Micro-geometry Surface Modelling in the Process of Low-Rigidity Elastic-Deformable Shafts Turning

Research Paper


The paper presents a method of modelling roughness parameters in the process of low-rigidity elastic-deformable shafts turning. The developed model assumes that the cutting tool moves relative to the part in accordance with the kinematics of turning. The cutting tool vibrates in conformance with the direction of the thrust component of the machining force, and the cutting edge transfers the profile of its tip onto the part being machined. Moreover, the article contains results of the empirical verification of developed model realized by testing the repeatability of the roughness and waviness parameters of the surface during a 1-year operation of a lathe. Positive results confirm the model can be used for prediction of surface quality parameters in low-rigidity shafts turning.


Turning Surface roughness model Geometrical structure parameters Low-rigidity parts Surface quality 


  1. Altintas Y (2000) Manufacturing automation: metal cutting mechanics, machine tool vibrations and CNC design. Cambridge University Press, CambridgeGoogle Scholar
  2. Arnaud L, Gonzalo O, Seguy S, Jauregi H, Peigne G (2011) Simulation of low rigidity part machining applied to thin-walled structures. Int J Adv Manuf Technol 54:479–488CrossRefGoogle Scholar
  3. Bajić D, Celent L, Jozić S (2012) Modeling of the influence of cutting parameters on the surface roughness, tool wear and cutting force in face milling in off-line process control. J Mech Eng 58:673–682CrossRefGoogle Scholar
  4. Campa FJ, de Lacalle LNL, Urbikain G, Ruiz D (2008) Definition of cutting conditions for thin-to-thin milling of aerospace low rigidity parts. In: Proceedings of the ASME international manufacturing science and engineering conference, vol 1, pp 359–368Google Scholar
  5. Campomanes ML, Altintas Y (2003) An improved time domain simulation for dynamic milling at small radial immersions. Trans ASME J Manuf Sci Eng 125:416–422CrossRefGoogle Scholar
  6. Cardi AA, Firpi HA, Bement MT, Liang SY (2008) Workpiece dynamics analysis and prediction during chatter of turning process. Mech Syst Signal Process 22:1481–1494CrossRefGoogle Scholar
  7. Chen CK, Tsao YM (2006) A stability analysis of regenerative chatter in turning process without using tailstock. Int J Adv Manuf Technol 29:648–654CrossRefGoogle Scholar
  8. Furdui F, Cirstoin CA (2015) Experimental research on surface roughness in turning of E355 alloy steel on CNC machine tool. Appl Mech Mater 760:385–390CrossRefGoogle Scholar
  9. Gola A, Świć A (2011) Computer-aided machine tool selection for focused flexibility manufacturing systems using economical criteria. Actual Probl Econ 124(10):383–389Google Scholar
  10. Hassui A, Diniz AE (2003) Correlating surface roughness and vibration on plunge cylindrical grinding of steel. Int J Mach Tools Manuf 43:855–862CrossRefGoogle Scholar
  11. Huang YA, Liu HM, Yin ZP, Xiong YL (2009) Complex surface machining: thermo-mechanical analysis for error prediction of low-rigidity workpiece. Lecture notes in artificial intelligence, vol 5928, pp 666–677Google Scholar
  12. Jianliang G, Rongdi H (2006) A united model of diametral error in slender bar turning with a follower rest. Int J Mach Tools Manuf 46:1002–1012CrossRefGoogle Scholar
  13. Klosowski G, Gola A, Świć A (2015) Application of fuzzy logic controller for machine load balancing in discrete manufacturing system. In: Jackowski K et al (ed) IDEAL 2015, LNCS 9375, 2015, pp 256–263Google Scholar
  14. Li H, Shin YC (2006) A comprehensive dynamic and milling simulation model. Trans ASME J Manuf Sci Eng 128:86–95CrossRefGoogle Scholar
