With the rising demand for complex, integrated and autonomous systems in the field of engineering, efficient and versatile Predictive Maintenance (PdM) frameworks have become a requirement for monitoring the health status of these systems since safety, reliability and optimum asset utilisation, are key issues. However, due to the continuously changing dynamics of industrial operations, the data recorded for developing PdM frameworks are often high-dimensional and characterised by undesirable features such as high level of uncertainty, class imbalance and multiclass among others. These...