Predictive maintenance in the Industry 4.0: A systematic literature review
Industry 4.0 is collaborating directly for the technological revolution. Both machines and
managers are daily confronted with decision making involving a massive input of data and …
managers are daily confronted with decision making involving a massive input of data and …
Machine Learning for industrial applications: A comprehensive literature review
Abstract Machine Learning (ML) is a branch of artificial intelligence that studies algorithms
able to learn autonomously, directly from the input data. Over the last decade, ML …
able to learn autonomously, directly from the input data. Over the last decade, ML …
Machine learning and data mining in manufacturing
A Dogan, D Birant - Expert Systems with Applications, 2021 - Elsevier
Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …
[HTML][HTML] Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers
Since the introduction of the concept of “digital twins”(DTs) in 2002, the number of practical
applications in different industrial sectors has grown rapidly. Despite the hype surrounding …
applications in different industrial sectors has grown rapidly. Despite the hype surrounding …
Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
Remaining useful life (RUL) prediction has been a hotspot in the engineering field, which is
useful to avoid unexpected breakdowns and reduce maintenance costs of the system. Due …
useful to avoid unexpected breakdowns and reduce maintenance costs of the system. Due …
[PDF][PDF] 基于机器学习的设备剩余寿命预测方法综述
裴洪， 胡昌华， 司小胜， 张建勋， 庞哲楠， 张鹏 - 机械工程学报, 2019 - qikan.cmes.org
随着科学技术的发展和生产工艺的进步, 当代设备日益朝着大型化, 复杂化,
自动化以及智能化方向发展. 为保障设备安全性与可靠性, 剩余寿命(Remaining useful life …
自动化以及智能化方向发展. 为保障设备安全性与可靠性, 剩余寿命(Remaining useful life …
A digital twin to train deep reinforcement learning agent for smart manufacturing plants: Environment, interfaces and intelligence
Filling the gaps between virtual and physical systems will open new doors in Smart
Manufacturing. This work proposes a data-driven approach to utilize digital transformation …
Manufacturing. This work proposes a data-driven approach to utilize digital transformation …
Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics
The use of a modern technological system requires a good engineering approach,
optimized operations, and proper maintenance in order to keep the system in an optimal …
optimized operations, and proper maintenance in order to keep the system in an optimal …
Deep transfer learning based on sparse autoencoder for remaining useful life prediction of tool in manufacturing
Deep learning with ability to feature learning and nonlinear function approximation has
shown its effectiveness for machine fault prediction. While, how to transfer a deep network …
shown its effectiveness for machine fault prediction. While, how to transfer a deep network …