Utilisation of artificial neural networks to rationalise processing windows in directed energy deposition applications
The application of Directed Energy Deposition (DED) when using new materials or new instruments, requires significant empirical testing to define a suitable or optimum process operation window. Determining the ideal DED parameters is challenging due to the complexity of the deposition process being...
Main Authors: | D.R. Feenstra, A. Molotnikov, N. Birbilis |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-01-01
|
Series: | Materials & Design |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127520308789 |
Similar Items
-
A comparative study on optimization of machining parameters by turning aerospace materials according to Taguchi method
by: Altin Abdullah
Published: (2017-01-01) -
Deposition of Nickel-Based Superalloy Claddings on Low Alloy Structural Steel by Direct Laser Deposition
by: André Alves Ferreira, et al.
Published: (2021-08-01) -
Functionally Graded Additive Manufacturing of Thin-Walled 316L Stainless Steel-Inconel 625 by Direct Laser Metal Deposition Process: Characterization and Evaluation
by: Omid Mehrabi, et al.
Published: (2023-06-01) -
A Review on Direct Laser Deposition of Inconel 625 and Inconel 625-Based Composites—Challenges and Prospects
by: Fahad Zafar, et al.
Published: (2023-04-01) -
Microstructure and Mechanical Properties of Hastelloy X Fabricated Using Directed Energy Deposition
by: Yoon-Sun Lee, et al.
Published: (2023-05-01)