Systems Hub Seminar - Improving capability, efficiency and quality for additive manufacturing using collaborating robots and in-situ closed-loop control

ABSTRACT

In this seminar, Dr. Cai will introduce two of his ongoing projects for improving capability, efficiency and quality in additive manufacturing (AM). The first project investigates hybrid AM using collaborating robots. The operational spatial constraints that may lead to robot collision are classified and modeled. The contours within each layer of an object are sorted based on an algorithm considering process priorities, material distribution on the actuators, and the spatial constraints for collision avoidance. The sorted contours are then arranged into a series of deposition groups for subsequent concurrent fabrication. The proposed approach has been incorporated into a virtual manufacturing system for visualization and validation of AM processes with various types of robotic actuators. Case studies will be presented for different robot configurations and part types. A recent development based on augmented reality for constructing a digital twin of the multi-robot system will also be discussed. The second project uses vision-based in-situ inspection and artificial neuro network to enable real-time monitoring and closed-control of AM processes. Depending on specific processes, representative morphological and dynamic features are extracted from process video frames using computer vision algorithms. After proper preprocessing, they are fed into a neuro network to create the mapping between resultant droplet behavior and control parameters (e.g. activation voltage and frequency). A proportional–integral–derivative (PID) control scheme is built based on this network to make sure the material deposition remains stable under system disturbance. Case studies will be presented for two different AM processes: electrohydrodynamic inkjet (e-jet) printing and droplet-based inkjet printing. At the end of the seminar, Dr. Cai will also briefly introduce other related projects on Digital and Smart Manufacturing and Virtual/Augmented Reality for STEM education.