Please join us in welcoming Nosakhare Edoimioya.
Additive manufacturing (AM) has been gaining attention due to its versatility in fabricating complex parts when compared to traditional manufacturing processes. As an example of this versatility, we saw AM used by hobbyists, companies, and universities during the COVID-19 pandemic to fill production gaps for personal protective equipment while traditional manufacturing ramped up. However, AM’s adoption in industry has been limited by its production speed and part accuracy, which are not yet comparable to traditional manufacturing. Using a model-based vibration control technique known as the filtered B-splines (FBS) method, researchers at the Smart and Sustainable Automation (S2A) Lab at the University of Michigan have demonstrated a 2x productivity boost while retaining the part quality in traditional (serial-axis) AM machines. In this talk, I will discuss my research which leverages the FBS method to control advanced (parallel-axis) manipulators for extrusion-based AM; these manipulators are optimized for high speeds but have nonlinear dynamics, which leads to challenges when controlling them. I will show results of how my work on implementing FBS on parallel-axis manipulators (specifically the H-frame and delta robot manipulators) has led to improvements in the shape accuracy of the parts they fabricate. Furthermore, I will discuss plans to extend the work to robotic arm manipulators that are being used for AM.
Nosa Edoimioya is a Ph.D. candidate in the department of Mechanical Engineering at the University of Michigan. Prior to that, he received the BS in Mechanical Engineering from Stanford University in 2017 and the MS in Mechanical Engineering from the University of Michigan in 2019. He was awarded the Rackham Merit Fellowship in 2017 and the NSF Graduate Research Fellowship in 2018 to support his doctoral research. He has taught courses in mechatronics and manufacturing as the lead lecturer at Ashesi University in Ghana and assisted in teaching courses in dynamics and control at the University of Michigan.
