Particle Shape Characterisation and Classification using Automated Microscopy and Shape Descriptors in Batch Manufacture of Particulate Solids

It is known that size alone, as often defined as the volume equivalent diameter, is not sufficient for characterizing many particulate products. The shape of crystalline products can be as important as size in many applications. Traditionally particulate shape is often defined by some simple descriptors such as the maximum length and aspect ratio. Although these descriptors are intuitive, they result in loss of some information of the original shape. This paper presents a method to use principal component analysis (PCA) to derive simple latent shape descriptors from microscope images of particulate products made in batch processes, and the use of the descriptors for identification of batch to batch variations. Data from batch runs of both a laboratory crystalliser and an industrial crystallisation reactor are analysed using the approach. Qualitative and quantitative comparison with the use of traditional shape descriptors that have physical meanings and Fourier shape descriptors is also made.