Advertisement

Assurance of Accuracy of Longitudinal Section of Profile Surfaces Milled at High Feeds

  • A. A. Fomin
  • V. G. Gusev
  • A. R. Sadrtdinov
Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)

Abstract

The article considers the process of profile milling of extended surfaces with shaping cutters and independent factors determining the dominant influence on the optimization parameter as well as the deviation of the longitudinal section profile of the product. One-factor experiments were conducted on the basis of which the operating conditions of the technological system were further determined under which the processing process proceeds steadily with a minimum level of vibration. Under these operating conditions of the technological system, multifactorial experiments were performed. The multifactorial experimental model of the optimization parameter as a function of the elements of the cutting mode was obtained on the basis of which the deviation of the profile of the longitudinal section was simulated in a wide range of values of the independent factors of the profile milling process. The statistical processing of the data of the planned and realized multifactor experiment was carried out, the multifactor model was tested for adequacy and its graphical interpretation was presented which allowed obtaining the scientific data necessary for the well-founded construction of intensive operations of workpiece profile milling.

Keywords

Multifactorial experiment Longitudinal section Milling Mathematical model Cutting tool Cutting speed Processed surface Cutting depth Feed speed 

References

  1. 1.
    Jawahir IS, Van Luttervelt CA (1993) Recent developments in chip control research and applications. CIRP Ann Manuf Technol 42(2):659–693.  https://doi.org/10.1016/S0007-8506(07)62531-1CrossRefGoogle Scholar
  2. 2.
    Vorburger TV, Teague EC (1981) Optical techniques for on-line measurement of surface topography. Precis Eng 3(2):61–83.  https://doi.org/10.1016/0141-6359(81)90038-6CrossRefGoogle Scholar
  3. 3.
    Fomin AA (2013) Kinematics of surface formation in milling. Russ Eng Res 33(11):660–662CrossRefGoogle Scholar
  4. 4.
    Drapalyuk MV et al (2016) Modeling the digging process of tree root system by the mechanism with hydropulse drive. IOP Conf Ser Mater Sci Eng 142:012090.  https://doi.org/10.1088/1757-899X/142/1/012090CrossRefGoogle Scholar
  5. 5.
    Young RD, Vorburger TV, Teague EC (1980) In-process and on-line measurement of surface finish. CIRP Ann Manuf Technol 29(1):435–440.  https://doi.org/10.1016/S0007-8506(07)61366-3CrossRefGoogle Scholar
  6. 6.
    Xiang Su et al (2016) Predictive model of milling force for complex profile milling. Int J Adv Manuf Technol 87(5–8):1653–1662Google Scholar
  7. 7.
    Fomin AA (2017) Microgeometry of surfaces after profile milling with the use of automatic cutting control system. In: Proceedings of 2017, ICIEAM 2017, art. no. 8076117.  https://doi.org/10.1109/icieam.2017.8076117
  8. 8.
    Ohuchi T, Murase YJ (2005) Milling of wood and wood-based materials with a computerized numerically controlled router IV: development of automatic measurement system for cutting edge profile of throw-away type straight bit. Wood Sci 51:278.  https://doi.org/10.1007/s10086-004-0663-xCrossRefGoogle Scholar
  9. 9.
    Stepanov VV et al (2017) Composite material for railroad tie. Solid State Phenom 265:587–591.  https://doi.org/10.4028/www.scientific.net/SSP.265.587CrossRefGoogle Scholar
  10. 10.
    Rehbinder PA, Shchukin ED (1972) Surface phenomena in solids during deformation and fracture processes. Prog Surf Sci 3:97–188.  https://doi.org/10.1016/0079-6816(72)90011-1CrossRefGoogle Scholar
  11. 11.
    Zhou Y, Chen ZC, Tang J, Liu S (2016) An innovative approach to NC programming for accurate five-axis flank milling of spiral bevel or hypoid gears. Comput Aided Des 84:15–24.  https://doi.org/10.1016/j.cad.2016.11.003MathSciNetCrossRefGoogle Scholar
  12. 12.
    Gusev VG, Fomin AA, Sadrtdinov AR (2017) Dynamics of stock removal in profile milling process by shaped tool. Procedia Eng 206:279–285CrossRefGoogle Scholar
  13. 13.
    Su X et al (2016) Predictive model of milling force for complex profile milling. Int J Adv Manuf Technol 87(5):1653–1662.  https://doi.org/10.1007/s00170-016-8589-1CrossRefGoogle Scholar
  14. 14.
