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Control of directed energy deposition process for manufacturing complex geometry components by Additive Manufacturing (AM)

Grant number: 19/00343-1
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): April 01, 2019
Effective date (End): February 28, 2022
Field of knowledge:Engineering - Mechanical Engineering
Principal Investigator:Reginaldo Teixeira Coelho
Grantee:Kandice Suane Barros Ribeiro
Home Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:16/11309-0 - The study, development and application of a hybrid process: Additive Manufacturing (AM) plus High Speed Machining/Grinding (HSM/G), AP.TEM


Additive Manufacturing (AM) has been an area of great interest for both universities and industries due to its new product properties and sustainable production capabilities. One of AM main process for manufacturing metal parts is the Directed Energy Deposition (DED), which is based on a simultaneous deposition of metal powder and laser beam layer by layer through a pre-defined deposition toolpath generated in CAM software. This process is commonly applied in repair and rebuild of damaged and worn components, and to manufacture new parts in hard-to-machine materials. However, during fabrication the complex thermal activity of newly deposited layers and its influence in previous deposited material affects the quality of metal deposition, making the reprodudibility of parts and maintenance of microstructure and mechanical properties a challenge for production. With this regard, the aim of this research is to develop a method for controlling DED processes parameters e.g. deposited layer thickness, feedstock and energy delivered to accomplish effective material joining and reprodudibility of additive manufactured parts. A compound of different optical methods of monitoring laser processes has been applied in the literature but acoustic and optical methods are rarely combined. For quality and process reliability purposes, such solution might produce interesting data towards closed loop manufacturing control and further knowledge in AM via DED. (AU)