Integration of in situ Imaging and Chord Length Distribution Measurements for Estimation of Particle Size and Shape

TL;DR

This paper introduces two methods that combine in situ imaging and chord length distribution measurements to accurately estimate particle size and shape, addressing challenges in real-time manufacturing quality control.

Contribution

The paper proposes novel algorithms that integrate imaging and CLD data to improve in situ particle size and shape estimation during manufacturing processes.

Findings

Enhanced accuracy in particle size distribution estimation

Improved aspect ratio determination from combined data

Robust algorithms for real-time in-line measurement

Abstract

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.