  The tuning of fused filament fabrication parameters is notoriously
challenging. We propose an autonomous data-driven method to select parameters
based on in situ measurements. We use a laser sensor to evaluate the surface
roughness of a printed part. We then correlate the roughness to the mechanical
properties of the part, and show how print quality affects mechanical
performance. Finally, we use Bayesian optimization to search for optimal print
parameters. We demonstrate our method by printing liquid crystal polymer
samples, and successfully find parameters that produce high-performance prints
and maximize the manufacturing process efficiency.
