About This Webinar
Traditional quality control methods in industries such as food, pharmaceuticals, chemicals, and recycling often still rely on laboratory-based analysis of a limited number of random samples. This approach fails to provide a comprehensive insight about the entire production flow. Quantitative chemical imaging (QCI) offers an impactful solution by enabling real-time analysis of the chemical composition of a material flow directly within the production line.
This talk demonstrates the development of an application model using the QCI classification algorithm to quantitatively analyze multiple chemical components, measuring the concentration and distribution of chemical compounds in a product. This paves the way for more efficient and precise quality control in industrial production.
*** This presentation premiered during the
2025 Vision Spectra Conference. For more information on Photonics Media conferences and summits, visit
events.photonics.com
About the presenter
Matthias Kerschhaggl, Ph.D., is CTIO of EVK, an Austrian based expert company for industrial imaging. He is engaged in data science and analytics, predominantly dealing with data streams stemming from sensor-based sorting and control applications used in industries such as food, chemical, mining and pharmaceuticals. He holds a doctorate in experimental physics and has more than 15 years of experience in the fields of statistical learning and data mining of datasets from various areas (astroparticle physics, integral field spectrographs, hyperspectral and inductive imaging).