Viny Saajan Victor

"Informed Machine Learning and Visual Analytics for Virtual Spinning"

Spinning processes are the initial step to produce fibers or yarns from polymers. Optimization of industrial spinning processes is a big challenge for the industry due to its stochastic nature. In principle, spinning processes can be simulated by a combination of differential equations describing the fiber properties and partial differential equations for the surrounding airflow. However, utilizing simulations to optimize the production process requires domain knowledge, and the simulation findings are difficult to interpret. The goal of our research is to develop informed machine learning models that incorporate domain expertise to accelerate the optimization process as well as advanced interactive techniques and visualizations to gain a deeper understanding of industrial spinning processes.

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