The Transformation of Manufacturing by Artificial Intelligence DOI
Dipan Kumar Das, Priyambada Mallick, Siddharth Parthasarathy

et al.

Advances in logistics, operations, and management science book series, Journal Year: 2024, Volume and Issue: unknown, P. 42 - 73

Published: March 4, 2024

The combination of artificial intelligence (AI) and industrial momentum heralded a revolution in product design, manufacturing, optimization. This summary provides an overview the transformative changes brought by business through integration AI technology explores various factors influencing process quality innovation. Faced with need for precision efficiency, companies have adopted as revolutionary tool. Through real-world case study, this research how AI-based optimization can modify turbine blades to improve aerodynamic efficiency while reducing associated design testing costs. will also take closer look at field additive showing 3D printing based on algorithms is revolutionizing traditional manufacturing processes.

Language: Английский

Additive Manufacturing Modification by Artificial Intelligence, Machine Learning, and Deep Learning: A Review DOI Creative Commons
Mohsen Soori, Fooad Karımı Ghaleh Jough, Roza Dastres

et al.

Deleted Journal, Journal Year: 2025, Volume and Issue: unknown, P. 200198 - 200198

Published: Feb. 1, 2025

Language: Английский

Citations

3
Exploring Conductive Filler‐Embedded Polymer Nanocomposite for Electrical Percolation via Electromagnetic Shielding‐Based Additive Manufacturing DOI

Nilam Qureshi,

Vivek Dhand, Shaik Subhani

et al.

Advanced Materials Technologies, Journal Year: 2024, Volume and Issue: unknown

Published: April 18, 2024

Abstract This review delves into the progress made in additive manufacturing through incorporation of conductive fillers nanocomposites. Emphasizing critical role percolation and conductivity, study highlights advancements material selection, particularly focusing on carbon nanotubes with low thresholds. The practical applications these nanocomposites polymer composites are explored, emphasizing understanding Furthermore, present paper investigates potential materials as lightweight alternatives for electromagnetic interference shielding (EMI), key sectors such automotive aerospace industries. integration advanced materials, modeling techniques, standardization is discussed pivotal successful implementation. Overall, underscores significant strides enhancing electrical properties capabilities strategic use filler manufacturing.

Language: Английский

Citations

13
Recent progress in scientific machine learning for numerical solutions of partial differential equations DOI

Eunbin Koh,

Namjung Kim

JMST Advances, Journal Year: 2025, Volume and Issue: unknown

Published: May 12, 2025

Language: Английский

Citations

0
AI-driven DfAM of aeronautical hydrogen gas turbine combustors DOI

Alberto Boretti,

Aijun Huang

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 77, P. 851 - 862

Published: June 20, 2024

Language: Английский

Citations

2
Measuring the Dimension Accuracy of Products Created by 3D Printing Technology with the Designed Measuring System DOI Creative Commons
Martin Pollák, Dominik Sabol, Karol Goryl

et al.

Machines, Journal Year: 2024, Volume and Issue: 12(12), P. 884 - 884

Published: Dec. 5, 2024

The integration of precision measurement techniques using depth scanners with PLC control provides new possibilities for increasing the efficiency and quality measuring 3D printed products. Comprehensive analysis measurements in combination advanced algorithms can provide more accurate dimensional characteristics prediction defects. overall goal such systems is to assess accuracy reliability products manufactured by printing technology, which will fundamentally affect their increased use industrial sectors. article describes design implementation a system servo drive used proposed solution sensor, primarily oriented precise technology. entire program plan implemented through CCW software ver. 12 (Connected Component Workbench) micro motion devices. connection itself realized combinations HMI (Human Machine Interface) panel controller. It controller that subject created software, be direction, position, speed, acceleration servomotor. result scanning connected intended applications object error detection dimension accuracy.

Language: Английский

Citations

2
DEPOSITION QUALITY OPTIMIZATION OF ADDITIVE FRICTION STIR DEPOSITED ALUMINIUM ALLOY USING UNSUPERVISED MACHINE LEARNING DOI Creative Commons
Akshansh Mishra

Advanced Engineering Letters, Journal Year: 2024, Volume and Issue: 3(2), P. 52 - 63

Published: Jan. 1, 2024

Additive friction stir deposition (AFSD) is a promising solid-state additive manufacturing technology, but achieving continuous high quality remains challenging due to complex process-structure connections. This study investigates unsupervised machine learning algorithms for mapping process parameters outcomes without requiring extensive labelled data. On experimental data, including hierarchical clustering, k-means, spectral Gaussian mixtures, autoencoders, and self-organizing maps are used. The find intrinsic patterns groupings in the multi- factor data an unbiased manner. With silhouette score of 0.7618, k-means clustering performed best, showing cohesive clustering. Visualizations like dendrograms trained shed light on links between quality. cluster analysis identifies conditions that result poor highlights ability approaches capture based solely with no prior system knowledge. data-driven strategy has potential significantly improve AFSD optimization control, implications boosting industrial adoption. framework lays groundwork using productivity advanced procedures.

Language: Английский

Citations

1
The Transformation of Manufacturing by Artificial Intelligence DOI
Dipan Kumar Das, Priyambada Mallick, Siddharth Parthasarathy

et al.

Advances in logistics, operations, and management science book series, Journal Year: 2024, Volume and Issue: unknown, P. 42 - 73

Published: March 4, 2024

The combination of artificial intelligence (AI) and industrial momentum heralded a revolution in product design, manufacturing, optimization. This summary provides an overview the transformative changes brought by business through integration AI technology explores various factors influencing process quality innovation. Faced with need for precision efficiency, companies have adopted as revolutionary tool. Through real-world case study, this research how AI-based optimization can modify turbine blades to improve aerodynamic efficiency while reducing associated design testing costs. will also take closer look at field additive showing 3D printing based on algorithms is revolutionizing traditional manufacturing processes.

Language: Английский

Citations

0