[HTML][HTML] Edge-cloud cooperation-driven smart and sustainable production for energy-intensive manufacturing industries

S Ma, Y Huang, Y Liu, X Kong, L Yin, G Chen - Applied Energy, 2023 - Elsevier
Energy-intensive manufacturing industries are characterised by high pollution and heavy
energy consumption, severely challenging the ecological environment. Fortunately …

An automatic method for constructing machining process knowledge base from knowledge graph

L Guo, F Yan, T Li, T Yang, Y Lu - Robotics and Computer-Integrated …, 2022 - Elsevier
The process knowledge base is the key module in intelligent process design, it determines
the intelligence degree of the design system and affects the quality of product design …

[HTML][HTML] Degradation curves integration in physics-based models: Towards the predictive maintenance of industrial robots

P Aivaliotis, Z Arkouli, K Georgoulias… - Robotics and computer …, 2021 - Elsevier
Predictive maintenance has been proposed to maximize the overall plant availability of
modern manufacturing systems. To this end, research has been conducted mainly on data …

Machine Learning Applications in Manufacturing-Challenges, Trends, and Future Directions

A Manta-Costa, SO Araújo, RS Peres… - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
The emergence of Industry 4.0 (I4. 0) has significantly transformed manufacturing
landscapes, introducing interconnected, dynamic, and data-rich environments. This article …

An IIoT-driven and AI-enabled framework for smart manufacturing system based on three-terminal collaborative platform

L Bu, Y Zhang, H Liu, X Yuan, J Guo, S Han - Advanced Engineering …, 2021 - Elsevier
Smart manufacturing has great potential in the development of network collaboration, mass
personalised customisation, sustainability and flexibility. Customised production can better …

A twin data and knowledge-driven intelligent process planning framework of aviation parts

J Li, G Zhou, C Zhang - International Journal of Production …, 2022 - Taylor & Francis
As the core link of intelligent manufacturing, the process planning of aviation parts still faces
the challenges such as relying on manual experiences for process decision-making and …

A cost-effective manufacturing process recognition approach based on deep transfer learning for CPS enabled shop-floor

B Liu, Y Zhang, J Lv, A Majeed, CH Chen… - Robotics and computer …, 2021 - Elsevier
The rapid development of the industrial Internet of Things has promoted manufacturing to
develop towards the cyber-physical system, of which highly accurate process recognition …

Adaptive design change considering making small impact on the original manufacturing process

W Shijie, Z Xueliang, L **gya, Z Yingfeng - Advanced Engineering …, 2024 - Elsevier
In the development of complex products, there are various design changes from the product
itself, costumers need, and manufacturing environment issues. However, few references …

Edge-cloud cooperation driven self-adaptive exception control method for the smart factory

W Wang, T Hu, J Gu - Advanced Engineering Informatics, 2022 - Elsevier
Production exceptions often occur due to the uncertainties of resources such as random
machine broken, urgent production tasks. The timely identification and optimal control of the …

Knowledge discovery using an enhanced latent Dirichlet allocation-based clustering method for solving on-site assembly problems

W Ning, J Liu, H **ong - Robotics and Computer-Integrated Manufacturing, 2022 - Elsevier
Prompt responses to problems/faults arising in an assembly workshop are crucial in terms of
production reliability and efficiency. However, human-dependent tasks are time-consuming …