Predictions of in-situ melt pool geometric signatures via machine learning techniques for laser metal deposition
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Predictions of in-situ melt pool geometric signatures via machine learning techniques for laser metal deposition
Authors
Keywords
-
Journal
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
Volume -, Issue -, Pages 1-17
Publisher
Informa UK Limited
Online
2022-03-14
DOI
10.1080/0951192x.2022.2048422
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Coaxial Monitoring of AISI 316L Thin Walls Fabricated by Direct Metal Laser Deposition
- (2021) Vito Errico et al. Materials
- Mechanistic data-driven prediction of as-built mechanical properties in metal additive manufacturing
- (2021) Xiaoyu Xie et al. npj Computational Materials
- Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing
- (2021) D.R. Gunasegaram et al. Additive Manufacturing
- Machine Learning in Additive Manufacturing: A Review
- (2020) Lingbin Meng et al. JOM
- K-Nearest Neighbors regression for the discrimination of gamma rays and neutrons in organic scintillators
- (2020) Matthew Durbin et al. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT
- Utilisation of artificial neural networks to rationalise processing windows in directed energy deposition applications
- (2020) D.R. Feenstra et al. MATERIALS & DESIGN
- Machine learning in additive manufacturing: State-of-the-art and perspectives
- (2020) C. Wang et al. Additive Manufacturing
- Investigation on coaxial visual characteristics of molten pool in laser-based directed energy deposition of AISI 316L steel
- (2020) Zi-jue Tang et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- In-situ high-speed X-ray imaging of piezo-driven directed energy deposition additive manufacturing
- (2019) Sarah J. Wolff et al. Scientific Reports
- The Effect of Specific Energy Density on Microstructure and Corrosion Resistance of CoCrMo Alloy Fabricated by Laser Metal Deposition
- (2019) Jinbao Li et al. Materials
- Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives
- (2019) Xinbo Qi et al. Engineering
- Parametric studies and manufacturability experiments on smooth self-supporting topologies
- (2019) Yun-Fei Fu et al. Virtual and Physical Prototyping
- Design and experimental validation of self-supporting topologies for additive manufacturing
- (2019) Yun-Fei Fu et al. Virtual and Physical Prototyping
- A numerical investigation on the physical mechanisms of single track defects in selective laser melting
- (2018) C. Tang et al. INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
- Data-driven cost estimation for additive manufacturing in cybermanufacturing
- (2018) Siu L. Chan et al. JOURNAL OF MANUFACTURING SYSTEMS
- Additive manufacturing of metallic components – Process, structure and properties
- (2018) T. DebRoy et al. PROGRESS IN MATERIALS SCIENCE
- Laser Direct Metal Deposition of 2024 Al Alloy: Trace Geometry Prediction via Machine Learning
- (2018) Fabrizia Caiazzo et al. Materials
- Effect of laser energy density on defects behavior of direct laser depositing 24CrNiMo alloy steel
- (2018) Lin Cao et al. OPTICS AND LASER TECHNOLOGY
- Real-Time Composition Monitoring Using Support Vector Regression of Laser-Induced Plasma for Laser Additive Manufacturing
- (2017) Lijun Song et al. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
- An empirical-statistical model for coaxial laser cladding of NiCrAlY powder on Inconel 738 superalloy
- (2016) M. Ansari et al. OPTICS AND LASER TECHNOLOGY
- Printability of alloys for additive manufacturing
- (2016) T. Mukherjee et al. Scientific Reports
- A camera based feedback control strategy for the laser cladding process
- (2012) J.T. Hofman et al. JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
- Layer-to-Layer Height Control for Laser Metal Deposition Process
- (2011) Lie Tang et al. JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now