The remaining useful life (RUL) estimations become one of the most essential aspects of
predictive maintenance (PdM) in the era of industry 4.0. Predictive maintenance aims to …

Predictive Maintenance (PdM) aims to detect forth-coming failures in machinery to reduce
costs associated with defective products and equipment inactivity. Remaining Useful Life …

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 …

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 …

Predictive maintenance (PdM) plays an important role in industrial manufacturing. One of the
most fundamental ideas underlying many PdM solutions is to estimate Remaining Useful …

The CNN-GRU network is an open-source software package for predicting the remaining
useful lives (RULs) of systems and components using advanced deep learning techniques …

Accurate and timely prediction of remaining useful life (RUL) of a machine enables the
machine to have an appropriate operation and maintenance decision. Data-driven RUL …

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 …

Remaining useful life (RUL) prediction is one of the most important concepts in prognostics
and health management (PHM). In this study, the RUL of milling machine cutting tools is …

Early detection of faulty patterns and timely scheduling of maintenance events can minimize
risk to the underlying processes and increase a system's lifespan, reliability, and availability …