Machine Learning Algorithms for Predicting Mechanical Stiffness of Lattice Structure-Based Polymer Foam
Polymer foams are extensively utilized because of their superior mechanical and energy-
absorbing capabilities; however, foam materials of consistent geometry are difficult to …
absorbing capabilities; however, foam materials of consistent geometry are difficult to …
[HTML][HTML] Application of the Gradient-Boosting with Regression Trees to Predict the Coefficient of Friction on Drawbead in Sheet Metal Forming
Correct design of the sheet metal forming process requires knowledge of the friction
phenomenon occurring in various areas of the drawpiece. Additionally, the friction at the …
phenomenon occurring in various areas of the drawpiece. Additionally, the friction at the …
Machine learning-driven detection of anomalies in manufactured parts from resonance frequency signatures
L Zhang, S Askar, A Alkhayyat… - Nondestructive …, 2024 - Taylor & Francis
This study aims to enhance the detection and characterisation of anomalies in manufactured
parts by integrating machine learning (ML) with resonance frequency spectra data. A key …
parts by integrating machine learning (ML) with resonance frequency spectra data. A key …
[PDF][PDF] Trzepieci nski
SM Najm - Eng. Sci, 2021 - researchgate.net
Correct design of the sheet metal forming process requires knowledge of the friction
phenomenon occurring in various areas of the drawpiece. Additionally, the friction at the …
phenomenon occurring in various areas of the drawpiece. Additionally, the friction at the …
Triboinformatics approach for prediction of high-stress abrasive wear and coefficient of friction in Al/TiC nanocomposites using machine learning techniques
This study highlights the importance of Al–Fe–Si alloys in modern engineering for their
enhanced hardness, strength, and wear resistance, improving fuel efficiency in the …
enhanced hardness, strength, and wear resistance, improving fuel efficiency in the …
INTEGRATING NEURAL NETWORKS INTO SHEET METAL FORMING: A REVIEW OF RECENT ADVANCES AND APPLICATIONS
In order to predict defects, improve performance, and streamline operations, machine
learning techniques are becoming ever more indispensable in manufacturing processes …
learning techniques are becoming ever more indispensable in manufacturing processes …
Automatic Explanation Of Metal's Phenomena By Application Of Artificial Neural Networks–Use Case For Hot Extruded Aluminum Alloy 6082
T Goričan, M Terčelj, I Peruš - 2024 - preprints.org
Artificial intelligence methods, especially artificial neural networks (ANNs), have recently
been successfully used more and more frequently in the mathematical description of …
been successfully used more and more frequently in the mathematical description of …