In-Process Prediction of Surface Roughness for High-Precision Grinding by Utilizing Power Sensor and Artificial Neural Network

Machine learning-assisted prediction and Bayesian optimisation of wire EDM process parameters for surface roughness of AISI S7 tool steel

AISI S7 tool steel finds application in aerospace, automotive, and tooling industries for its high toughness and impact resistance. Machining this material with acceptable quality remains challenging. This study investigates the influence of Wire Electrical Discharge Machining (WEDM) process parameters, including pul...

Data-driven prediction and surrogate-based parameter selection for density and surface roughness in SLM of 316L SS under data scarcity

Optimization of surface roughness and tool life during the milling of zirconium alloy using response surface methodology and machine learning model

Commercially, zirconium alloys are beneficial for nuclear power generation with the capacity to increase electricity output. This study employed the Response Surface Methodology (RSM) and Machine Learning (ML) model validated by physical machining experiments to investigate the surface roughness (SR) and tool life (TL)...

Machine Learning Based Predictive Modeling of Machining Performance of Ti-6Al-4V under MQL Lubricating Conditions

Evaluating the performance of machined Ti-6AI-4V alloy under Minimum Quantity lubrication (MQL) using machine learning models to support sustainable and efficient milling found the developed models offer a reliable data-driven framework for optimizing machining parameters and improving sustainability.

Data driven prediction of overcut in electrical discharge drilling of Ti-6Al-4V using machine learning for process improvement

Feature Selection and Multivariate Regression for Paper Surface Roughness Prediction

Paper surface roughness is an important quality parameter because it affects coating quality, printability, and the final appearance of paper. Accurate prediction of roughness remains challenging due to the large number of correlated variables monitored throughout the papermaking process. This study compares three feat...