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  5. A Study of the Effect of Machine Parameters on Defects Produced in EOS Additive Manufacturing Builds
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A Study of the Effect of Machine Parameters on Defects Produced in EOS Additive Manufacturing Builds

Date Issued
May 1, 2023
Author(s)
Malone, Tina White  
Advisor(s)
Andrew Yu
Additional Advisor(s)
James L. Simonton
Mingzhou Jin
Feng Yuan Zhang
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/29402
Abstract

5Additive Manufacturing (AM) is defined in the American Society for Testing and Materials (ASTM) standard F2792 as “a process of joining materials to make objects from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies. It provides an advanced method for building complex geometries and parts for high performance with a significant cost savings. 55It’s advantages include the reduced need for tools and molds commonly used in manufacturing, a large reduction in wasted material, much shorter manufacturing cycles for the building of hardware, and its uniquely inherent ability to produce much more complex shapes. Polymers, metals, ceramics, and composites can all be built using some method of AM.


The use of standardized vendor parameters for additive manufacturing builds has resulted in numerous defects in the as-built parts. This study looked at HR-1 products built on an EOS M290 DMLS 3D printer. The builds were monitored using an EOS in-situ monitoring system to identify when “problems” began to occur and it compares the “problems” with the results of post build computed tomography inspections. It also looked at the defects produced and evaluated them versus the additive manufacturing process parameters.

Subjects

Additive Manufacturin...

In Situ Monitoring

Design of Experiments...

Alloy Development

Non-Destructive Evalu...

HR-1 Alloy

Disciplines
Industrial Engineering
Metallurgy
Degree
Doctor of Philosophy
Major
Industrial Engineering
File(s)
Thumbnail Image
Name

Dissertation_4_25_23.docx

Size

21.03 MB

Format

Microsoft Word XML

Checksum (MD5)

6c1dddb16fab134e359c13c2dce6cbcd

Thumbnail Image
Name

auto_convert.pdf

Size

4.14 MB

Format

Adobe PDF

Checksum (MD5)

cc9de49f5fb8886a6df98228c22974b8


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