Skip to main content

Tool Quality Monitoring in Friction Stir Welding Process

  • Conference paper
  • First Online:
Machines, Mechanism and Robotics

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

  • 3894 Accesses

Abstract

The present research aims at monitoring the quality of the tool in an advanced joining technique named friction stir welding by analyzing the force signals. Five tools with different qualities, namely a cracked tool, a tool with a half-pin, material sticking to the pin, tool without a pin, and a healthy tool, have been selected. Discrete wavelet transform has been applied on the acquired signal, and statistical feature of the wavelet coefficients has been extracted which aid in differentiating the selected tools’ condition. The depicted idea will improve the weld quality, reduce rejection of product, and subsequently will help avoid machine downtime which may occur because of a faulty tool.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 299.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 379.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wang L, Gao RX (2006) Condition monitoring and control for intelligent manufacturing. https://doi.org/10.1007/1-84628-269-1

  2. Thomas W, Nicholas E (1997) Friction stir welding for the transportation industries. Mater Des 18:269–273. https://doi.org/10.1016/S0261-3069(97)00062-9

    Article  Google Scholar 

  3. Mishra D, Sahu SK, Mahto RP, Pal SK, Pal K (2019) Friction stir welding for joining of polymers. Springer, Singapore, pp 123–162. https://doi.org/10.1007/978-981-13-0378-4_6

  4. Mishra RS, Ma ZY (2005) Friction stir welding and processing, vol 50. https://doi.org/10.1016/j.mser.2005.07.001

  5. Jain R, Kumari K, Kesharwani RK, Kumar S, Pal SK, Singh SB et al (2015) Friction stir welding: scope and recent development, pp 179–229. https://doi.org/10.1007/978-3-319-20152-8_6

  6. Sahu SK, Mishra D, Mahto RP, Sharma VM, Pal SK, Pal K et al (2018) Friction stir welding of polypropylene sheet. Eng Sci Technol Int J 21:245–254. https://doi.org/10.1016/j.jestch.2018.03.002

    Article  Google Scholar 

  7. Elangovan K, Balasubramanian V (2008) Influences of tool pin profile and welding speed on the formation of friction stir processing zone in AA2219 aluminium alloy. J Mater Process Technol 200:163–175. https://doi.org/10.1016/j.jmatprotec.2007.09.019

    Article  Google Scholar 

  8. Chen C, Kovacevic R, Jandgric D (2003) Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum. Int J Mach Tools Manuf 43:1383–1390. https://doi.org/10.1016/S0890-6955(03)00130-5

    Article  Google Scholar 

  9. Soundararajan V, Atharifar H, Kovacevic R (2006) Monitoring and processing the acoustic emission signals from the friction-stir-welding process. Proc Inst Mech Eng Part B J Eng Manuf 220:1673–1685. https://doi.org/10.1243/09544054JEM586

    Article  Google Scholar 

  10. Kleiner D, Bird CR (2004) Signal processing for quality assurance in friction stir welds. Insight 46:85–87

    Article  Google Scholar 

  11. Fleming P, Lammlein D, Wilkes D, Bloodworth T, Cook G, Strauss A et al (2008) In-process gap detection in friction stir welding. Sens Rev 28(1):62–67. https://doi.org/10.1108/02602280810850044

    Article  Google Scholar 

  12. Jene T, Dobmann G, Wagner G, Eifler D (2008) Monitoring of the friction stir welding process to describe parameter effects on joint quality. Mater Sci 5454:1–11. https://doi.org/10.1007/BF03266668

    Article  Google Scholar 

  13. Fleming PA, Lammlein DH, Wilkes DM, Cook GE, Strauss AM, Delapp DR et al (2009) Misalignment detection and enabling of seam tracking for friction stir welding. Sci Technol Weld Join 14:93–96. https://doi.org/10.1179/136217108X372568

    Article  Google Scholar 

  14. Kumar U, Yadav I, Kumari S, Kumari K, Ranjan N (2015) Defect identification in friction stir welding using discrete wavelet analysis. Adv Eng Softw 85:43–50. https://doi.org/10.1016/j.advengsoft.2015.02.001

    Article  Google Scholar 

  15. Kumari S, Jain R, Kumar U, Yadav I, Ranjan N, Kumari K et al (2016) Defect identification in friction stir welding using continuous wavelet transform. J Intell Manuf 30:1–12. https://doi.org/10.1007/s10845-016-1259-1

    Article  Google Scholar 

  16. Mishra D, Roy RB, Dutta S, Pal SK, Chakravarty D (2018) A review on sensor based monitoring and control of friction stir welding process and a roadmap to Industry 4.0. J Manuf Process 36:373–397. https://doi.org/10.1016/j.jmapro.2018.10.016

    Article  Google Scholar 

  17. Chauhan P, Jain R, Pal SK, Singh SB (2018) Modeling of defects in friction stir welding using coupled Eulerian and Lagrangian method. J Manuf Process 34:158–166. https://doi.org/10.1016/j.jmapro.2018.05.022

    Article  Google Scholar 

  18. Gao RX, Yan R. Wavelets: theory and applications for manufacturing, pp 1–224. https://doi.org/10.1007/978-1-4419-1545-0

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Mishra, D., Roy, R.B., Pal, S.K., Chakravarty, D. (2022). Tool Quality Monitoring in Friction Stir Welding Process. In: Kumar, R., Chauhan, V.S., Talha, M., Pathak, H. (eds) Machines, Mechanism and Robotics. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-0550-5_52

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-0550-5_52

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0549-9

  • Online ISBN: 978-981-16-0550-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics