A Survey on Detection of Various Casting Defects Using Deep Learning Techniques

In the mass production process, producing the product quality is a challenging task, because of the metal casting process, the presence of the product varies irregularly due to the kinds of defects. Identification of faulty products early in an automatic manner is one of the challenges in the industry. This work is a systematic review of various kinds of defects in the casting process, automated defect detection systems with deep learning approaches, and an analysis of their performance. Deep learning approaches are used to produce high-quality products in production lines and enhance the quality inspection process earlier in an automatic manner.