Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Development of an online machining process monitoring system: a case study of the broaching process

  • 476 Accesses

  • 17 Citations

Abstract

This paper presents a new online machining process monitoring system based on the PXI hardware platform and the LabVIEW software platform. The whole system is composed of the following interconnected packages: sensing, triggering, data acquisition, characterisation, condition monitoring and feature extraction packages. Several signal processing methods, namely, cross-correlation, resample, short-time Fourier transform (STFT) and statistical process control, are developed to extract the features of tool malfunctions and construct the thresholds of malfunction-free zones. Experimental results show that the developed online process monitoring system is efficient for acquiring, analysing and presenting sensory signals simultaneously, while the developed signal processing techniques are effective for detecting tool wear and constructing thresholds for tool-malfunction-free zones. Additionally, a sensitivity analysis of the signals acquired from alternative sensors versus those collected from a dedicated platform dynamometer has been carried out. This enables the evaluation of the possibility to employ alternative sensing techniques in an industrial environment.

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

References

  1. 1.

    Liang SY, Hecker RL, Landers RG (2004) Machining process monitoring and control: the state-of-the-art. J Manuf Sci Eng—Trans ASME 126(2):297–310

  2. 2.

    Rehorn AG, Jiang J, Orban PE (2005) State-of-the-art methods and results in tool condition monitoring: a review. Int J Adv Manuf Technol 26(7–8):693–710

  3. 3.

    Tlusty J, Andrews GC (1983) A critical review of sensors for unmanned machining. Annals CIRP 32(2):611–622

  4. 4.

    Lee JM, Choi DK, Kim J, Chu CN (1995) Real-time tool breakage monitoring for NC milling process. Annals CIRP 44(1):59–62

  5. 5.

    Stein JL, Wang CH (1990) Analysis of power monitoring on AC induction drive systems. J Dyn Syst Meas Control 112(2):239–248

  6. 6.

    Altintas Y (1992) Prediction of cutting forces and tool breakage in milling from feed drive current measurements. J Eng Ind 114(4):386–392

  7. 7.

    Li X, Djordjevich A, Venuvinod P (2000) Current-sensor-based feed cutting force intelligent estimation and tool wear condition monitoring. IEEE Trans Ind Electron 47(3):697–702

  8. 8.

    Jemielniak K (1999) Commercial tool condition monitoring systems. Int J Adv Manuf Technol 15(10):711–721

  9. 9.

    Du R, Elbestawi MA, Li S (1992) Tool condition monitoring in turning using fuzzy set theory. Int J Mach Tools Manuf 32(6):781–796

  10. 10.

    Zhu R, Devor RE, Kapoor SG (2003) A model-based monitoring and fault diagnosis methodology for free-form surface machining process. J Manuf Sci Eng—Trans ASME 125(3):397–404

  11. 11.

    Jantunen E (2002) A summary of methods applied to tool condition monitoring in drilling. Int J Mach Tools Manuf 42(9):997–1010

  12. 12.

    Varghese B, Pathare S, Gao R, Malkin S (2000) Development of a sensor-integrated “intelligent” grinding wheel for in-process monitoring. Annals CIRP 49(1):231–234

  13. 13.

    Axinte DA, Gindy N (2003) Tool condition monitoring in broaching. Wear 254(3–4):370–382

  14. 14.

    Axinte DA, Gindy N, Fox K, Unaue I (2004) Process monitoring to assist the workpiece surface quality in machining. Int J Mach Tools Manuf 44(10):1091–1108

  15. 15.

    Crochiere RE, Rabiner LR (1983) Multirate digital signal processing. Prentice-Hall, Englewood Cliffs, New Jersey

  16. 16.

    Allen JB, Rabiner LR (1977) A unified approach to short time-time Fourier analysis and synthesis. Proc IEEE 65(11):1558–1564

Download references

Author information

Correspondence to D. Shi.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Shi, D., Axinte, D.A. & Gindy, N.N. Development of an online machining process monitoring system: a case study of the broaching process. Int J Adv Manuf Technol 34, 34–46 (2007). https://doi.org/10.1007/s00170-006-0588-1

Download citation

Keywords

  • Process monitoring
  • Broaching
  • Feature extraction