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From Data to Decisions: Machine Learning in Material Development & QA/QC
Posted 11th of february 2025
SPEAKER
Charles Jouanique
Charles Jouanique has been active in the industry for over 13 years. In addition to developing new digital business models, he is also an entrepreneur and a multiple business angel for startups. He is the Co-Founder in charge of Sales & Marketing at LabV, a software company within the NETZSCH Group.
ABSTRACT
How can data from R&D projects and test results be used to make informed decisions in product development? In this webinar, we will explore how machine learning models can help identify relationships between material composition and test results.
Using practical examples, we will demonstrate:
- – How models predict material composition changes’ effects on viscosity and chemical resistance.
- – How target values for specific test results can be used to generate recommendations for formulation adjustments.
The goal is to provide a better understanding of the potential of data-driven analyses and to show how these approaches can support complex decision-making in research, development, and quality assurance.