Fatigue Testing of 3D-Printed Compliant Joints

An Experimental Study

Master Thesis (2018)
Author(s)

L.A. Safai (TU Delft - Mechanical Engineering)

Contributor(s)

Juan Cuellar Lopez – Mentor

Gerwin Smit – Mentor

A. A. A. Zadpoor – Mentor

Faculty
Mechanical Engineering
Copyright
© 2018 Lauren Safai
More Info
expand_more
Publication Year
2018
Language
English
Copyright
© 2018 Lauren Safai
Graduation Date
19-10-2018
Awarding Institution
Delft University of Technology
Programme
['Biomedical Engineering']
Faculty
Mechanical Engineering
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

As interest in additive manufacturing, or 3D printing, increases, technological improvements are making printing methods quicker and more cost efficient. Inventors and innovators are able to print low-cost and complex geometries rapidly as a result of the manufacturing time being reduced from weeks to hours. With the large amount of polymeric materials available, the design and manufacturing of products are continuously changing as more industries adopt the use of additive manufacturing. One up-and-coming application of additive manufacturing is monolithic compliant joints, which use the elastic deformation of the flexural arms as a mechanism for to complete the desired function. With additive manufacturing becoming more prevalent, it is essential that parts are able to withstand the mechanical and environmental stresses that occur during use. Understanding a material’s response to cyclic loading and unloading is important, as the majority of parts will experience fatigue behavior. Fatigue is a progressive and permanent structural change that could result in a crack or complete rupture, making a part unable to perform its desired task. Since additive manufacturing of compliant joints is a new field, it is critical to understand fatigue behavior in 3D-printed parts so that fatigue behavior can be predicted and prevented.

Files

Thesis_v3.pdf
(pdf | 12 Mb)
License info not available