Remaining useful life (RUL) prediction, known as 'prognostics', has long been recognized as
one of the key technologies in prognostics and health management (PHM) to maintain the …

This article gives an overview of the artificial intelligence (AI) applications for power
electronic systems. The three distinctive life-cycle phases, design, control, and maintenance …

Integration of each aspect of the manufacturing process with the new generation of
information technology such as the Internet of Things, big data, and cloud computing makes …

In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …

Due to the complex changes in physicochemical properties of lithium-ion batteries during
the process from degradation to failure, it is difficult for methods based on physical or data …

Batteries are prevalent energy providers for modern systems. They can also be regarded as
storage units for renewable and sustainable energy. Failures of batteries can bring huge …

In the context of Industry 4.0, smart factories use advanced sensing and data analytic
technologies to understand and monitor the manufacturing processes. To enhance …

The increasing complexity of industrial processes, the continuing search for higher profits,
and increasingly demanding production constraints call for the implementation of a proactive …

As hybrid and electric vehicle technologies continue to advance, car manufacturers have
begun to employ lithium ion batteries as the electrical energy storage device of choice for …

Prognostics focuses on predicting the future performance of a system, specifically the time at
which the system no long performs its desired functionality, its time to failure. As an important …