Skip to main content
SpringerLink
Log in

Chatter prediction in turning process of conical workpieces by using case-based resoning (CBR) method and taguchi design of experiment

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abtract

The detection of undesirable vibrations in turning operations is an important task for a manufacturing engineer. Many different approaches were used to chatter detection on turning processes though they need complex analysis and expensive equipment. Case-based reasoning (CBR) is a method that seems to solve many problems addressed in knowledge-based (KB) systems. CBR includes nonlinear calculating units called nodes. The data used for the system performance derived from experiments conducted on a turning machine according to the principles of Taguchi design of experiments (DOE) method. In this research, image processing and machine vision (IPMV) approach and CBR have been carried out to chatter detection. In CBR, by using a large number of nodes on the systems, 4 MΩ quartz crystal oscillator and increasing sampling rate from 7.5 to 30 K/s accurate system could be obtained with 6.55% mean square error (MSE) in comparison to IPMV and neural network that has 14.60% and 8.5% MSE, respectively. Also another special ability of the CBR system is detecting chatter from two materials simultaneously by separate input signals into two materials and downsampling the output of both filters through those materials by using low-pass filter.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Venkatamaran S, Krishnan R, Rao KK (1993) A rule-rule-case based system for image analysis. In: 1st Euro Conf. on Case-based Reasoning. 2, pp 410–415

  2. Aamodt A, Plaza E (1994) Case-based reasoning methodological variations and system approaches. J AI Commun 7:39–59

    Google Scholar 

  3. Bickraj K, Demetgul M, Tansel IN, Kaya B, Ozcelik B (2008) Detection of the development of chatter in end milling operation by using index base reasoning (IBR), Proceedings of ECTC ASME Early Career Technical Conference October 3–4, Miami, Florida, USA

  4. Finnie GR, Wittig GE, Desharnais JM (1997) Estimating software development effort with case-based reasoning, 2nd Intl. Conf. on Case-Based Reasoning, pp 13–22

  5. Tobias SA (1965) Machine tool vibration, 1st edn. Blackie, London

    Google Scholar 

  6. Saffury J, Altus E (2009) Optimized chatter resistance of viscoelastic turning bars. J Sound Vib 324:26–39

    Article  Google Scholar 

  7. Budak E, Ozlu E (2007) Annals analytical modeling of chatter stability in turning and boring operations: a multi-dimensional approach of the CIRP 56(1), pp 401–404

  8. Cardi AA, Firpi HA, Bement MT, Liang SY (2008) Workpiece dynamic analysis and prediction during chatter of turning process. Mech Syst Sig Process 22:1481–1494

    Article  Google Scholar 

  9. Tangjitsitcharoen S, Moriwakib T (2008) Intelligent monitoring and identification of cutting states of chips and chatter on CNC turning machine. J Manuf Processes 10:40–46

    Article  Google Scholar 

  10. Clancy BE, Shin YC (2002) A comprehensive chatter prediction model for face turning operation including tool wear effect. Int J Mach Tools Manuf 42:1035–1044

    Article  Google Scholar 

  11. Anderson CS, Semercigil SE, Turan OF (2007) A passive adaptor to enhance chatter stability for end mills was inspected. Int J Mach Tools Manuf 47:1777–1785

    Article  Google Scholar 

  12. Kima HY, Shenb YF, Ahna JH (2002) Development of a surface roughness measurement system using reflected laser beam. J Mater Process Technol 130–131:662–667

    Article  Google Scholar 

  13. Rajaram Narayanan M, Gowri S, Murali Krishna M (2007) On Line Surface Roughness Measurement Using Image Processing and Machine Vision Proceedings of the World Congress on Engineering 2007 Vol I WCE 2007, July 2–4, London, UK

  14. Devillez A, Dudzinski D (2007) Tool vibration detection with eddy current sensors in machining process and computation of stability lobes using fuzzy classifiers. Mech Syst Sig Process 21(1):441–456

    Article  Google Scholar 

  15. Benardos PG, Vosniakos GC (2002) Prediction of surface roughness in CNC face milling using neural networks and Taguchi’s design of experiments. Robot Comput-Integr Manuf 18:343–354

    Article  Google Scholar 

  16. Sori E, Narimani R, Rohani Esfehani E (2007) Optimization cutting parameters by using multi variable genetic algorithm, In proceeding of 1st National Conference of Manufacturing and Design, Najaf Abad, NMEC 4–5 February, Isfehan, Iran, pp208

  17. Lez-Brambila OG, Rubio E, Jauregui JC, Herrera-Ruiz G (2006) Chattering detection in cylindrical grinding processes using the wavelet transform. Int J Mach Tools Manuf 46:1934–1938

    Article  Google Scholar 

  18. Lee BY, Tarng YS (2001) Surface roughness inspection by computer vision in turning operations. Int J Mach Tools Manuf 41:1251–1263

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of High Technology Engineering, Iran University of Industries and Mines, 578-Hafez Street-Karimkhan BLV, Tehran, Iran

    Amir Mahyar Khorasani, Abdolhossein Jalali Aghchai & Ali Khorram

Authors
  1. Amir Mahyar Khorasani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Abdolhossein Jalali Aghchai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ali Khorram
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amir Mahyar Khorasani.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Khorasani, A.M., Jalali Aghchai, A. & Khorram, A. Chatter prediction in turning process of conical workpieces by using case-based resoning (CBR) method and taguchi design of experiment. Int J Adv Manuf Technol 55, 457–464 (2011). https://doi.org/10.1007/s00170-010-3060-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-010-3060-1

Keywords

Search

Navigation