Benyettou R., Amroune S., Slamani M., Kılıç A.

Academic Journal of Manufacturing Engineering, vol.21, no.1, pp.97-104, 2023 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 1
  • Publication Date: 2023
  • Journal Name: Academic Journal of Manufacturing Engineering
  • Journal Indexes: Scopus, Applied Science & Technology Source
  • Page Numbers: pp.97-104
  • Keywords: ANN, Bio composite, Delamination, Drilling, Palm fiber
  • Istanbul Technical University Affiliated: Yes


The This work studies the drilling performance of bio composites reinforced with cellulosic fibres. The drilling was carried out at three spindle speeds and at three feed rates using three dissimilar drills namely: HSS-TITAN, HSS-CARBIDE, and HSS-SUPER. The drilling performance was evaluated in terms of the delamination factor which was determined using the free software image J. The results showed that the value of this factor decreased with increasing spindle speed and increased with increasing feed rate. On the other hand, the HSS-SUPER drill causes less delamination than the other two drills. To predict the delamination value, the artificial neural network (ANN) method was used. The best hole quality was obtained when using the HSS-SUPER drill, with a spindle speed of 2200 rpm and a feed rate of 40 mm/rev. The worst case was brought when using an HSS-carbide drill, with a spindle speed of 500 rpm and a feed rate of 120 mm/rev.