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 …

Reliability of prognostics and health management systems relies upon accurate
understanding of critical components' degradation process to predict the remaining useful …

An increase in unplanned downtime of machines disrupts and degrades the industrial
business, which results in substantial credibility damage and monetary loss. The cutting tool …

Predicting remaining useful life (RUL) is crucial for system maintenance. Condition
monitoring makes not only degradation data available for RUL estimation but also …

Prognostics and health management (PHM) has attracted increasing attention in modern
manufacturing systems to achieve accurate predictive maintenance that reduces production …

There has been considerable advances, over the last few decades, in sensing
instrumentation, hardware, signal processing algorithms, and internet technology …

Prognosis and health management (PHM) are mandatory tasks for real-time monitoring of
damage propagation and aging of operating systems during working conditions. More …

Data-driven techniques, especially on artificial intelligence (AI) such as deep learning (DL)
techniques, have attracted more and more attention in the manufacturing sector because of …

The search for effective asset utilization has been constant, especially in industries with
evolving mechanization. In this context, maintenance management gains visibility because it …

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 …