Control of on-demand nanoliter drop volume and jetting velocity in piezoelectric inkjet printing |
| |
| Affiliation: | 1. Orthopedic Surgery Department at the University of Bisha, Bisha, Saudi Arabia;2. Orthopedic Surgery Department at the King Saud University, Riyadh, Saudi Arabia;3. Radiology Department at the Prince Sultan Military Medical City, Riyadh, Saudi Arabia;4. Orthopedic Surgery Department at the Prince Sultan Military Medical City, Riyadh, Saudi Arabia;1. School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA;2. School of Materials Engineering, Purdue University, West Lafayette, IN, USA;3. Purdue Institute for Cancer Research, Purdue University, West Lafayette, IN, USA;4. Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA;5. Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, USA |
| |
| Abstract: | Consistent dosages placed with high accuracy onto the substrate are critical for drop-on-demand (DoD) inkjet printing to be adopted in additive manufacturing and device characterization. Practically, the consistency of drop volume and drop jetting velocity is subject to process uncertainties, such as fluctuations of applied pressure and variations in printheads, for which open-loop approaches are unable to compensate. In this work, a stochastic process model of the relation between two control parameters of a firing waveform and two output features, drop volume and drop jetting velocity, is developed from standard printhead calibration data. An image-based control strategy based on a projection-based one-step-ahead Kalman estimator for model parameters estimation is proposed to regulate the drop volume and the drop jetting velocity. The effectiveness of the proposed control strategy is experimentally validated for three inks with broad properties. By including input boundary layers, an order of magnitude improvement in reducing drop volume and jetting velocity variations is also experimentally demonstrated. |
| |
| Keywords: | Inkjet printing Additive manufacturing Stochastic systems Kalman filter Process control |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
