A Study on the Material Properties and Process Conditions Reasoning using Regression and Classification of Machine Learning

In this paper, we explain the property prediction and manufacturing process condition inference methodology of ceramic materials with the introduction of AI models and perform PoC of the proposed method. We selected the optimal model by applying data with various input characteristics related to material properties to regression/classification machine learning models with proven performance. The accuracy of the final selected model was more than 90%, showing the possibility of drastically reducing the material development period.