Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing

By Donghong Ding, Zengxi Pan, Dominic Cuiuri, Huijun Li, S. Duin, Nathan Larkin. 2016

236 citations recorded by the source corpus.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/8e241fb328fd09f0a9dd990fabbf07b62468253b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Huijun Li
2. Zengxi Pan
3. Dominic Cuiuri
4. Donghong Ding
5. Bintao Wu
6. Jialuo Ding
7. Stewart W. Williams
8. John Norrish

In Mechanical Engineering

1. Huijun Li
2. Zengxi Pan
3. Donghong Ding
4. Dominic Cuiuri
5. Jialuo Ding
6. Bintao Wu
7. Stewart W. Williams
8. John Norrish

Citations in the corpus

• Numerical analysis of heat transfer and fluid flow in multilayer deposition of PAW-based wire and arc additive manufacturing (2018, methodology): “Bead modelling work using empirical models or artificial neural networks can establish the relationship between deposition parameters and bead shape [8-10].”
• Arc Welding Processes for Additive Manufacturing: A Review (2018, methodology): “Based on this “basic” MAT path routine, further studies [56, 78] have proposed adaptive MAT paths to further improve geometrical accuracy and produce void-free deposition.”