Machine vision based condition monitoring and fault diagnosis of machine tools using information from machined surface texture: A review

Y Liu, L Guo, H Gao, Z You, Y Ye, B Zhang - Mechanical Systems and …, 2022 - Elsevier
Abstract Machine vision based condition monitoring and fault diagnosis of machine tools
(MVCMFD-MTs) is a vital technique of condition-based maintenance (CBM) in both metal …

Remaining useful life prediction using deep learning approaches: A review

Y Wang, Y Zhao, S Addepalli - Procedia manufacturing, 2020 - Elsevier
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 …

Intelligent maintenance systems and predictive manufacturing

J Lee, J Ni, J Singh, B Jiang… - Journal of …, 2020 - asmedigitalcollection.asme.org
With continued global market growth and an increasingly competitive environment,
manufacturing industry is facing challenges and desires to seek continuous improvement …

Time-series classification in smart manufacturing systems: An experimental evaluation of state-of-the-art machine learning algorithms

MA Farahani, MR McCormick, R Harik… - Robotics and Computer …, 2025 - Elsevier
Manufacturing is transformed towards smart manufacturing, entering a new data-driven era
fueled by digital technologies. The resulting Smart Manufacturing Systems (SMS) gather …

[HTML][HTML] Enabling predictive maintenance integrated production scheduling by operation-specific health prognostics with generative deep learning

S Zhai, B Gehring, G Reinhart - Journal of Manufacturing Systems, 2021 - Elsevier
Abstract Predictive Maintenance (PdM) is one of the core innovations in recent years that
sparks interest in both research and industry. While researchers develop more and more …

A systematic literature review of predictive maintenance for defence fixed-wing aircraft sustainment and operations

MJ Scott, WJC Verhagen, MT Bieber, P Marzocca - Sensors, 2022 - mdpi.com
In recent decades, the increased use of sensor technologies, as well as the increase in
digitalisation of aircraft sustainment and operations, have enabled capabilities to detect …

An improved generic hybrid prognostic method for RUL prediction based on PF-LSTM learning

K Xue, J Yang, M Yang, D Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate estimation and prediction of the state-of-health (SOH) and remaining useful life
(RUL) are fundamental to optimal maintenance strategies formulation for prognostics and …

Post-prognostics demand management, production, spare parts and maintenance planning for a single-machine system using Reinforcement Learning

K Wesendrup, B Hellingrath - Computers & Industrial Engineering, 2023 - Elsevier
Abstract Production Planning and Control (PPC) is crucial for any manufacturer and
comprises steps such as demand management, production, or source planning …

A similarity based methodology for machine prognostics by using kernel two sample test

H Cai, X Jia, J Feng, W Li, L Pahren, J Lee - ISA transactions, 2020 - Elsevier
This paper proposes a novel similarity-based algorithm for Remaining Useful Life (RUL)
prediction and a methodology for machine prognostics. In the proposed RUL prediction …

Using temporal convolution network for remaining useful lifetime prediction

J Chen, D Chen, G Liu - Engineering Reports, 2021 - Wiley Online Library
Abstract Because Convolutional Neural Network (CNN) can extract spatial feature, while
Long Short‐Term Memory (LSTM) can learn temporal features, many methods combining …