Magnetooptical Nondestructive Inspection (MONDI) plays a vital role in many industries, especially in detecting metal defects, including ferromagnetic materials. Among the challenges encountered by the MONDI are the orientation of a magnetizer and irregular shapes of defects, which make it difficult to determine the seriousness of these defects.
A significant challenge in nondestructive evaluation has been understanding the difficulty in measuring rough defects. The traditional approaches, which include running numerous finite element models, were time-consuming and constraining.
A pioneering study has unveiled a cutting-edge automatic and dependable nondestructive evaluation (NDE) technique, revolutionizing the quantification of subsurface defects in metallic components. Through the innovative integration of a non-contact laser ultrasonic technique with a sophisticated machine learning (ML) algorithm, researchers have achieved remarkable strides in simultaneously measuring the width and depth of subsurface defects.
In the current economic situation of many companies, the need to reduce production time is a critical element. However, the quality of the final product will decrease as we speed up the production process. Humans usually use regular methods of quality control, and this causes a short interruption in production time. This can cause a pause in the production process and increase its time. However, many methods have been introduced to help companies and manufacturers do efficient quality management and decrease the time of quality control.
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