Direct process feedback in extrusion-based 3D bioprinting

Abstract

A major limitation in extrusion-based bioprinting is the lack of direct process control, which limits the accuracy and design complexity of printed constructs. The lack of direct process control results in a number of defects that can influence the functional and mechanical outcomes of the fabricated structures. The machine axes motion cannot be reliably used to predict material placement, and precise fabrication requires additional sensing of the material extrusion. We present an iteration-to-iteration process monitoring system that enables direct process control in the material deposition reference frame. To fabricate parts with low dimensional errors, we integrate a non-contact laser displacement scanner into the printing platform. After fabrication of the initial print using the as-designed reference trajectory, the laser scanner moves across the part to measure the material placement. A custom image processing algorithm compares the laser scanner data to the as-designed reference trajectory to generate an error vector. To compensate for the measured error, the algorithm modifies the axes reference trajectory for the second print iteration. We implement the in situ process monitoring and error compensation technique on an experimental platform to evaluate system performance and demonstrate improvement in spatial material placement.

Process monitoring for material extrusion additive manufacturing: a state-of-the-art review

“…The majority of the identified studies can be assigned to the field of monitoring techniques for fused deposition modeling [35]. The other sub-categories addressed are large-format MEX [58][59][60][61][62][63], bioprinting [64], and direct ink writing [65][66][67][68]. In addition to the processing of conventional filaments, some studies have examined manufacturing processes for continuous fibers [69,70], pastes [71], and pellets [60,62,63,72,73].…”

“…Therefore, a relative movement between the inspection object and sensor should be attained to generate a 3D point cloud from a large number of height profiles. Hence, the laser triangulation system is attached to the extrusion head of the MEX machine and can be moved over the layer surface [62,64,72,73,[195][196][197].…”

Guiding Lights: Tissue Bioprinting Using Photoactivated Materials

“…It is the only biofabrication technique which can create truly anisotropic properties 313 , as the flow of the material can be used to effectively align fibrils, microgels, and by implication, cells. To benefit from this phenomenon, non-planar slicing software 335 and curvilinear printing 336 could be harnessed to exploit the natural anisotropy of tissues or organs, replacing arbitrary layer-by-layer slicing. Extrusion bioprinting explicitly benefits from high-yield stress, viscous materials, thus the functionality of extrusion bioinks can be augmented through the addition of multifunctional nanoparticles and high cell densities in ways not possible for other techniques.…”

Computer vision-aided bioprinting for bone research

“…The shade of the color shows the level of the error, and a darker area means a higher level error; otherwise, a lighter area means a lower level error. 40 f From top to bottom, the plots show the task error for the scaffold error, the first iteration of correction error, and the second iteration of correction error. 40 (Figures adapted with permission from McBethe et al 23 and Armstrong et al 40 ) …”