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Comparison of various tool wear prediction methods during end milling of metal matrix composite


[ 1 ] Instytut Technologii Mechanicznej, Wydział Budowy Maszyn i Zarządzania, Politechnika Poznańska | [ D ] phd student | [ P ] employee

Scientific discipline (Law 2.0)

[2.9] Mechanical engineering

Year of publication


Published in

Archives of Mechanical Technology and Materials

Journal year: 2018 | Journal volume: vol. 38

Article type

scientific article

Publication language


  • tool wear
  • diagnosis
  • miling
  • metal matrix composite

EN In this paper, the problem of tool wear prediction during milling of hard-to-cut metal matrix composite Duralcan™ was presented. The conducted research involved the measurements of acceleration of vibrations during milling with constant cutting conditions, and evaluation of the flank wear. Subsequently, the analysis of vibrations in time and frequency domain, as well as the correlation of the obtained measures with the tool wear values were conducted. The validation of tool wear diagnosis in relation to selected diagnostic measures was carried out with the use of one variable and two variables regression models, as well as with the application of artificial neural networks (ANN). The comparative analysis of the obtained results enabled the selection of the most effective tool wear prediction method.

Pages (from - to)

1 - 7




License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

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Ministry points / journal in years 2017-2021


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