Machine Learning: Supervised Algorithms to Determine the Defect in High-Precision Foundry Operation

In this paper, we represent a method for machine learning to predict the defect in foundry operation. Foundry has become driving tool produce part another industry like automobile, marine, and weapon. These processes mainly have two critical problems decrease quality assurance. Now, increase of The process’s failure is associated with micro shrinkage ultimate tensile strength. We process by utilizing classifier maximum strength describe process, evaluate predataset from compare accuracy stability.