Skip to main content
SpringerLink
Log in

On-line monitoring of tool wear in turning operation in the presence of tool misalignment

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

Abstract

A vision system using high-resolution CCD camera and back-light was developed for the on-line measurement of nose wear of cutting tool inserts. Initial study showed that the system is sensitive to several factors in the work environment such as misalignment of cutting tool, presence of micro-dust particles, vibration and intensity variation of ambient light. An algorithm using Wiener filtering, median filtering, morphological operations and thresholding was developed to decrease the system error caused by these factors. A conforming method was used to overcome misalignment of the tool insert during offline and on-line measurement. The algorithm, combined with a subtraction method, was applied to measure the nose wear area of the inserts under different machining conditions.

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. Sortino M (2003) Application of statistical filtering for optical detection of tool wear. Int J Mach Tools Manuf 43:493–497

    Article  Google Scholar 

  2. Pfeifer T, Wiegers L (2000) Reliable tool wear monitoring by optimized image and illumination control in machine vision. Measurement 28:209–218

    Article  Google Scholar 

  3. Jun Z, Jianxin D, Jianhua Z, Xing A (1997) Failure mechanisms of a whisker-reinforced ceramic tool when machining nickel-based alloys. Wear 208(1–2):220–225

    Article  Google Scholar 

  4. Ezugwu EO, Bonney J (2004) Effect of high-pressure coolant supply when machining nickel-base, Inconel 718, alloy with coated carbide tools. J Mater Process Technol 153–154:1045–1050

    Article  Google Scholar 

  5. Kassim AA, Mian Z, Mannan MA (2004) Connectivity oriented fast Hough transform for tool wear monitoring. Pattern Recognit 37:1925–1933

    Article  Google Scholar 

  6. Lanzetta M (2001) A new flexible high-resolution vision sensor for tool condition monitoring. J Mater Process Technol 119:73–82

    Article  Google Scholar 

  7. Kwon Y, Fischer GW (2003) A novel approach to quantifying tool wear and tool life measurements for optimal tool management. Int J Mach Tools Manuf 43:359–368

    Article  Google Scholar 

  8. Dimla DES (2000) Sensor signals for tool wear monitoring in metal cutting operations-A review of methods. Int J Mach Tools Manuf 40:1073–1098

    Article  Google Scholar 

  9. Yang MY, Kwon OD (1996) Crater wear measurement using computer vision and automatic focusing. J Mater Process Technol 58:362–367

    Article  Google Scholar 

  10. Wang WH, Hong GS, Wong YS (2006) Flank wear measurement by a threshold independent method with sub-pixel accuracy. Int J Mach Tools Manuf 46(2):199–207

    Article  Google Scholar 

  11. Kurada S, Bradley C (1997) A machine vision system for tool wear assessment. Tribol Int 30(4):294–304

    Article  Google Scholar 

  12. Wong YS, Nee AYC, Li XQ, Riesdorf C (1997) Tool condition monitoring using laser scatter pattern. J Mater Process Technol 63:205–210

    Article  Google Scholar 

  13. Jurkovic J, Korosec M, Kopac J (2005) New approach in tool wear measuring technique using CCD vision system. Int J Mach Tools Manuf 45:1023–1030

    Article  Google Scholar 

  14. Dawson TG, Kurfess TR (2005) Quantification of tool wear using white light interferometry and three-dimensional computational metrology. Int J Mach Tools Manuf 45:591–596

    Article  Google Scholar 

  15. Devillez A, Lesko S, Mozer W (2004) Cutting tool crater wear measurement with white light interferometry. Wear 256:56–65

    Article  Google Scholar 

  16. Wang WH, Wong YS, Hong GS (2006) 3D measurement of crater wear by phase shifting method. Wear 261(2):164–171

    Article  Google Scholar 

  17. Mannan MA, Kassim AA, Jing M (2000) Application of image and sound analysis techniques to monitor the condition of cutting tools. Pattern Recognit Lett 21:969–979

    Article  MATH  Google Scholar 

  18. Choudhury SK, Bartarya G (2003) Role of temperature and surface finish in predicting tool wear using neural network and design of experiments. Int J Mach Tools Manuf 43:747–753

    Article  Google Scholar 

  19. Galbiati LJ (1990) Machine vision and digital image processing fundamentals. Prentice-Hall, Upper Saddle River, NJ, USA

    Google Scholar 

  20. Gonzalez RC, Woods RE, Eddins SL (2004) Digital image processing using Matlab. Pearson-Prentice Hall, Upper Saddle River, NJ, USA

    Google Scholar 

  21. Gonzalez RC, Woods RE (2002) Digital image processing. Pearson Education, Upper Saddle River, NJ, USA

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Engineering Campus, Universiti Sains Malaysia, 14300, Nibong Tebal, Malaysia

    H. H. Shahabi & M. M. Ratnam

Authors
  1. H. H. Shahabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M. M. Ratnam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. M. Ratnam.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shahabi, H.H., Ratnam, M.M. On-line monitoring of tool wear in turning operation in the presence of tool misalignment. Int J Adv Manuf Technol 38, 718–727 (2008). https://doi.org/10.1007/s00170-007-1119-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-007-1119-4

Keywords

Search

Navigation