughness prediction studies in end milling operations are usually based on three main parameters composed of cutting speed, feed rate and depth of cut. The stepover ratio is usually neglected without investigating it. The aim of this study is to discover the role of the stepover ratio in surface roughness prediction studies in flat end milling operations. In realising this, machining experiments are performed under various cutting conditions by using sample specimens. The surface roughnesses of these specimens are measured. Two ANN structures were constructed. First of them was arranged with considering, and the second without considering the stepover ratio. ANN structures were trained and tested by using the measured data for predicting the surface roughness. Average RMS error of the ANN model considering stepover ratio is 0.04 and without considering stepover ratio is 0.26. The first model proved capable of prediction of average surface roughness (Ra) with a good accuracy and the second model revealed remarkable deviations from the experimental values. (C) 2009 Elsevier Ltd. All rights reserved.