A comparative study of linear, random forest and adaboost regressions for modeling non-traditional machining

G Shanmugasundar, M Vanitha, R Čep, V Kumar… - Processes, 2021 - mdpi.com
Non-traditional machining (NTM) has gained significant attention in the last decade due to
its ability to machine conventionally hard-to-machine materials. However, NTMs suffer from …

Predictive modelling framework on the basis of artificial neural network: a case of nano-powder mixed electric discharge machining

M Sana, MU Farooq, S Anwar, R Haber - Heliyon, 2023 - cell.com
In this modern era where Industry 4.0, plays a crucial role in enhancing productivity, quality,
and resource utilization by digitalizing and providing smart operation to industrial systems …

Machine learning techniques for smart manufacturing: a comprehensive review

A Shaikh, S Shinde, M Rondhe… - Industry 4.0 and Advanced …, 2022 - Springer
The smart manufacturing revolution is continuously enabling the manufacturers to achieve
their prime goal of producing more and more products with higher quality at a minimum cost …

Estimation of machinability performance in wire-EDM on titanium alloy using neural networks

UMR Paturi, S Cheruku, S Salike… - Materials and …, 2022 - Taylor & Francis
The impact of process factors on wire-cut electrical discharge machining (WEDM)
performance is complex and nonlinear. In the present work, initially, the WEDM tests were …

Artificial intelligence–built analysis framework for the manufacturing sector: performance optimization of wire electric discharge machining system

K Ishfaq, M Sana, WM Ashraf - The International Journal of Advanced …, 2023 - Springer
In the era of industry 4.0, digitalization and smart operation of industrial systems contribute to
higher productivity, improved quality, and efficient resource utilization for industrial …

Multi-objective optimization of wire electrical discharge machining process using multi-attribute decision making techniques and regression analysis

M Seidi, S Yaghoubi, F Rabiei - Scientific Reports, 2024 - nature.com
Wire electrical discharge machining (WEDM) is one of the most important non-traditional
machining methods that is widely used in various industries. The present research work is …

Machine learning algorithms evaluation and optimization of WEDM of nickel based super alloy: A review

AK Sehgal, SS Nain - Materials Today: Proceedings, 2022 - Elsevier
WEDM commonly used in numerous industries, including as aerospace and aeronautics, to
make superior-quality products at minimal cost and weight while maintaining high accuracy …

Machine learning-based optimization of geometrical accuracy in wire cut drilling

M Ghasempour-Mouziraji, M Hosseinzadeh… - … International Journal of …, 2022 - Springer
Wire cut electrical discharge machining (EDM) equipment is run by computer numerically
controlled (CNC) instruments and it is widely used in various industries such as aerospace …

Prediction of Surface Roughness of Monel K 500 Super Alloy by Using Artificial Neural Network

VD Ganesh, RM Bommi - Materials Science Forum, 2023 - Trans Tech Publ
The surface roughness is a feature that is of tremendous relevance in the assessment of
cutting performance, and it plays an essential part in the manufacturing process as well. In …

Estimation of surface roughness of direct metal laser sintered AlSi10Mg using artificial neural networks and response surface methodology

UMR Paturi, DG Vanga, RB Duggem… - Materials and …, 2023 - Taylor & Francis
Direct metal laser sintering (DMLS) is a metal-specific additive manufacturing (AM)
technique that has grown in efficiency and precision due to compelling advancements in …