  High performance sheet metals with a multi-phase microstructure suffer from
deformation induced damage formation during forming in the constituent phases
but importantly also where these intersect. To capture damage in terms of the
physical processes in three dimensions (3D) and its stochastic nature during
deformation, two challenges remain to be tackled: First, bridging high
resolution analysis towards large scales to consider statistical data and,
second, characterising in 3D with a resolution appropriate for sub-micron sized
voids at a large scale. Here, we present how this can be achieved using
panoramic scanning electron microscopy (SEM), metallographic serial sectioning,
and deep-learning assisted automatic image analysis. This brings together the
3D evolution of active damage mechanisms with volumetric and environmental
information for thousands of individual damage sites. We also assess potential
surface preparation artefacts in 2D analyses. Overall, we find that for the
material considered here, a dual phase (DP800) steel, martensite cracking is
the dominant but not sole origin of deformation induced damage and that for a
quantitative comparison of damage density, metallographic preparation can
induce additional surface damage density far exceeding what is commonly induced
between uniaxial straining steps.
