REGRESSION MODELING OF THE HOLE QUALITIES DURING COLD WORK TOOL STEELS DRILLING, WITH DIFFERENT CHARACTERISTICS DRILL BITS

Yıl 2017, Cilt: 1 Sayı: 2, 52 - 60, 15.09.2017

İskender Özkul , Berat Barış Buldum , Adnan Akkurt

https://doi.org/10.31127/tuje.316220

Cited By: 1

Öz

In this study, drill operations have been tested on Sleipner cold work tool steel by various machining parameters and drill bits. Solid Carbide Uncoated drill bits and TiAlN Coated reamed drill bits were used in experiments. Both drill bits were machined on Sleipner steel with four different cutting speeds. After machining, thrust forces and moments values generated during cutting, consisting surface and the hole qualities have been measured. Drilled by reamed drill bit’s hole gave better results quality as a result of the studies. It was reached as conclusion that the optimum values parameters of the cutting speeds are between 40 to 42 m/min for both the drill bits.

Anahtar Kelimeler

Machinability, Drilling cutting forces, Surface roughness, cold work tool steel

Kaynakça

• Çiçek, A., T. Kıvak, I. Uygur, E. Ekici and Y. Turgut (2012). "Performance of cryogenically treated M35 HSS drills in drilling of austenitic stainless steels." The International Journal of Advanced Manufacturing Technology Vol. 60, No. 1 pp. 65-73.
• Farid, A. A., S. Sharif and M. H. Idris (2011). "Chip morphology study in high speed drilling of Al–Si alloy." The International Journal of Advanced Manufacturing Technology Vol. 57, No. 5-8 pp. 555-564.
• Isbilir, O. and E. Ghassemieh (2012). "Finite element analysis of drilling of carbon fibre reinforced composites." Applied Composite Materials Vol. 19, No. 3-4 pp. 637-656.
• Ohzeki, H., H. Hoshi and A. Fumihito (2012). "Drilling of carbon fiber reinforced plastic composites with feedback control based on cutting force." Journal of Advanced Mechanical Design, Systems, and Manufacturing Vol. 6, No. 1 pp. 52-64.
• Özkul, İ. (2012). Takım çeliği malzemelerin geleneksel ve modern işleme yöntemleri ile işlenebilirliklerinin araştırılması Master thesis, Gazi University, Ankara, Turkey.
• Salimi, A., S. Abbasgholizadeh, S. Taghizadeh and A. Safarian (2011). "Using of artifical neural Networks to predict drill wear in machining process." Australian Journal of Basic and Applied Sciences Vol. 5, No. 12 pp. 2752-2760.
• Tash, M. M., F. Samuel and S. Alkahtani (2012). "Machinability of Heat-Treated 356 and 319 Aluminum Alloys: Methodology for Data Processing and Calculation of Drilling Force and Moment." Advanced Materials Research Vol. 396, No. pp. 1008-1022.
• http://www.uddeholm.com/files/PB_Uddeholm_sleipner_english.pdf. [Accessed 26 May 2017].
• Zitoune, R., V. Krishnaraj, B. S. Almabouacif, F. Collombet, M. Sima and A. Jolin (2012). "Influence of machining parameters and new nano-coated tool on drilling performance of CFRP/Aluminium sandwich." Composites Part B: Engineering Vol. 43, No. 3 pp. 1480-1488.