Digital twins: A survey on enabling technologies, challenges, trends and future prospects
Digital Twin (DT) is an emerging technology surrounded by many promises, and potentials
to reshape the future of industries and society overall. A DT is a system-of-systems which …
to reshape the future of industries and society overall. A DT is a system-of-systems which …
A review on deep learning in machining and tool monitoring: Methods, opportunities, and challenges
V Nasir, F Sassani - The International Journal of Advanced Manufacturing …, 2021 - Springer
Data-driven methods provided smart manufacturing with unprecedented opportunities to
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …
Transformer network for remaining useful life prediction of lithium-ion batteries
D Chen, W Hong, X Zhou - Ieee Access, 2022 - ieeexplore.ieee.org
Accurately predicting the Remaining Useful Life (RUL) of a Li-ion battery plays an important
role in managing the health and estimating the state of a battery. With the rapid development …
role in managing the health and estimating the state of a battery. With the rapid development …
A review on the application of deep learning in system health management
Given the advancements in modern technological capabilities, having an integrated health
management and diagnostic strategy becomes an important part of a system's operational …
management and diagnostic strategy becomes an important part of a system's operational …
[HTML][HTML] Augmenting organizational decision-making with deep learning algorithms: Principles, promises, and challenges
The current expansion of theory and research on artificial intelligence in management and
organization studies has revitalized the theory and research on decision-making in …
organization studies has revitalized the theory and research on decision-making in …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Remaining useful life estimation using a bidirectional recurrent neural network based autoencoder scheme
Abstract System remaining useful life (RUL) estimation is one of the major prognostic
activities in industrial applications. In this paper, we propose a sensor-based data-driven …
activities in industrial applications. In this paper, we propose a sensor-based data-driven …
An improved similarity-based prognostic algorithm for RUL estimation using an RNN autoencoder scheme
Remaining useful life (RUL) estimation of a degrading system is the major prognostic activity
in many industry applications. This paper presents an improved version of the similarity …
in many industry applications. This paper presents an improved version of the similarity …
A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines
The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …
applications. It is of no exception in the area of prognostics and health management (PHM) …
A review of machine learning methods applied to structural dynamics and vibroacoustic
Abstract The use of Machine Learning (ML) has rapidly spread across several fields of
applied sciences, having encountered many applications in Structural Dynamics and …
applied sciences, having encountered many applications in Structural Dynamics and …