Integrating AI in NDE: Techniques, Trends, and Further Directions
Eduardo P\'erez, Cemil Emre Ardic, Ozan \c{C}ak{\i}ro\u{g}lu, Kevin, Jacob, Sayako Kodera, Luca Pompa, Mohamad Rachid, Han Wang, Yiming Zhou,, Cyril Zimmer, Florian R\"omer, Ahmad Osman

TL;DR
This paper surveys recent AI techniques applied to nondestructive evaluation (NDE), focusing on magnetic, ultrasound, thermography, and optical methods, highlighting trends, challenges, and future directions in NDE 4.0.
Contribution
It provides a comprehensive overview of AI applications in NDE, categorizing methods by tasks and drawing interdisciplinary connections to guide future research.
Findings
AI enhances NDE capabilities across multiple modalities
Common mathematical problems unify different NDE tasks
The survey identifies key trends and future directions in NDE 4.0
Abstract
The digital transformation is fundamentally changing our industries, affecting planning, execution as well as monitoring of production processes in a wide range of application fields. With product line-ups becoming more and more versatile and diverse, the necessary inspection and monitoring sparks significant novel requirements on the corresponding Nondestructive Evaluation (NDE) systems. The establishment of increasingly powerful approaches to incorporate Artificial Intelligence (AI) may provide just the needed innovation to solve some of these challenges. In this paper we provide a comprehensive survey about the usage of AI methods in NDE in light of the recent innovations towards NDE 4.0. Since we cannot discuss each NDE modality in one paper, we limit our attention to magnetic methods, ultrasound, thermography, as well as optical inspection. In addition to reviewing recent AI…
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Taxonomy
TopicsImpact of AI and Big Data on Business and Society
