Effects on machinability of cryogenic treatment applied to carbide tools in the milling of Ti6AI4V with optimization via the Taguchi method and grey relational analysis

EKİCİ E., UZUN G.

JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, cilt.44, sa.7, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 44 Sayı: 7
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s40430-022-03572-1
  • Dergi Adı: JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: Ti6AI4V alloy, Cryogenic treatment, Cutting force, Surface roughness, Taguchi method, Grey relational analysis, UNCOATED WC-CO, SURFACE-ROUGHNESS, WEAR BEHAVIOR, MULTIOBJECTIVE OPTIMIZATION, PROCESS PARAMETERS, MULTIRESPONSE OPTIMIZATION, CUTTING PARAMETERS, SUBZERO TREATMENTS, CHIP MORPHOLOGY, PERFORMANCE
  • Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet

Özet

The effects of processing parameters and cryogenic treatment on cutting force and surface roughness in the milling of Ti6AI4V alloy were investigated in this study. The effects of cutting speed, feed rate, and the treatments applied to the tools were evaluated through the Taguchi method and grey relational analysis. Control factors in the experiments performed under dry cutting conditions were based on two different cutting speeds and three different feed rates and tool properties. It was observed that the cutting force values decreased with increased cutting speed and significantly increased parallel to the feed rate. In terms of surface roughness, they were observed to change based on cutting parameters. Whereas the most effective parameter for cutting force was feed rate, with a 81.9% contribution, for surface roughness it was cutting speed, with a 48.8% contribution. Optimum machining conditions were determined as A(1)B(3)C(2) following the grey relational analysis performed for both responses.