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Prediction of the surface roughness of wood for machining

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Abstract

The surface quality of solid wood is very important for its effective response in manufacturing processes. The effects of feed rate, cutting depth and rake angle on surface roughness and power consumption were investigated and modeled. Neuro-fuzzy methodology was applied and shown that it could be useful, reliable and an effective tool for modeling the surface roughness of wood. Thus, the results of the present research can be successfully applied in the wood industry to reduce time, energy and high experimental costs.

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Authors and Affiliations

  1. High School, Applied Professional Studies, Filipa Filipovića 20, Vranje, 17500, Serbia

    Damjan Stanojevic

  2. Faculty of Forestry, University of Belgrade, Kneza Višeslava 1, Belgrade, 11000, Serbia

    Marija Mandic, Gradimir Danon & Srdjan Svrzic

Authors
  1. Damjan Stanojevic
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  2. Marija Mandic
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  3. Gradimir Danon
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  4. Srdjan Svrzic
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Corresponding author

Correspondence to Damjan Stanojevic.

Additional information

The online version is available at http://www.springerlink.com

Corresponding editor: Yu Lei.

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Stanojevic, D., Mandic, M., Danon, G. et al. Prediction of the surface roughness of wood for machining. J. For. Res. 28, 1281–1283 (2017). https://doi.org/10.1007/s11676-017-0401-z

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  • DOI: https://doi.org/10.1007/s11676-017-0401-z

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