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Development of process monitoring system in drilling process using fuzzy rules

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Abstract

This study describes the development of process monitoring system in drilling process in high speed machining center. The system monitors the several state variables of the cutting process of a drill. However, the thrust force and torque signals have been chosen to detect and monitor the drilling process, the acoustic emission signal has been also analyzed. Experimental data have allowed defining statistical behavior of the variables for non-fault conditions, tool wear and breakage. The new approach in this project is to use the standard data acquisition software LabVIEW for the purpose of data collection, signal analysis, decision making and sending back the message to the machine.

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References

  • Abele E, Versch A, Ekinovic S, Kulas N (2002) Drilling at the stability limits with mechatronic toolholders. In: Cebalo R, Zagreb HS. International Scientific Conference on Production Engineering. Computer integrated manufacturing and high speed machining, June 13–14, 2002, Brijuni, Croatia

  • Al-Habaibeh A, Liu G, Gindy N (2002) Sensor fusion for an integrated process and machine condition monitoring system, 15th Triennial World Congress, Barcelona, Spain

  • Bishop H (2001) Robert: student edition LabVIEW 6i. National Instrument, Prentice Hall, Austin, TX

    Google Scholar 

  • Carr JJ (1988) Data acquisition and control. In: Microcomputer applications for scientists and engineers, Tab Books Inc., Blue Ridge Summit, PA

  • Dominguez AR, DeMiguel Gonzalez LJ (2002) Fault diagnosis of multi-tooth machine tool based on statistical signal processing, 2002 IFAC 15th Triennial World Congress, Barselona, Spain

  • Dornfeld DA (1998) Monitoring of ultraprecision machining processses. 8th International Machine Tool Engineers Conference (IMEC), Osaka

  • Kirchheim A, Wlfer P (1998) Sensor fused intelligent monitoring system for machining, Kistler

  • Landers RG, Ulsoy AG (2002) Process monitoring and control of machining operations, The University of Michigan, Ann Arbor, Michigan

  • Liang SY, Hecker RL, Landers RG (2002) Machining process monitoring and control: the state-of-the-art, Proceedings of IMECE2002, New Orleans, Louisiana

  • Narayanan SB, Fang J, Bernard G, Atlas L (1994) Feature representations for monitoring of Tool Wear, Proceedings of the 1994 IEEE ICASSP, vol 6, pp 137–140

  • Pontuale G, Farrelly FA, Petri A, Pitolli L, Krogh F (2001) Properties of acoustic emission signals for tool condition monitoring (TCM) applications In: Proceedings of 17th international congress on acoustics, Rome

  • Smith GT (1993) CNC machining technology, Springer-Verlag, London

  • Thyer GE (1988) Computer numerical control of machine tools. Heinemann Professional Publishing Ltd, London

    Google Scholar 

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Correspondence to Hla Myo Tun.

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Tun, H.M., Kyaw, M. & Naing, Z.M. Development of process monitoring system in drilling process using fuzzy rules. Int J Syst Assur Eng Manag 2, 78–83 (2011). https://doi.org/10.1007/s13198-011-0054-9

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  • DOI: https://doi.org/10.1007/s13198-011-0054-9

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