Machine learning-based bead modeling of wire arc additive manufacturing (WAAM) using an industrial robot
Author:
Publisher
Elsevier BV
Subject
General Medicine
Reference21 articles.
1. L. Yuan, D. Ding, Z. Pan, Z. Yu, B. Wu, and S. Van Duin, “Application of Multidirectional Robotic Wire Arc Additive Manufacturing Process for the Fabrication of Complex Metallic Parts,” vol. 16, no. 1, pp. 454–464, 2020
2. A. Paolini, S. Kollmannsberger, and E. Rank, “Additive manufacturing in construction: A review on processes, applications, and digital planning methods,” Addit. Manuf., vol. 30, no. October, p. 100894, 2019
3. The use of teaching-learning based optimization technique for optimizing weld bead geometry as well as power consumption in additive manufacturing;Venkatarao;J. Clean. Prod.,2021
4. Multi-criteria environmental and economic impact assessment of wire arc additive manufacturing;Priarone;CIRP Ann.,2020
5. Selection of process parameters for near-net shape deposition in wire arc additive manufacturing by genetic algorithm;Kumar;J. Mater. Eng. Perform.,2020
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1. Multi-objective Optimization of Short-Circuit Gas Metal Arc Welding for Overhang Structures by Grey Relational Analysis Integrated Taguchi Method;Journal of Materials Engineering and Performance;2024-09-12
2. A review of wire and arc additive manufacturing using different property characterization, challenges and future trends;International Journal of System Assurance Engineering and Management;2024-08-29
3. Study of Multilayer Welded Structure Made of AISI 316LSi Using WAAM;Tehnicki vjesnik - Technical Gazette;2024-04-15
4. Reinforcement learning as data-driven optimization technique for GMAW process;Welding in the World;2023-12-21
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