734-936-0378

Applications:
ASME Adavanced Material Manufacturing, Aerospace Engineering, CIRP Community, Climate Research, Environmental Sciences, Industrial Engineering, Materials Science, Medical Imaging, Transportation Research
Methodologies:
Artificial Intelligence, Classification, Data Mining, Deep Learning, Geographic Information Systems, Machine Learning, Predictive Modeling, Statistical Modeling, Tensor Analysis

Mihaela (Miki) Banu

Research Associate Professor

Mechanical Engineering

In the area of multi-scale modeling of manufacturing processes: (a) Models for understanding the mechanisms of forming and joining of lightweight materials. This new understanding enables the development of advanced processes which remove limitations of current state-of-the-art capabilities that exhibit limited formability of high strength lightweight alloys, and limited reproducibility of joining quality; (b) Innovative multi-scale finite element models for ultrasonic welding of battery tabs (resulting in models adopted by GM for designing and manufacturing batteries for the Chevy Volt), and multi-scale models for ultrasonic welding of short carbon fiber composites (resulting in models adopted by GM for designing and manufacturing assemblies made of carbon fiber composites with metallic parts); (c) Data-driven algorithms of prediction geometrical and microstructural integrity of the incremental formed parts. Machine learning is used for developing fast and robust methods to be integrated into the designing process and replace finite element simulations.