Skip to main content
SpringerLink
Log in

Tool condition monitoring in an end-milling operation based on the vibration signal collected through a microcontroller-based data acquisition system

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

Abstract

Machine condition plays an important role in machining performance. A machine condition monitoring system will provide significant economic benefits when applied to machine tools and machining processes. Development of such a system requires reliable machining data that can reflect machining processes. This study demonstrates a tool condition monitoring approach in an end-milling operation based on the vibration signal collected through a low-cost, microcontroller-based data acquisition system. A data acquisition system has been built through interfacing a microcontroller with a signal transducer for collecting cutting vibration. The examination tests of this developed system have been carried out on a CNC milling machine. Experimental studies and data analysis have been performed to validate the proposed system. The onsite tests show the developed system can perform properly as proposed.

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. Al-Habaibeh A, Gindy N (2000) A new approach for systematic design of condition monitoring systems for milling operations. J Mater Process Technol 107:243–251

    Article  Google Scholar 

  2. Frankowiak M, Grosvenor R, Prickett P (2005) A review of the evolution of microcontroller-based machine and process monitoring. Int J Mach Tools Manuf 45:578–582

    Article  Google Scholar 

  3. DeGarmo EP, Black JT, Kohser RA (1997) Materials and processes in manufacturing, 8th ed. Prentice Hall, Upper Saddle River, NJ

    Google Scholar 

  4. Chen S, Jen YW (2000) Data fusion neural network for tool condition monitoring in CNC milling machining. Int J Mach Tools Manuf 40(3):381–400

    Article  Google Scholar 

  5. Al-Habaibeh A, Zorriasatine F, Gindy N (2002) Comprehensive experimental evaluation of a systematic approach for cost effective and rapid design of condition monitoring systems using Taguchi’s method. J Mater Process Technol 124:372–383

    Article  Google Scholar 

  6. Milfelner M, Cus F, Balic J (2005) An overview of data acquisition systems for cutting force measuring and optimization in milling. J Mater Process Technol 164:1281–1288

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Tzeng Y, Jean M (2005) Dimensional quality of optimization of high-speed CNC milling process with dynamic quality characteristic. Robot Comput-Integr Manuf 21:506–517

    Article  Google Scholar 

  9. Ertekin YM, Kwon Y, Tseng T (2003) Identification of common sensory features for the control of CNC milling operations under varying cutting conditions. Int J Mach Tools Manuf 43(9):897–904

    Article  Google Scholar 

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

    Article  Google Scholar 

  11. Chung KT, Geddam A (2003) A multi-sensor approach to the monitoring of end milling operations. J Mater Process Technol 139:15–20

    Article  Google Scholar 

  12. Zhang Z, Chen JC (in press) Development of an in-process surface roughness adaptive control in end milling operations. Int J Adv Manuf Technol 31:877–887

    Article  Google Scholar 

  13. Shearman S (2003) Machine condition monitoring, part 1: vibration acquisition and analysis. Sensors. Retrieved August 29, 2007 from http://archives.sensorsmag.com/articles/0503/16/

  14. Smith G, Lee S (2005) A method for detecting tool wear on a CNC lathe using a doppler radar detector. Int J Adv Manuf Technol 25:270–280

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Technology, University of Northern Iowa, 32 ITC, Cedar Falls, IA, 50614, USA

    Julie Z. Zhang

  2. Department of Agriculture and Biosystems Engineering, Iowa State University, Ames, IA, USA

    Joseph C. Chen

Authors
  1. Julie Z. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joseph C. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julie Z. Zhang.

Additional information

All rights reserved. This study, or parts thereof, may not be reproduced in any form without written permission of the authors. This paper has not been published nor has it been submitted for publication elsewhere.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, J.Z., Chen, J.C. Tool condition monitoring in an end-milling operation based on the vibration signal collected through a microcontroller-based data acquisition system. Int J Adv Manuf Technol 39, 118–128 (2008). https://doi.org/10.1007/s00170-007-1186-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-007-1186-6

Keywords

Search

Navigation