Abstract
Laser metal deposition (LMD) is an additive manufacturing (AM) technologies in that belongs to the class of direct energy deposition which is suitable for manufacturing of alloys and composites materials. LMD is an efficient AM technique which is capable of producing end-use products starting from depositing the powder/wire material layer-by-layer. During LMD process, a laser beam is used as a heat source to generate a melt-pool on the substrate and melts the powder that is deposited through a co-axial nozzle and supported with a shielding gas that helps to prevent oxidation. LMD is capable of producing complex shaped and functionally graded parts which are useful in many industrial applications. This AM technology can also be used in repairing worn out parts that cannot be repaired by other manufacturing technology. In this paper, a review of laser metal deposition of titanium alloy is presented. This provides an overview of LMD of titanium alloys grade 5 (Ti6Al4V) and focuses on the effects of processing parameters on the overall evolving properties.
| Original language | English |
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| Title of host publication | 2019 International Conference on Engineering, Science, and Industrial Applications, ICESI 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728121741 |
| DOIs | |
| Publication status | Published - Aug 2019 |
| Event | 2019 International Conference on Engineering, Science, and Industrial Applications, ICESI 2019 - Tokyo, Japan Duration: 22 Aug 2019 → 24 Aug 2019 |
Publication series
| Name | 2019 International Conference on Engineering, Science, and Industrial Applications, ICESI 2019 |
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Conference
| Conference | 2019 International Conference on Engineering, Science, and Industrial Applications, ICESI 2019 |
|---|---|
| Country/Territory | Japan |
| City | Tokyo |
| Period | 22/08/19 → 24/08/19 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Information Systems
- Decision Sciences (miscellaneous)
- Energy Engineering and Power Technology
- Industrial and Manufacturing Engineering
- Health Informatics
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