Journal of Materials Science

, Volume 42, Issue 20, pp 8725–8737 | Cite as

Cutting characteristics of beard hair

  • S. M. Thozhur
  • A. D. CrocombeEmail author
  • P. A. Smith
  • K. Cowley
  • M. Mullier


The cutting behaviour of beard hair has been investigated quantitatively and qualitatively. High speed cutting tests were conducted on beard hair samples using a purpose built cutting rig (provided by Gillette, UK) to determine the cutting forces. High speed digital video photography was used to record the cutting process. In parallel with these tests, low speed cutting tests were undertaken within a scanning electron microscope (SEM) to gain a better understanding of the cutting process. Results from the high speed cutting tests showed that the peak cutting stresses are influenced strongly by moisture (the cutting stress for ‘wet’ samples is reduced by about 30% as compared to dry samples) while the effects on the cutting stress of other variables (subject age, blade approach angle and sample ageing due to prolonged storage) appeared to be less noticeable. The angle of cut was affected by the distance of the initial contact point (between the hair and the blade) from the base of the hair with the line of cut shifting towards the hair axis with increasing distance from the base. Qualitative observations from video-recordings and still images taken during the cutting tests, conducted in-situ within the SEM as well as the high speed cutting rig, showed four main cutting mechanisms of hair, which are documented in this paper. The distance from the initial contact point to the base of the hair and the moisture level were the parameters which controlled the mechanism of failure. Qualitative observations of the sort reported here are a necessary pre-cursor to the development of finite element models to simulate a cutting operation.


Hair Sample Scalp Hair Blade Angle Cutting Test Hair Surface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors would like to acknowledge the sponsorship offered by The Gillette Company to facilitate the research work discussed in this paper and the co-operation extended by the organisation through granting access to the high-speed cutting rig/video-recording apparatus.


  1. 1.
    Thozhur SM, Crocombe AD, Smith PA, Mullier M, Cowley K (2006) J Mat Sci 41(4):1109CrossRefGoogle Scholar
  2. 2.
    Dawber RPR (1986) Bioeng Skin 2:1Google Scholar
  3. 3.
    Dawber R (1996) Clin Dermatol 14:105CrossRefGoogle Scholar
  4. 4.
    Jones LN (2001) Clin Dermatol 19:95CrossRefGoogle Scholar
  5. 5.
    Swift JA (1991) Intl J Cosmet Sci 13:143CrossRefGoogle Scholar
  6. 6.
    Swift JA (1997) AIM J EXS 78:149Google Scholar
  7. 7.
    Watanabe H, Yahagi K. (1992) Jpn J Tribol 37(4):427Google Scholar
  8. 8.
    Feughelman M (1997) Cosmet Sci Technol Ser 17:1Google Scholar
  9. 9.
    Feughelman M (1982) J Soc Cosmet Chem 33:385Google Scholar
  10. 10.
    Sakai M, Nagase S, Okada T, Satoh N, Tsujii K (2000) Bull Chem Soc Jpn 73:2169CrossRefGoogle Scholar
  11. 11.
    Feughelman M (1964) Textile Res J 34:539CrossRefGoogle Scholar
  12. 12.
    Feughelman M (1994) Textile Res J 64(4):236Google Scholar
  13. 13.
    Deem D, Rieger MM (1976) J Soc Cosmet Chem 27:579Google Scholar
  14. 14.
    Trusty PA (1994) PhD thesis (University of Surrey)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • S. M. Thozhur
    • 1
  • A. D. Crocombe
    • 1
    Email author
  • P. A. Smith
    • 1
  • K. Cowley
    • 2
  • M. Mullier
    • 2
  1. 1.School of EngineeringUniversity of SurreyGuildfordUK
  2. 2.Gillette Management Inc.ReadingUK

Personalised recommendations