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.
Agenda:
- 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
