PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

A simplistic regression-based genetic algorithm optimization of tool-work interface temperature

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This work aims to investigate the average tool-work interface temperature for the HSS tool and AISI 1040 steel pair. A tool-work thermocouple is proposed for the measurement of temperature because of its simple construction in addition to the low cost. The machining process of AISI 1040 steel is considered due to its extensive application, including industry usage. The changes in cutting temperature are studied for combinations of cutting speed, feed and the depth of cut during turning operation. The orthogonal array L9 by Taguchi is adopted for designing the experiments within a restricted set of runs. The average cutting temperature shows an increasing curve with functions of speed versus depth of cut and speed versus feed. But no clear trend is observed for a combination of feed versus depth of cut. A second-order regression equation with reasonable accuracy (R 2 = 0.99) is fitted using the data. Analysis of variance (ANOVA) reveals the highest contribution from cutting speed, which influences average temperature at the interface of tool and work. Further, the genetic algorithm predicts an optimal combination of parameters, which is 82.542 m/min cutting speed, 0.276 mm/rev feed rate and 0.2 mm depth.
Słowa kluczowe
Rocznik
Strony
141--156
Opis fizyczny
Bibliogr. 33 poz., rys., tab., wykr.
Twórcy
autor
  • Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi – 835215, India
autor
  • Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi – 835215, India
  • Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi – 835215, India
  • Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi – 835215, India
  • Department of Mechanical Engineering, Birla Institute of Technology Mesra, Ranchi – 835215, India
autor
  • Department of Mechanical Engineering, Heritage Institute of Technology Kolkata – 700107, India
Bibliografia
  • 1. O’Sullivan D., Cotterell M., Temperature measurement in single point turning, Journal of Materials Processing Technology, 118(1–3): 301–308, 2001, doi: 10.1016/S0924-0136 (01)00853-6.
  • 2. M’Saoubi R., Chandrasekaran H., Investigation of the effects of tool micro-geometry and coating on tool temperature during orthogonal turning of quenched and tempered steel, International Journal of Machine Tools and Manufacture, 44(2–3): 213–224, 2004, doi: 10.1016/j.ijmachtools.2003.10.006.
  • 3. Chinchanikar S., Choudhury S.K., Evaluation of chip-tool interface temperature: effect of tool coating and cutting parameters during turning hardened AISI 4340 steel, Procedia Materials Science, 6: 996–1005, 2014, doi: 10.1016/j.mspro.2014.07.170.
  • 4. Tamerabet Y., Brioua M., Tamerabet M., Khoualdi S., Experimental investigation on tool wear behavior and cutting temperature during dry machining of carbon steel SAE 1030 using KC810 and KC910 coated inserts, Tribology in Industry, 40(1): 52–65, 2018, doi: 10.24874/ti.2018.40.01.04.
  • 5. Ueda T., Al Huda M., Yamada K., Nakayama K., Kudo H., Temperature measurement of CBN tool in turning of high hardness steel, CIRP Annals, 48(1): 63–66, doi: 10.1016/S0007-8506(07)63132-1.
  • 6. Liu X.L., Wen D.H., Li Z.J., Xiao L., Yan F.G., Cutting temperature and tool wear of hard turning hardened bearing steel, Journal of Materials Processing Technology, 129(1–3): 200–206. 2002, doi: 10.1016/S0924-0136(02)00651-9.
  • 7. Dosbaeva G.K., El Hakim M.A., Shalaby M.A., Krzanowski J.E., Veldhuis S.C., Cutting temperature effect on PCBN and CVD coated carbide tools in hard turning of D2 tool steel, International Journal of Refractory Metals and Hard Materials, 50: 1–8, 2015, doi: 10.1016/j.ijrmhm.2014.11.001.
  • 8. Mia M., Dhar N.R., Response surface and neural network based predictive models of cutting temperature in hard turning, Journal of Advanced Research, 7(6): 1035–1044, 2016, doi: 10.1016/j.jare.2016.05.004.
  • 9. Kaminski J., Alvelid B., Temperature reduction in the cutting zone in water-jet assisted turning, Journal of Materials Processing Technology, 106(1–3): 68–73, 2000, doi: 10.1016/S0924-0136(00)00640-3.
  • 10. Dhar N.R., Paul S., Chattopadhyay A.B., Role of cryogenic cooling on cutting temperature in turning steel, Journal of Manufacturing Science and Engineering, 124(1): 146–154, 2002, doi: 10.1115/1.1413774.
  • 11. Gupta M.K., Singh G., Sood P.K., Experimental investigation of machining AISI 1040 medium carbon steel under cryogenic machining: a comparison with dry machining, Journal of The Institution of Engineers (India): Series C, 96: 373–379, 2015, doi: 10.1007/s40032-015-0178-9.
  • 12. Dhar N.R., Islam M.W., Islam S., Mithu M.A.H., The influence of minimum quantity of lubrication (MQL) on cutting temperature, chip and dimensional accuracy in turning AISI-1040 steel, Journal of Materials Processing Technology, 171(1): 93–99, 2006, doi: 10.1016/j.jmatprotec.2005.06.047.
  • 13. Khan M.M.A., Mithu M.A.H., Dhar N.R., Effects of minimum quantity lubrication on turning AISI 9310 alloy steel using vegetable oil-based cutting fluid, Journal of Materials Processing Technology, 209(15–16): 5573–5583, 2009, doi: 10.1016/j.jmatprotec. 2009.05.014.
  • 14. Leshock C.E., Shin Y.C., Investigation on cutting temperature in turning by a tool-work thermocouple technique, Journal of Manufacturing Science and Engineering, 119(4A): 502–508, 1997, doi: 10.1115/1.2831180.
