By Identifying the Ideal Manufacturing Conditions, Machine Learning Reduces the Need for Expensive and Time-Consuming ExperimentationTSUKUBA, Japan, - (NewMediaWire) - December 3, 2024 - Polymers ...

Machine learning algorithms need data, so the researchers designed a polymerization process that would quickly and efficiently generate experimental data to feed into the mathematical model.

Machine learning is already being applied to screen for cracks in metal tanks and pipes in NPPs. Enhanced precision, reduced cost and optimized human oversight from machine learning has the potential ...