Technical Challenges in the Road to NDE 4.0

NDE 4.0 ecosystems include a large number of entities. For a system perspective, there are many active interconnected contributors. In order to achieve levels of quality, efficiency, and reliability of inspection systems during their application, it is necessary to know the essential variables of the systems regarding these aspects. That is, in other words, to identify the essential variables, to control them, and to qualify the inspection systems in order to verify their correct performance. To see the importance and complexity of these tasks, three examples regarding important subjects of the NDE 4.0 ecosystem and their impact are presented. First, essential variables and qualification of the NDE inspection system; second, developing ontologies and defining data file formats standards; and third, qualified artificial intelligence applications for automatic analysis of NDE inspection data.

Publication Details

Journal
e-Journal of Nondestructive Testing
Published
2025-05-24
DOI
https://doi.org/10.58286/31310
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Technical Challenges in the Road to NDE 4.0

e-Journal of Nondestructive Testing
Digital Transformation in Industry
article

Technical Challenges in the Road to NDE 4.0

article en

Abstract

NDE 4.0 ecosystems include a large number of entities. For a system perspective, there are many active interconnected contributors. In order to achieve levels of quality, efficiency, and reliability of inspection systems during their application, it is necessary to know the essential variables of the systems regarding these aspects. That is, in other words, to identify the essential variables, to control them, and to qualify the inspection systems in order to verify their correct performance. To see the importance and complexity of these tasks, three examples regarding important subjects of the NDE 4.0 ecosystem and their impact are presented. First, essential variables and qualification of the NDE inspection system; second, developing ontologies and defining data file formats standards; and third, qualified artificial intelligence applications for automatic analysis of NDE inspection data.

e-Journal of Nondestructive TestingVol. 30(6)
Openalex Percentile: Top 84%
Digital Transformation in Industry
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