  • 15. Grzesik W., Experimental investigation of the cutting temperature when turning with coated indexable inserts, International Journal of Machine Tools and Manufacture, 39(3): 355–369, 1999, doi: 10.1016/S0890-6955(98)00044-3.
  • 16. Ren X.J., Yang Q.X., James R.D., Wang L., Cutting temperatures in hard turning chromium hard facings with PCBN tooling, Journal of Materials Processing Technology, 147(1): 38–44, 2004, doi: 10.1016/j.jmatprotec.2003.10.013.
  • 17. Dhar N.R., Kamruzzaman M., Cutting temperature, tool wear, surface roughness and dimensional deviation in turning AISI-4037 steel under cryogenic condition, International Journal of Machine Tools and Manufacture, 47(5): 754–759, 2007, doi: 10.1016/ j.ijmachtools.2006.09.018.
  • 18. List G., Sutter G., Bouthiche A., Cutting temperature prediction in high speed machining by numerical modelling of chip formation and its dependence with crater wear, International Journal of Machine Tools and Manufacture, 54–55: 1–9, 2012, doi: 10.1016/j.ijmachtools.2011.11.009.
  • 19. Hosseini S.B., Beno T., Klement U., Kaminski J., Ryttberg K., Cutting temperatures during hard turning – Measurements and effects on white layer formation in AISI 52100, Journal of Materials Processing Technology, 214(6): 1293–1300, 2014, doi: 10.1016/ j.jmatprotec.2014.01.016.
  • 20. Arrazola P.-J., Aristimuno P., Soler D., Childs T., Metal cutting experiments and modelling for improved determination of chip/tool contact temperature by infrared thermography, CIRP Annals, 64(1): 57–60, 2015, doi: 10.1016/j.cirp.2015.04.061.
  • 21. Gosai M., Bhavsar S.N., Experimental study on temperature measurement in turning operation of hardened steel (EN36), Procedia Technology, 23: 311–318, 2016, doi: 10.1016/ j.protcy.2016.03.032.
  • 22. Heigel J.C., Whitenton E., Lane B., Donmez M.A., Madhavan V., Moscoso-Kingsley W., Infrared measurement of the temperature at the tool–chip interface while machining Ti–6Al–4V, Journal of Materials Processing Technology, 243: 123–130, 2017, doi: 10.1016/j.jmatprotec.2016.11.026.
  • 23. Saez-de-Buruaga M., Soler D., Aristimuno˜ P.X., Esnaola J.A., Arrazola P.J., Determining tool/chip temperatures from thermography measurements in metal cutting, Applied Thermal Engineering, 145: 305–314, 2018, doi: 10.1016/j.applthermaleng. 2018.09.051.
  • 24. Soler D., Aristimuno˜ P.X., Saez-de-Buruaga M., Garay A., Arrazola P.J., New calibration method to measure rake face temperature of the tool during dry orthogonal cutting using thermography, Applied Thermal Engineering, 137: 74–82, 2018, doi: 10.1016/j.applthermaleng.2018.03.056.
  • 25. Dessoly V., Melkote S.N., Lescalier C., Modeling and verification of cutting tool temperatures in rotary tool turning of hardened steel, International Journal of Machine Tools and Manufacture, 44(14): 1463–1470, 2004, doi: 10.1016/j.ijmachtools.2004.05.007.
  • 26. Kara F., Aslantas¸ K., C¸ ic¸ek A., Prediction of cutting temperature in orthogonal machining of AISI 316L using artificial neural network, Applied Soft Computing, 38: 64–74, 2016, doi: 10.1016/j.asoc.2015.09.034.
  • 27. Kumar R., Sahoo A.K., Das R.K., Panda A., Mishra P.C., Modelling of flank wear, surface roughness and cutting temperature in sustainable hard turning of AISI D2 steel, Procedia Manufacturing, 20: 406–413, 2018, doi: 10.1016/j.promfg.2018.02.059.
  • 28. Shihab S.K., Khan Z.A., Mohammad A., Siddiqueed A.N., RSM based study of cutting temperature during hard turning with multilayer coated carbide insert, Procedia Materials Science, 6: 1233–1242, 2014, doi: 10.1016/j.mspro.2014.07.197.
  • 29. Mia M., Dhar N.R., Optimization of surface roughness and cutting temperature in highpressure coolant-assisted hard turning using Taguchi method, The International Journal of Advanced Manufacturing Technology, 88: 739–753, 2017, doi: 10.1007/s00170-016-8810-2.
  • 30. Singh V.K., Kumar C., Besra G., Mukhopadhyay A., Barman M., Measurement, modelling and optimization of the average temperature at the tool work interface for turning of AISI 1040 steel using ANN-GA methodology, Engineering Research Express, 3(3): 035020, 2021, doi: 10.1088/2631-8695/ac1958.
  • 31. Yadav R.N., A hybrid approach of Taguchi-Response surface methodology for modeling and optimization of duplex turning process, Measurement, 100: 131–138, 2017, doi: 10.1016/j.measurement.2016.12.060.
  • 32. Rajarajan S., Ramesh Kannan C., Dennison M.S., A comparative study on the machining characteristics on turning AISI 52100 alloy steel in dry and microlubrication condition, Australian Journal of Mechanical Engineering, 20(2): 360–371, 2020, doi: 10.1080/14484846.2019.1710019.
  • 33. Pratihar D.K., Soft Computing: Fundamentals and Applications, Alpha Science International Limited, 2014.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5aad511a-5538-495b-b910-2c21249ab9a7
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.