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October 9, 2025Engineering Technology & Applied Science ResearchOpen Access

Predicting the Resultant Cutting Force in Hard Turning Using Machine Learning Techniques

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Authors

CMChahrazed Hiba MimounKHKamel HaddoucheSMSouâd Makhfi

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Overview

Machine learning techniques predict resultant cutting force in machining AISI 52100 steel, highlighting ANFIS effectiveness.

Key Points

  • Predicted cutting force performance is enhanced with machine learning techniques like ANFIS.
  • Adaptive neuro-fuzzy inference system showed superior results compared to other machine learning models.
  • Model inputs include workpiece hardness, cutting speed, feed, and depth-of-cut for accurate force predictions.
  • Comparative analysis with experimental data confirms the validity of the models used.

Cite This Study

Mimoun et al. (2025) studied this question.

synapsesocial.com/papers/68e70db790569dd607ee64c7https://doi.org/10.48084/etasr.11759
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