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Forecast of deposited volume by directed energy deposition from process parameters

Grant number: 21/10167-6
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2021
Effective date (End): August 31, 2022
Field of knowledge:Engineering - Production Engineering - Product Engineering
Principal researcher:Reginaldo Teixeira Coelho
Grantee:Ana Cecília Reghini
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

Abstract

The different additive manufacturing (AM) processes with metal alloys are increasingly used in different areas of industry, requiring a growing understanding of their operation and the factors that influence their results. Among such processes, the one is known as DED - Directed Energy Deposition, can be used for the manufacture or repair of parts, using, for that, an energy source capable of melting the metallic material being used. In its realization, fundamental parameters are found, such as laser power, head displacement speed, and powder mass flow, which are related to the shape, dimensions, and other characteristics of the deposition. However, this relationship is currently not fully known, so that many realizations of the process must be made based on the "trial-and-error" method, in the hope that the initially determined parameters will lead to obtaining the previously desired characteristics. Thus, it is of great interest to formulate a model that can predict the volume of material deposited based on such parameters, considering that this volume has a direct influence on the presence of internal pores and voids, elements whose presence reduces the quality of the part by affecting the mechanical characteristics of the deposited material. Thus, this project aims to obtain an analytical model, analyzing different printed geometric shapes, with increasing degree of complexity: tracks (lines), layers, and solids under the bias of their volume and their relationship with the parameters used during deposition. (AU)

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