# Development of a Powder Analysis Procedure Based on Imaging Techniques for Examining Aggregation and Segregation Phenomena

## TL;DR

This paper introduces a new imaging-based method to analyze powder particle aggregation and segregation, improving quality control in manufacturing and pharmaceutical industries.

## Contribution

The novel contribution is a methodology combining fractal and textural image analysis to validate particle size distribution in powder production.

## Key findings

- Fractal analysis quantifies particle structure complexity and self-similarity.
- Textural analysis provides insights into particle arrangement and spatial correlations.
- The method detects irregularities and variations missed by traditional techniques.

## Abstract

In this manuscript, a method that utilizes classical image techniques to assess particle aggregation and segregation, with the primary goal of validating particle size distribution determined by conventional methods, is presented. This approach can represent a supplementary tool in quality control systems for powder production processes in industries such as manufacturing and pharmaceuticals. The methodology involves the acquisition of high-resolution images, followed by their fractal and textural analysis. Fractal analysis plays a crucial role by quantitatively measuring the complexity and self-similarity of particle structures. This approach allows for the numerical evaluation of aggregation and segregation phenomena, providing valuable insights into the underlying mechanisms at play. Textural analysis contributes to the characterization of patterns and spatial correlations observed in particle images. The examination of textural features offers an additional understanding of particle arrangement and organization. Consequently, it aids in validating the accuracy of particle size distribution measurements. To this end, by incorporating fractal and structural analysis, a methodology that enhances the reliability and accuracy of particle size distribution validation is obtained. It enables the identification of irregularities, anomalies, and subtle variations in particle arrangements that might not be detected by traditional measurement techniques alone.