Optimal machining conditions for turning Ti-6Al-4V using response surface methodology
Source abstract
Abstract
Machining titanium is one of ever-increasing magnitude problems due to its characteristics such as low thermal conductivity, modulus of elasticity and work hardening. The efficient titanium alloy machining involves a proper selection of process parameters to minimize the tangential force (F z) and surface roughness (R a). In the present work, the performance of PVD/TiAlN coated carbide inserts was investigated using response surface methodology (RSM) for turning Ti-6Al-4V. The effects of process parameters such as speed (v), feed (f), depth of cut (d) and back rake angle (γ y ) on F z and R a were investigated. The experimental plan used for four factors and three levels was designed based on face centered, central composite design (CCD). The experimental results indicated that F z increased with the increase in d, f and decreased with the increase in v and γ y , whereas R a decreased with the increase in v and γ y , and increased with d and v. The goodness of fit of the regression equations and model fits (R 2) for F z and R a were found to be 0.968 and 0.970, which demonstrated that it was an effective model. A confirmation test was also conducted in order to verify the correctness of the model.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced machining processes and optimization · Advanced Machining and Optimization Techniques · Advanced Surface Polishing Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (18)
Show source-provided references
1. Donachie MJ Jr, ASM International (2000) Titanium: a technical guide, 2nd edn. Material Information Society, Materials Park, pp 79–8410.31399/asm.tb.ttg2.t61120079 ↗
2. Ezugwu EO, Wang ZM (1997) Titanium alloys and their machinability—a review. J Mater Process Technol 68(3):262–27410.1016/S0924-0136(96)00030-1 ↗
3. Komanduri R, Von Turkovich BF (1981) New observations on the mechanism of chip formation when machining titanium alloys. Wear 69(2):179–18810.1016/0043-1648(81)90242-8 ↗
4. Hong HATJM, Riga AT, Gahoon JM, Scott CG (1993) Machinability of steels and titanium alloys under lubrication. Wear 162:34–3910.1016/0043-1648(93)90481-Z ↗
5. Kramer BM, Hartung PD (1981) Theoretical considerations in the machining of nickel-based alloys. In: Cutting Tool Materials. ASM, Materials Park, Ohio, pp 57–74
6. Noordin MY, Venkatesh VC, Sharif S, Elting S, Abdullah A (2004) Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel. J Mater Process Technol 145(1):46–5810.1016/S0924-0136(03)00861-6 ↗
7. Montgomery DC (1997) Design and analysis of experiments, 4th edn. Wiley, New York
8. Thiele JD, Melkote S (1999) Effect of cutting edge geometry and workpiece hardness on surface generation in the finish hard turning of AISI 52100 steel. J Mater Process Technol 94(2):216–22610.1016/S0924-0136(99)00111-9 ↗
9. Neşeli S, Yaldız S, Türkeş E (2011) Optimization of tool geometry parameters for turning operations based on the response surface methodology. Measurement 44(3):580–58710.1016/j.measurement.2010.11.018 ↗
10. Masounave J, Youssef YA, Beauchamp Y, Thomas M (1997) An experimental design for surface roughness and built-up edge formation in lathe dry turning. Int J Qual Sci 2(3):167–18010.1108/13598539710170803 ↗
11. Makadia AJ, Nanavati JI (2013) Optimization of machining parameters for turning operations based on response surface methodology. Measurement 46(6):1521–152910.1016/j.measurement.2012.11.026 ↗
12. Choudhury IA, El-Baradie MA (1997) Surface roughness prediction in the turning of high-strength steel by factorial design of experiments. J Mater Process Technol 67(1):55–6110.1016/S0924-0136(96)02818-X ↗
13. Fnides B, Yallese MA, Mabrouki T, Rigal JF (2011) Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot work tool steel. Sadhana 36(1):109–12310.1007/s12046-011-0007-7 ↗
14. Saini S, Ahuja IS, Sharma VS (2012) Influence of cutting parameters on tool wear and surface roughness in hard turning of AISI H11 tool steel using ceramic tools. Int J Precis Eng Manuf 13(8):1295–130210.1007/s12541-012-0172-6 ↗
15. Mandal N, Doloi B, Mondal B (2012) Force prediction model of zirconia toughened alumina (ZTA) inserts in hard turning of AISI 4340 steel using response surface methodology. Int J Precis Eng Manuf 13(9):1589–159910.1007/s12541-012-0209-x ↗
16. Tsourveloudis NC (2010) Predictive modelling of the Ti6Al4V alloy surface roughness. J Intell Robot Syst 60(3–4):513–53010.1007/s10846-010-9427-6 ↗
17. Ramesh S, Karunamoorthy L, Palanikumar K (2008) Surface roughness analysis in machining of titanium alloy. Mater Manuf Process 23(2):174–18110.1080/10426910701774700 ↗
18. Makadia AJ, Nanavati JI (2013) Optimization of machining parameters for turning operations based on response surface methodology. Measurement 46(1):1521–152910.1016/j.measurement.2012.11.026 ↗