  Metal additive manufacturing (AM) processes often fabricate a near-net shape
that includes the as-designed part as well as the sacrificial support
structures that need to be machined away by subtractive manufacturing (SM), for
instance multi-axis machining. Thus, although AM is capable of generating
highly complex parts, the limitations of SM due to possible collision between
the milling tool and the workpiece can render an optimized part
non-manufacturable. We present a systematic approach to topology optimization
(TO) of parts for AM followed by SM to ensure removability of support
structures, while optimizing the part's performance. A central idea is to
express the producibility of the part from the near-net shape in terms of
accessibility of every support structure point using a given set of cutting
tool assemblies and fixturing orientations. Our approach does not impose any
artificial constraints on geometric complexity of the part, support structures,
machining tools, and fixturing devices. We extend the notion of inaccessibility
measure field (IMF) to support structures to identify the inaccessible points
and capture their contributions to non-manufacturability by a continuous
spatial field. IMF is then augmented to the sensitivity field to guide the TO
towards a manufacturable design. The approach enables efficient and effective
design space exploration by finding nontrivial complex designs whose near-net
shape can be 3D printed and post-processed for support removal by machining
with a custom set of tools and fixtures. We demonstrate the efficacy of our
approach on nontrivial examples in 2D and 3D.
