Integration of Hybrid Machine Learning and Multi-Objective Optimization for Enhanced Turning Parameters of EN-GJL-250 Cast Iron

Integration of Hybrid Machine Learning and Multi-Objective Optimization for Enhanced Turning Parameters of EN-GJL-250 Cast Iron

This study aims to optimize the turning parameters for EN-GJL-250 grey cast iron using hybrid machine learning techniques integrated with multi-objective optimization algorithms. The experimental design focused on evaluating the impact of cutting tool type, testing three tools: uncoated and coated s...

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Bibliographic Details
Main Authors: Yacine Karmi, Haithem Boumediri, Omar Reffas, Yazid Chetbani, Sabbah Ataya, Rashid Khan, Mohamed Athmane Yallese, Aissa Laouissi
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Crystals
Subjects:
cutting parameters
surface roughness
hybrid machine learning
predictive modeling
multi-objective optimization
Online Access:https://www.mdpi.com/2073-4352/15/3/264
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