Bootstrap analysis for predicting circularity and cylindricity errors in palm/jute fiber reinforced hybrid composites

  • Mohamed Slamani
  • , Abdelmalek Elhadi
  • , Salah Amroune
  • , Mustapha Arslane
  • , Moussa Zaoui
  • , Nashmi Alrasheedi
  • , Borhen Louhichi
  • , Jean François Chatelain

Résultats de recherche: Contribution à un journalArticle publié dans une revue, révisé par les pairsRevue par des pairs

3 Citations (Scopus)

Résumé

Hybrid composites reinforced with palm and jute fibers are increasingly valued in modern manufacturing due to their exceptional strength-to-weight ratio and eco-friendly properties. This study examines the drilling process of these hybrid composites, with a focus on circularity and cylindricity errors as key indicators of hole quality. The composite material was composed of 15 % palm fibers and 15 % jute fibers by weight. A distinguishing feature of this research is the innovative use of bootstrap analysis to quantify uncertainty in predicting circularity and cylindricity errors. The investigation explored the effects of spindle speed and feed rate on machining outcomes, uncovering intricate interdependencies between these parameters. Results show that lower spindle speeds yield more precise and consistent hole quality, while higher speeds increase variability. Two regression models were developed to predict circularity and cylindricity errors, demonstrating strong predictive accuracy with R-squared values of 0.91 and 0.95, respectively. The application of bootstrap analysis further validated the robustness of these models by providing detailed uncertainty estimates across a range of cutting conditions. Machining conditions associated with minimal errors were determined at a spindle speed of 1592 rpm and a feed rate ranging from 0.08 mm/rev to 0.12 mm/rev, yielding circularity errors as low as 44 µm and cylindricity errors of 59 µm.

langue originaleAnglais
Numéro d'article117042
journalMeasurement: Journal of the International Measurement Confederation
Volume249
Les DOIs
étatPublié - 31 mai 2025

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  1. SDG 9 – Industrie, innovation et infrastructure
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