Cloud-enabled prognosis for manufacturing

R Gao, L Wang, R Teti, D Dornfeld, S Kumara, M Mori… - CIRP annals, 2015 - Elsevier
Advanced manufacturing depends on the timely acquisition, distribution, and utilization of
information from machines and processes across spatial boundaries. These activities can …

Maintenance for sustainability in the industry 4.0 context: A scoping literature review

C Franciosi, B Iung, S Miranda, S Riemma - IFAC-PapersOnLine, 2018 - Elsevier
Industrial and manufacturing systems have a huge impact on energy and resources
consumption, on the emissions to the environment and, hence, on the society. For these …

The use of Digital Twin for predictive maintenance in manufacturing

P Aivaliotis, K Georgoulias… - International Journal of …, 2019 - Taylor & Francis
This paper presents a methodology to calculate the Remaining Useful Life (RUL) of
machinery equipment by utilising physics-based simulation models and Digital Twin …

KSPMI: a knowledge-based system for predictive maintenance in industry 4.0

Q Cao, C Zanni-Merk, A Samet, C Reich… - Robotics and Computer …, 2022 - Elsevier
In the context of Industry 4.0, smart factories use advanced sensing and data analytic
technologies to understand and monitor the manufacturing processes. To enhance …

A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance

D Mourtzis, E Vlachou - Journal of manufacturing systems, 2018 - Elsevier
Abstract Manufacturing, through the Industry 4.0 concept, is moving to the next phase; that of
digitalization. Industry 4.0 enables the transition of traditional manufacturing systems to …

An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities

P O'Donovan, K Leahy, K Bruton, DTJ O'Sullivan - Journal of big data, 2015 - Springer
The term smart manufacturing refers to a future-state of manufacturing, where the real-time
transmission and analysis of data from across the factory creates manufacturing intelligence …

Identification of energy efficiency trends in the context of the development of industry 4.0 using the Polish steel sector as an example

R Wolniak, S Saniuk, S Grabowska, B Gajdzik - Energies, 2020 - mdpi.com
The steel sector is crucial for the national economy of Poland and the global economy. In
response to the challenges of the global steel market and the need to increase the sector's …

Real-time remote maintenance support based on augmented reality (AR)

D Mourtzis, V Siatras, J Angelopoulos - Applied Sciences, 2020 - mdpi.com
In the realm of the current industrial revolution, interesting innovations as well as new
techniques are constantly being introduced by offering fertile ground for further investigation …

Leveraging the capabilities of industry 4.0 for improving energy efficiency in smart factories

N Mohamed, J Al-Jaroodi, S Lazarova-Molnar - Ieee Access, 2019 - ieeexplore.ieee.org
Factories use many manufacturing processes that consume a lot of energy and highly
contribute to greenhouse gas emissions. The introduction of the concept of Industrial Internet …

[HTML][HTML] Machine condition monitoring enabled by broad range vibration frequency detecting triboelectric nano-generator (TENG)-based vibration sensors

I Mehamud, P Marklund, M Björling, Y Shi - Nano Energy, 2022 - Elsevier
Vibration analysis is an efficient method to monitor machine condition status. Different types
of vibration sensors, such as microelectromechanical, and piezoelectric accelerometers …