Optimised tool life by partial swarm optimisation
Source abstract
Abstract
The aim of the this paper is to develop the tool life prediction model for P20 tool steel with aid of statistical method and find the optimisation values with partial swarm optimisation (PSO), using coated carbide cutting tool. By using Response Surface Method (RSM), first and second order models were developed with 95% confidence level. The tool life model was developed in terms of cutting speed, feed rate, axial depth and radial depth, using RSM. It was found that the feedrate, cutting speed, axial depth and radial depth played a major role. Tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions obtained from PSO are: cutting speed of 100 m/s, federate of 0.1 mm/tooth, axial depth of 1.9596 mm and radial depth of 2 mm. Using these parameters, a tool life of 40.52 min was obtained.
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Research context
OpenAlex topics: Advanced machining processes and optimization · Manufacturing Process and Optimization · Advanced Measurement and Metrology Techniques
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References (15)
Show source-provided references
1. David a. Stephenson and John S . Agapiou (19997) Metal cutting theory and practice, Marcel Dekker, Inc. ISBBN: 08247957792
2. Krar. Ostwald (1995) Technology of Machine Tools,44th Edition; McGraw –Hill.
3. Adrian Sharman, Richard C.Dewes, David K.Aspinwall (2001) Tool life when high speed ball nose end milling Inconel 718, Journal of Materials Processing and Technology,Vol .118, pp. 299-35. doi: 10.11016/S0924-00136(01)008555-X
4. Alaudin, M., EL Baradie, M.A., and Hashmi, M.S.J. (1997) ’Prediction of tool life in end milling by response surface methodology’, Journal off Materials Processing Technology, Vol. 71, pp. 456-465. doi:10 .1016/S0924-0136(97)001111-810.1016/S0924-0136(97)00111-8 ↗
5. Mead, R. and Pike, DD.J. (1975) A review of response surface methodology from a biometric viewpoint, Biometrics, Vol. 31, pp. 8003-851. ISSN: 0006341X10.2307/2529809 ↗
6. Hill, W.J. and Hunter, W.G. (1966) A review of response surface methodology: a literature survey, Technometrics, Vol. 88, pp. 571-590. ISSN: 00401706
7. Hicks, C.R, (1993) Fundamental Concepts in the Design of Experiments, 4th Edition, Saunders College Publishing
8. Childs,T., Maekawa, K., Obikawa, T. , and Ymane, Y. (2000) Metal Machining: Theory and Application, John Wiley & Sons Press.ISBNN:034069159XX
9. Trent, E.M., and Wright, P.K., (2000) Metal Cutting, 4th Edition, Buttwroth-Heinemann Press.10.1016/B978-075067069-2/50007-3 ↗
10. Devillez, A., Lesko, S.., and Mozer, W. (2004) Cutting tool crater wear measurement with white light interferometry, Wear, Vol. 2566, pp. 56–65.. doi: 10.10166/S0043-1648(03)00384-310.1016/S0043-1648(03)00384-3 ↗
11. O’Sullivan, D. and Cotterell, M. (2001)) Temperature measurement in single point turning, Journal of Materials Processing Techhnology, Vol.. 118, ppp. 301–3008. doi: 100.1016/S0924-0136(01)000853-610.1016/S0924-0136(01)00853-6 ↗
12. Wang, J., Huang, C.Z., and Song, W.GG.(2003) The effect of tool flank wear on the orthogonal cutting process and its practical implications, Journal of Materials Processing Technology, Vol. 142, pp.. 338–346. doi: 10.1016/S00924-0136(03))00604-610.1016/S0924-0136(03)00604-6 ↗
13. Chou, Y.K. and Evanss, C.J. (19977) Tool wear mechanism in continuous cutting of hhardened tool steels, Wear, Vol. 22, pp. 59–65.. doi:10.10166/S0043-1648(97)00139-710.1016/S0043-1648(97)00139-7 ↗
14. [14 ] Choudhury, S.K. and Kishore, K.K. (2000) Tool wear measurement in turning using force ratio, International Journal Machine and Tools Manufacture, Vol. 40, pp. 899–911. doi:10.10166/S0890-6955(99)00088-710.1016/S0890-6955(99)00088-7 ↗
15. Yijian Liu, Xiongxiong He “Modeling Identification of Power Plant Thermal Process Based on PSO Algorithm” American Control Conference , Portland, USSA, June 8-100, 2005