To overcome the limitations associated with purely physics-based and data-driven modeling
methods, hybrid, physics-based data-driven models have been developed, with improved …

In the field of predictive maintenance (PdM), machine learning (ML) has gained importance
over the last years. Accompanying this development, an increasing number of papers use …

Surveys on explainable artificial intelligence (XAI) are related to biology, clinical trials,
fintech management, medicine, neurorobotics, and psychology, among others. Prognostics …

In recent years, numerous explainable artificial intelligence (XAI) use cases have been
developed, to solve numerous real problems in industrial applications while maintaining the …

The term Industry 4.0 has become increasingly pervasive in the context of industrial
manufacturing and it has been considered the fourth industrial revolution (Henning [1]). The …

Cerebral hemorrhages require rapid diagnosis and intensive treatment. This study aimed to
detect cerebral hemorrhages and their locations in images using a deep learning model …

A state-of-the-art systematic review on XAI applied to Prognostic and Health Management
(PHM) of industrial asset is presented. This work provides an overview of the general trend …

Predictive maintenance (PdM) is a technique that keeps track of the condition and
performance of equipment during normal operation to reduce the possibility of failures …

Traditional maintenance strategies risk unforeseen failure, sophisticated physics-based
modeling, and manual feature extraction. Early detection and accurate predictions of …

For machine learning models to be reliable and trustworthy, their decisions must be
interpretable. As these models find increasing use in safety-critical applications, it is …