A review of implementation of Artificial Intelligence systems for weld defect classification

Machine Learning and 3D Reconstruction of Materials Surface for Nondestructive Inspection

“…Thus, we considered several studies that allow us to determine the current state of the problem with respect to the implementation of determining defects regarding the most popular methods of NDT. For example, the paper [14], due to a detailed review of existing technological solutions, demonstrates the applicability of individual artificial intelligence methods and their advantages and disadvantages in organizing a defect classification system during the ultrasonic and radiographic studies of test objects. There are approaches to the analysis of radiographic images in which the authors proposed a hybrid approach that combines deep learning (DL) models based on the use of the AlexNet network and autoencoders.…”

Opportunities of AI and ICME in Metals Recycling, Production and Processing

“…This branch of computer implementation is also known as computer-aided process planning (CAPP) and it includes Artificial Intelligence (AI), Integrated Computational Materials Engineering (ICME) as well as industrial twins (IT) and the occasional coupling of these methods. There are plentiful examples of research papers that are focused on the implementation of the foresaid methods in metal forming, welding and their defects (indicative work [2][3][4][5][6][7]) dating as far back as the late 20th century, foreshadowing what was to come. Circular economy is commonly known by its 4Rs (recovery, recycle, reduce, reuse) (Figure 1).…”

“…Proc. 2021, 5, 49 2 of 6 of the foresaid methods in metal forming, welding and their defects (indicative work [2][3][4][5][6][7]) dating as far back as the late 20th century, foreshadowing what was to come. Circular economy is commonly known by its 4Rs (recovery, recycle, reduce, reuse) (Figure 1).…”