PAUT

Quantitative Analysis

The software provides quantitative data related to the size, shape, and location of discontinuities. This data assesses the severity of found indications and makes informed decisions about the acceptance of the welds 

Automated Data Analysis

The developed algorithms analyze the large amount of data generated during PAUT more quickly and accurately than traditional approaches. This leads to faster and more reliable detection of flaws

Automated Reporting 

NDicateTM  automates the generation of inspection reports by extracting key information from ultrasonic data analysis. This saves time for inspectors and ensures that reports are consistent and comprehensive 

Defect Recognition and Classification 

NDicateTM  platform can be trained to recognize and classify different types of defects in the welds. This includes crack-like and planar types of discontinuities such as lack of fusion, incomplete penetration, or slag inclusions. By automating defect recognition, NDicate improves the consistency of inspections and reduces the risk of human error