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Towards robust defect detection in casting using contrastive learning
(Springer, 2023)
Defect detection plays a vital role in ensuring product quality and safety within industrial casting processes. In these dynamic environments, the occasional emergence of new defects in the production line poses a significant ...
Real-Time, Model-Agnostic and User-Driven Counterfactual Explanations Using Autoencoders
(MDPI, 2023)
Explainable Artificial Intelligence (XAI) has gained significant attention in recent years due to concerns over the lack of interpretability of Deep Learning models, which hinders their decision-making processes. To address ...
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
(MDPI, 2023)
In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is ...
Towards an Advanced Artificial Intelligence Architecture through Asset Administration Shell and Industrial Data Spaces
(2023)
This article develops an architecture for the implementation of Artificial Intelligence in the manufacturing value chain based on standard technologies and data spaces. The standards considered are IEC 63278 “Asset ...
A Methodology for Advanced Manufacturing Defect Detection through Self-Supervised Learning on X-ray Images
(MDPI, 2024)
In industrial quality control, especially in the field of manufacturing defect detection, deep learning plays an increasingly critical role. However, the efficacy of these advanced models is often hindered by their need ...
Predicting the effect of voids generated during RTM on the low-velocity impact behaviour by machine learning-based surrogate models
(Elsevier, 2023)
The main objective of the present paper is to demonstrate the feasibility of machine-learning-based surrogate models for predicting low-velocity impact behaviour considering void content and location generated during the ...