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March 5, 2026Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science1 citations

Prediction of drilling characteristics of crab carapace- coir-polymer composites using artificial neural network

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NBN. S. BalajiSRS. RajamuneeswaranBBBoopathi Rajan Marxim Rahula Bharath

Key Points

  • The aim is to predict the drilling characteristics of crab carapace-coir composite materials using artificial neural networks.
  • Full factorial design to assess drilling parameters
  • Variables include drill bit diameter, feed rate, and spindle speed
  • ANN model used for prediction of drilling performance
  • Optimal conditions reduce delamination to 1.05 while ensuring structural strength
  • Achieved thrust of 100 N and torque of 5.0 N-m
  • ANN model predicts parameters with an average absolute percentage error of less than 3%

Abstract

This study examines the drilling characteristics of crab carapace-impregnated coir polyester composite material. The chemical structure of the crab carapace offers better mechanical properties; however, optimizing drilling performance in a full factorial design under various drilling conditions, with the parameters of drill bit diameter, feed rate, and spindle speed. A reduction in feed rate combined with a small drill diameter and high spindle speed creates the optimal conditions to minimize the delamination value of 1.05 while maintaining structural strength and producing a strong thrust of 100 N and torque effects of 5.0 N-m on the composite material. The ANN was used to predict the drilling parameters, and the ANN model provides a precise prediction of drilling parameters within the defined boundaries for improved operation efficiency of this composite material, with average absolute percentage error of less than 3%. The ANN-based methodology shows efficient modeling capabilities for drilling operations in complex structured composite materials.

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Cite This Study

Balaji et al. (2026) studied this question.

synapsesocial.com/papers/69a91d6dd6127c7a504c039bhttps://doi.org/10.1177/09544062261422008
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