Effects of cutting parameters on tool wear in drilling of polymer composite by Taguchi method


INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, vol.58, pp.915-921, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 58
  • Publication Date: 2012
  • Doi Number: 10.1007/s00170-011-3464-6
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.915-921
  • Keywords: Drilling, Polymer composite, Tool wear, Taguchi, Analysis of variance (ANOVA), FIBER-REINFORCED PLASTICS
  • Yıldız Technical University Affiliated: Yes


Polymer composite products can be obtained by primary manufacturing processes such as contact molding, vacuum bag molding, resin transfer molding, or sheet molding compound and secondary processes such as drilling and saw cutting. Drilling is generally employed to make bolted or riveted assembles in composite structures. In drilling, some defects like delamination and crack are seen, and also undesired hole surface roughness related to tool wear is an another problem frequently encountered. In this study, tool wear in drilling of sheet molding compound (SMC) composite, consisted of 30 wt.% glass fiber, 25 wt.% polyester, and 45 wt.% calcium carbonate, was investigated. SMC composite was drilled under different cutting speeds, feeds, and drill point angles. Taguchi design of experiments and analysis of variance were utilized to determine the optimal cutting parameters and to analyze the effects of them on the tool wear. The feed followed by the drill point angle were found to be the important factors while cutting speed was the least effective parameter. Chip volume was accepted as a criterion to compare obtained data. Increasing feed and decreasing drill point angle reduced the tool wear. Multivariable linear regression analysis was also employed to determine the correlations between the factors and the tool wear. Finally, a model was generated and a good approximation was achieved in the comparison of the experimental data and the predicted data obtained from the model.