  Efficient processing of particulate products across various manufacturing
steps requires that particles possess desired attributes such as size and
shape. Controlling the particle production process to obtain required
attributes will be greatly facilitated using robust algorithms providing the
size and shape information of the particles from in situ measurements. However,
obtaining particle size and shape information in situ during manufacturing has
been a big challenge. This is because the problem of estimating particle size
and shape (aspect ratio) from signals provided by in-line measuring tools is
often ill posed, and therefore it calls for appropriate constraints to be
imposed on the problem. One way to constrain uncertainty in estimation of
particle size and shape from in-line measurements is to combine data from
different measurements such as chord length distribution (CLD) and imaging.
This paper presents two different methods for combining imaging and CLD data
obtained with in-line tools in order to get reliable estimates of particle size
distribution and aspect ratio, where the imaging data is used to constrain the
search space for an aspect ratio from the CLD data.
