Context:
With the widespread adoption of 3D printing and especially Fused Filament Fabrication techniques, the need for the development of robust monitoring methods to ensure print consistency and product quality has arisen.
Currently most (consumer grade) FFF 3D-printers do not feature movement and or process sensing abilities, operating by purely following instructions without verification of their correct execution. Monitoring of the printer through its motion/extrusion system, printhead/bed/filament temperatures, printhead acceleration and vision algorithms have been proposed as possible solutions with varying success.
Our group is in the midst of developing a methodology that can directly measure the properties of the produced part as it is being printed. Through the use of Electrical Impedance Tomography (EIT) in combination with conductively doped polymers, an image of the produced part and inter-layer adhesion can be derived.
Project description:
One of the key points in the creation of a 3D print is the first layer. The first layers determine the adhesion, warping and general quality of the print to great extent. With our measurement method the first layer also has an additional function, providing contact to the sample for the measurement itself through bed electrodes. Characterizing these first layer effects is therefore imperative to be able to characterize the quality of subsequent layer measurements.
This BSc assignment will focus on characterizing the types of first layer effects. A combination of experimentation and analytical modeling applied, to successfully determine the observability of the various defect types.
Student background:
We are looking for a BSc student in Electrical Engineering (EE), Advanced Technology (AT) or similar. Preferably, students have previous experience with (customized) FFF 3D printers and data processing in Python/MATLAB. Please submit your CV when interested in this assignment.
Contact: h.r.jonkers@utwente.nl