Predictive modeling of boriding kinetics on armco iron using linear regression approach

Authors

  • Yassine El Guerri Research Laboratory of Industrial Technologies, University of Tiaret, Algeria Author https://orcid.org/0009-0008-9664-2361
  • Bendaoud Mebarek Laboratoire de Recherche en Intelligence ArtificielleetSystèmes, University of Tiaret, Algeria Author https://orcid.org/0000-0002-6838-3867
  • Mourad Keddam Laboratoryof Materials Technology, USTHB, Algiers, Algeria Author https://orcid.org/0000-0002-7721-5830
  • Naima Hadjadj DépartementSM, FacultéST, University of Tissemsilt, Algeria; Laboratoired’Etudes Physique des Matériaux, USTO, Oran, Algeria Author
  • Omar Belguendouz Laboratoire Synthèseet Catalyse, University of Tiaret, Algeria Author
  • Mohammed Amine Khater Laboratoire de Recherche en Technologie de Fabrication Mécanique, ENPO, Oran, Algeria Author

DOI:

https://doi.org/10.62638/ZasMat1283

Abstract

Tools inevitably degrade over time, with lifespans varying based on material and usage.To mitigate this, thermochemical treatments such as boriding are employed. This process forms a boride layer with favorable tribological and mechanical properties. Generally, depending on the processing conditions, the layer may resultin either a mono-phased Fe2B or a bi-phased FeB/Fe2B structure.This study examines a mono-phased Fe2B layer formed by powder pack boriding of Armco Iron.The objective is to predict the thickness of this layer using a linear approach with minimal variables, and to compare the predictions with a more complex approach requiring additional parameters. Results show that both models yield similar predictive capabilities within the available interval, validating the linear model. However, the linear approach shows divergence when applied beyond the investigated interval, indicating limitations in its generalizability.

Keywords:

boride, boriding, layer, linear, regression, thickness

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29-07-2025

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