  15. Litak G, Rusinek R, Teter A (2004) Nonlinear analysis of experimental time series of a straight turning process. Meccanica 39:105–112CrossRefMATHGoogle Scholar
  16. Lopes LGD, Gomes JHD, de Paiva AP, Barca LF, Ferriera JR, Balestrassi PP (2013) A multivariate surface roughness modelling and optimization under conditions of uncertainty. Measurement 8(46):2555–2568CrossRefGoogle Scholar
  17. Lorong P, Coffignal G, Cohen-Assouline S (2008) Simulation du comportement dynamique d’un systeme usinant: modelisation de l’interaction outil/matiere en presence d’une piece flexible. Mec Ind 9:117–124Google Scholar
  18. Pahar I, Bayat M, Bayat M (2015) Variational approach for approximate analytical solution to non-linear natural vibration equations. IJST Trans Mech Eng 39(M1+):237–282Google Scholar
  19. Qi H, Tian Y, Zhang D (2013) Machining forces prediction for peripheral milling of low-rigidity component with curved geometry. Int J Adv Manuf Technol 64:1599–1610CrossRefGoogle Scholar
  20. Ratchev S, Liu S, Huang W, Becker AA (2004) Milling error prediction and compensation in machining of low-rigidity parts. Int J Mach Tools Manuf 44(15):1629–1641CrossRefGoogle Scholar
  21. Ryu SH, Lee HS, Chu CN (2003) The form error prediction in side wall machining considering tool deflection. Int J Mach Tools Manuf 43:731–737CrossRefGoogle Scholar
  22. Świć A, Taranenko W (2012) Adaptive control of machining accuracy of axial-symmetrical low-rigidity parts in elastic-deformable state. Maint Reliab 14(3):215–221Google Scholar
  23. Świć A, Taranenko V, Wolos D (2010) New method for machining of low-rigidity shafts. Adv Manuf Sci Technol 34:59–71Google Scholar
  24. Świć A, Wolos D, Litak G (2014a) Method of control of machining accuracy of low-rigidity elastic-deformable shafts. Lat Am J Solids Struct 11:260–278CrossRefGoogle Scholar
  25. Świć A, Wołos D, Zubrzycki J, Opielak M, Gola A, Taranenko V (2014b) Accuracy control in the machining of low rigidity shafts. Appl Mech Mater 613:357–367CrossRefGoogle Scholar
  26. Świć A, Draczew A, Gola A (2016) Method of achieving accuracy of thermo-mechanical treatment of low-rigidity shafts. Adv Sci Technol Res J 10(29):62–70CrossRefGoogle Scholar
  27. Tahavvor AR, Sepehrinia S (2014) Prediction of the temperature of the hole during the drilling process using artificial neural networks. IJST Trans Mech Eng 38(M1+):269–274Google Scholar
  28. Taranenko G, Taranenko W, Świć A, Szabelski J (2010) Modelling of dynamic system of low-rigidity shaft machining. Maint Reliab 4(48):4–15Google Scholar
  29. Tian LZ, Wu JH, Xiong ZH, Ding H (2015) Active chatter suppression in turning of low-rigidity workpiece by system matching. Lecture notes in artificial intelligence, vol 9245, pp 609–618Google Scholar
  30. Tlusty J (2000) Manufacturing processes and equipment. Prentice Hall, Upper Saddle RiverGoogle Scholar
  31. Urbicain G, Olvera D, Fernández A, Rodríguez A, Tabernero I, López de Lacalle LN (2012) Stability lobes in turning of low rigidity components. Adv Mater Res 498:231–236CrossRefGoogle Scholar
  32. Zhe-Zhu X, Xiao-Jing L, Sung-Ki L (2014) Study on positioning accuracy of nut/shaft air cooling ball screw for high-precision feed drive. Int J Precis Eng Manuf 15(1):111–116CrossRefGoogle Scholar

Copyright information

© Shiraz University 2016

Authors and Affiliations

  1. 1.Institute of Technological Systems of Information, Faculty of Mechanical EngineeringLublin University of TechnologyLublinPoland
  2. 2.Department of Enterprise Organization, Faculty of ManagementLublin University of TechnologyLublinPoland
  3. 3.Institute of Transport, Combustion Engines and Ecology, Faculty of Mechanical EngineeringLublin University of TechnologyLublinPoland

Personalised recommendations