  The success of the various secondary operations involved in the production of
particulate products depends on the production of particles with a desired size
and shape from a previous primary operation such as crystallisation. This is
because these properties of size and shape affect the behaviour of the
particles in the secondary processes. The size and the shape of the particles
are very sensitive to the conditions of the crystallisation processes, and so
control of these processes is essential. This control requires the development
of software tools that can effectively and efficiently process the sensor data
captured in situ. However, these tools have various strengths and limitations
depending on the process conditions and the nature of the particles.
  In this work, we employ wet milling of crystalline particles as a case study
of a process which produces effects typical to crystallisation processes. We
study some of the strengths and limitations of our previously introduced tools
for estimating the particle size distribution (PSD) and the aspect ratio from
chord length distribution (CLD) and imaging data. We find situations where the
CLD tool works better than the imaging tool and vice versa. However, in general
both tools complement each other, and can therefore be employed in a suitable
multi-objective optimisation approach to estimate PSD and aspect ratio.