    Safin R et al (2016) A mathematical model of thermal decomposition of wood in conditions of fluidized bed. Acta Facultatis Xylologiae Zvolen res Publica Slovaca 58(2):141–148.  https://doi.org/10.17423/afx.2016.58.2.15MathSciNetCrossRefGoogle Scholar
  15. 15.
    Banerjee A, Feng HY, Bordatchev EV (2012) Int J Adv Manuf Technol 59:21.  https://doi.org/10.1007/s00170-011-3478-0CrossRefGoogle Scholar
  16. 16.
    Timerbaev NF, Sadrtdinov AR, Safin RG (2017) Software systems application for shafts strength analysis in mechanical engineering. Procedia Eng 206:1376–1381.  https://doi.org/10.1016/j.proeng.2017.10.648CrossRefGoogle Scholar
  17. 17.
    Popov IA et al (2015) Cooling systems for electronic devices based on the ribbed heat pipe. Russ Aeronaut (Iz VUZ) 58(3):309–314CrossRefGoogle Scholar
  18. 18.
    Song G, Li J, Sun J (2013) Int J Adv Manuf Technol 68:1429.  https://doi.org/10.1007/s00170-013-4932-yCrossRefGoogle Scholar
  19. 19.
    Fomin AA (2017) Determining undeformed chip thickness models in milling and its verification during wood processing. Solid State Phenom 265:598–605CrossRefGoogle Scholar
  20. 20.
    Nakagawa T, Yuzawa T, Sampei M, Hirata A (2017) Improvement in machining speed with working gap control in EDM milling. Precis Eng 47:303–310.  https://doi.org/10.1016/j.precisioneng.2016.09.004CrossRefGoogle Scholar
  21. 21.
    Prosvirnikov DB et al (2017) IOP Conf Ser Mater Sci Eng 221.1:012009.  https://doi.org/10.1088/1755-1315/221/1/012009CrossRefGoogle Scholar
  22. 22.
    Timerbaev NF et al (2017) Gas purification system modeling in fatty acids removing from soapstock. In: Proceedings of 2017, ICIEAM 2017, art. no. 8076418.  https://doi.org/10.1109/icieam.2017.8076418
  23. 23.
    Gusev VG, Fomin AA (2017) Multidimensional model of surface waviness treated by shaping cutter. Procedia Eng 206:286–292CrossRefGoogle Scholar
  24. 24.
    Kolenchenko OV (2010) Influence of the milling conditions on the deformation and quality of the machined surface. Russ Eng Res 30(8):839–844CrossRefGoogle Scholar
  25. 25.
    Novák V, Rousek M, Kopecký Z (2011) Assessment of wood surface quality obtained during high speed milling by use of non-contact method. Drvna industrija 62(2):105–113CrossRefGoogle Scholar
  26. 26.
    Lashkov VA et al (2016) IOP Conf Ser Mater Sci Eng 124:012111.  https://doi.org/10.1088/1757-899X/124/1/012111CrossRefGoogle Scholar
  27. 27.
    Volkov DI, Koryazhkin AA (2012) Russ Eng Res 32:698.  https://doi.org/10.3103/S1068798X12070258CrossRefGoogle Scholar
  28. 28.
    Prosvirnikov DB et al (2017) Modelling heat and mass transfer processes in capillary-porous materials at their grinding by pressure release. In: Proceedings of 2017, ICIEAM 2017, art. no. 8076443.  https://doi.org/10.1109/icieam.2017.8076443
  29. 29.
    Tuntsev DV et al (2016) The mathematical model of fast pyrolysis of wood waste. In: Proceedings of 2015, MEACS 2015. art. no. 7414929.  https://doi.org/10.1109/meacs.2015
  30. 30.
    Fomin AA (2017) Limiting product surface and its use in profile milling design operations. Solid State Phenom 265:672–678.  https://doi.org/10.4028/www.scientific.net/SSP.265.672CrossRefGoogle Scholar
  31. 31.
    Popov IA, Shchelchkov AV, Gortyshov YF et al (2017) High Temp 55(4):524.  https://doi.org/10.1134/S0018151X17030208CrossRefGoogle Scholar
  32. 32.
    Timerbaev NF et al (2017) Application of software solutions for modeling and analysis of parameters of belt drive in engineering. IOP Conf Ser Earth Environ Sci 87(8):082047.  https://doi.org/10.1088/1755-1315/87/8/082047CrossRefGoogle Scholar
  33. 33.
    Fomin AA, Gusev VG (2013) Safe machining of blanks with nonuniform properties. Russ Eng Res 33(10):602–606.  https://doi.org/10.3103/S1068798X13100043CrossRefGoogle Scholar
  34. 34.
    Safin RG et al (2017) Technology of wood waste processing to obtain construction material. Solid State Phenom 265:245–249.  https://doi.org/10.4028/www.scientific.net/SSP.265.245CrossRefGoogle Scholar
  35. 35.
    Anisimova IV, Gortyshov YF, Ignat’ev VN (2016) Russ Aeronaut 59:414Google Scholar
  36. 36.
    Volkov DI, Koryazhkin AA (2014) Adaptive belt grinding of gas-turbine blades. Russ Eng Res 34(1):37–40CrossRefGoogle Scholar
  37. 37.
    Ovcharenko VE, Ivanov KV, Ivanov YF et al (2017) Russ Phys J 59:2114.  https://doi.org/10.1007/s11182-017-1022-xCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Vladimir State UniversityVladimirRussia
  2. 2.Kazan National Research Technological UniversityKazanRussia

Personalised recommendations