  The field of additive manufacturing (AM) has advanced considerably over
recent decades through the development of novel methods, materials, and
systems. However, as the field approaches maturity, it is relevant to
investigate the scaling frontiers and fundamental limits of AM in a generalized
sense. Here we propose a simplified universal mathematical model that describes
the essential process dynamics of many AM hardware platforms. We specifically
examine the influence of several key parameters on total manufacturing time,
comparing these with performance results obtained from real-world AM systems.
We find a inverse-cubic dependency on minimal feature size and a linear
dependency on overall structure size. These relationships imply how certain
process features such as parallelization and process dimensionality can help
move toward the fundamental limits. AM methods that are capable of varying the
size of deposited voxels provide one possibility to overcome these limits in
the future development of AM. We also propose a new framework for classifying
manufacturing processes as "top-down" vs "bottom-up" paradigms, which differs
from the conventional usage of such terms, and present considerations for how
"bottom-up" manufacturing approaches may surpass the fundamental limits of
"top-down" systems.
