  During the last decade, additive manufacturing has become increasingly
popular for rapid prototyping, but has remained relatively marginal beyond the
scope of prototyping when it comes to applications with tight tolerance
specifications, such as in aerospace. Despite a strong desire to supplant many
aerospace structures with printed builds, additive manufacturing has largely
remained limited to prototyping, tooling, fixtures, and non-critical
components. There are numerous fundamental challenges inherent to additive
processing to be addressed before this promise is realized. One ubiquitous
challenge across all AM motifs is to develop processing-property relationships
through precise, in situ monitoring coupled with formal methods and feedback
control. We suggest a significant component of this vision is a set of semantic
layers within 3D printing files relevant to the desired material
specifications. This semantic layer provides the feedback laws of the control
system, which then evaluates the component during processing and intelligently
evolves the build parameters within boundaries defined by semantic
specifications. This evaluation and correction loop requires on-the-fly
coupling of finite element analysis and topology optimization. The required
parameters for this analysis are all extracted from the semantic layer and can
be modified in situ to satisfy the global specifications. Therefore, the
representation of what is printed changes during the printing process to
compensate for eventual imprecision or drift arising during the manufacturing
process.
