Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …

The amount of data extracted from production processes has increased exponentially due to
the proliferation of sensing technologies. When processed and analyzed, data can bring out …

Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …

Abstract Approaches such as Cyber-Physical Systems (CPS), Internet of Things (IoT),
Internet of Services (IoS), and Data Analytics have built a new paradigm called Industry 4.0 …

With the advent of the fourth industrial revolution, the application of artificial intelligence in
the manufacturing domain is becoming prevalent. Maintenance is one of the important …

Failure prediction is the task of forecasting whether a material system of interest will fail at a
specific point of time in the future. This task attains significance for strategies of industrial …

Predictive maintenance is an essential aspect of microgrid operations as it enables
identifying potential equipment failures in advance, reducing downtime, and increasing the …

Driven by the ongoing migration towards Industry 4.0, the increasing adoption of artificial
intelligence (AI) has empowered smart manufacturing and digital transformation. AI …

Predictive maintenance is a field of study whose main objective is to optimize the timing and
type of maintenance to perform on various industrial systems. This aim involves maximizing …

The concept of maintenance has advanced significantly over the last decades from a
reactive service activity towards a pro-active one with more C-level attention. Among them …