After having established a strong foundation in kinetic models in a previous webinar, part two delves into the exciting realm of machine learning and its transformative potential for composite manufacturing. While kinetic models have served the industry well, the growing complexity of composite manufacturing demands more sophisticated approaches.

In this session, sensXPERT will explore innovative pathways to supercharge your production efficiency and enhance sustainability beyond the limits of traditional models. See how machine learning empowers composite manufacturers to achieve unprecedented accuracy in predicting key production parameters such as temperature, pressure and cure time. This translates to reduced cycle times and waste while increasing production throughput to maximize efficiency.

SensXPERT will provide concrete examples and case studies demonstrating how to bridge the gap between meticulously-controlled laboratory experiments and the realities of the production floor, overcoming the limitations of kinetic models.

Presented by:

sensXPERT logo
  • Define machine learning, its applications and their impact on composite manufacturing
  • Explore real-world case studies in diverse composites manufacturing applications and how they exploit integration options
  • Correlation analysis: uncovering hidden relationships between process parameters and product outcomes
  • Time series analysis: forecasting production trends
  • Anomaly detection: identifying irregularities
Dr. Nicholas Ecke
Application Engineer
Dr. Nicholas Ecke has been a part of the Netzsch Process Intelligence GmbH team alongside Dr. Alexander Chaloupka since October 2022. He studied process and medical engineering at the Technical University of Munich and was a chief engineer for the chair of composite materials at the Technical University of Kaiserslautern. In 2021, he completed his doctorate in engineering and his dissertation was awarded the Oechsler Prize. The thesis dealt with methods and approaches for developing and designing tribological components made of plastics. As a sensXPERT, Dr. Nicholas Ecke ensures the smooth integration of an intelligent sensor technology, namely the sensXPERT Digital Mold, in customers' production processes worldwide.
Dr. Phil Gralla
Data Scientist
Dr. Phil Gralla joined the data science team at Netzsch Process Intelligence GmbH in 2022. He studied applied mathematics and pure mathematics at the University of Bremen and Clemson (US). In 2023, Dr. Gralla completed his doctorate in mathematics. During his time as a research fellow at the University of Bremen, Dr. Gralla worked on various industry projects and conducted research on process control and optimization. Since 2019, he has been developing algorithms; initially for image processing and now for the sensXPERT digital mold and pipe solution.
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