ReviewMaterials (Basel, Switzerland)2022
On Smart Geometric Non-Destructive Evaluation: Inspection Methods, Overview, and Challenges.
Review in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Smart Diagnostics: Hierarchical Deep Learning of Acoustic Emission Signals for Early Crack Detection in Zirconia Dental Structures.Sensors (Basel, Switzerland) · 2026Article
- A Machine Learning Implementation to Predictive Maintenance and Monitoring of Industrial Compressors.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Inspection methods, also known as non-destructive evaluation (NDE), is a process for inspecting materials, products, and facilities to identify flaws, imperfections, and malfunctions without destruction or changing the integrity of materials, structures, and mechanisms. However, detecting those defects requires test conducting and results inferring, which is highly demanding in terms of analysis, performance, and time. New technologies are therefore needed to increase the efficiency, probability of detection, and interpretability of NDE methods to establish smart inspection. In this context, Artificial intelligence (AI), as a fundamental component of the Industry 4.0, is a well-suited tool to address downsides associated with the current NDE methods for analysis and interpretation of inspection results, where methods integrating AI into their inspection process become automated and are known as smart inspection methods. This article sheds a light on the conventional methods and the smart techniques used in defects detection. Subsequently, a comparison between the two notions is presented. Furthermore, it investigates opportunities for the integration of non-destructive evaluation (NDE) methods and Industry 4.0 technologies. In addition, the challenges hindering the progress of the domain are mentioned as the potential solutions. To this end, along with Industry 4.0 technologies, a virtual inspection system has been proposed to deploy smart inspection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.