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Surface roughness evaluation in hardened materials by pattern recognition using network theory

International Journal on Interactive Design and Manufacturing (IJIDeM) volume 13, pages 211–219 (2019)Cite this article

Abstract

Performance characteristics of the products made of metallic materials such as wear resistance, fatigue strength, stability of gaps and strain between the connections, corrosion resistance, etc., depend to a large extent by the quality of their surfaces roughness. An interactive control of the manufacturing parameters which influence the surface roughness is particularly crucial in the construction of many mechanical components. The present paper devises a new method for statistical pattern recognition on samples produced by the process of robot laser hardening using network theory and describes its application to the determination of surface roughness. The method is based on the analysis of SEM images. Indeed the data characterizing the state of surface irregularities detected as extremely small segments contain indicators of surface roughness. Different methods of machine learning techniques designed to predict the surface roughness of robot laser hardened material are discussed.

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Authors and Affiliations

  1. Jožef Stefan Institute, Ljubljana, Slovenia

    Matej Babič

  2. Department of Electrical, Electronic and Computer Engineering, University of Catania, Catania, Italy

    Michele Calì

  3. Kyiv National University of Construction and Architecture, Kiev, Ukraine

    Ivan Nazarenko

  4. Alma Mater Studiorum University of Bologna, Bologna, Italy

    Cristiano Fragassa

  5. University of Zenica, Zenica, Bosnia and Herzegovina

    Sabahudin Ekinovic

  6. Faculty of Materials, Metallurgy and Recycling, Kosice, Slovakia

    Mária Mihaliková

  7. Faculty of Mechanical Engineering, University of Montenegro, Podgorica, Montenegro

    Mileta Janjić

  8. Institute of Metals and Technology, Ljubljana, Slovenia

    Igor Belič

Authors
  1. Matej Babič
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  2. Michele Calì
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  3. Ivan Nazarenko
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  4. Cristiano Fragassa
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  5. Sabahudin Ekinovic
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  6. Mária Mihaliková
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  7. Mileta Janjić
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  8. Igor Belič
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Correspondence to Matej Babič.

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Babič, M., Calì, M., Nazarenko, I. et al. Surface roughness evaluation in hardened materials by pattern recognition using network theory. Int J Interact Des Manuf 13, 211–219 (2019). https://doi.org/10.1007/s12008-018-0507-3

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  • DOI: https://doi.org/10.1007/s12008-018-0507-3

Keywords

  • Surface roughness
  • Machine interactive learning
  • Statistical pattern recognition
  • Robot laser hardening
  • SEM images