Machine learning and reasoning for predictive maintenance in Industry 4.0: Current status and challenges
In recent years, the fourth industrial revolution has attracted attention worldwide. Several
concepts were born in conjunction with this new revolution, such as predictive maintenance …
concepts were born in conjunction with this new revolution, such as predictive maintenance …
From knowledge-based to big data analytic model: a novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0
Abstract The Internet of Things (IoT), Big Data and Machine Learning (ML) may represent
the foundations for implementing the concept of intelligent production, smart products …
the foundations for implementing the concept of intelligent production, smart products …
[HTML][HTML] Predictive maintenance for injection molding machines enabled by cognitive analytics for industry 4.0
V Rousopoulou, A Nizamis, T Vafeiadis… - Frontiers in Artificial …, 2020 - frontiersin.org
The exploitation of big volumes of data in Industry 4.0 and the increasing development of
cognitive systems, strongly facilitate the realm of predictive maintenance for real-time …
cognitive systems, strongly facilitate the realm of predictive maintenance for real-time …
ELFpm: A machine learning framework for industrial machines prediction of remaining useful life
The topic of predictive maintenance has great relevance in the search for the rationalization
and efficiency of the industrial plants in the context of Industry 4.0. Monitoring equipment …
and efficiency of the industrial plants in the context of Industry 4.0. Monitoring equipment …
Middleware for real-time event detection andpredictive analytics in smart manufacturing
Industry 4.0 is a recent trend of automation for manufacturing technologies and represents
the fourth industrial revolution which transforms current industrial processes with the use of …
the fourth industrial revolution which transforms current industrial processes with the use of …
A framework for big data analytical process and mapping—BAProM: Description of an application in an industrial environment
GG de Carvalho Chrysostomo, MVB de Aguiar Vallim… - Energies, 2020 - mdpi.com
This paper presents an application of a framework for Big Data Analytical Process and
Mapping—BAProM—consisting of four modules: Process Mapping, Data Management, Data …
Mapping—BAProM—consisting of four modules: Process Mapping, Data Management, Data …
Predictive analytics in a pulp mill using factory automation data—hidden potential
M Nykyri, M Kuisma, TJ Kärkkäinen… - 2019 IEEE 17th …, 2019 - ieeexplore.ieee.org
Industrial automation systems have collected vast amounts of data for years. Data analytics
and machine learning can be used to reveal different phenomena and anomalies, which …
and machine learning can be used to reveal different phenomena and anomalies, which …
[HTML][HTML] Reliability-as-a-Service for bearing risk assessment investigated with advanced mathematical models
As a key player in bearing service life, the lubricant chemistry has a profound effect on
bearing reliability. To increase the reliability of bearings, an Industrial Analytics solution is …
bearing reliability. To increase the reliability of bearings, an Industrial Analytics solution is …
Deep Learning based Decision Support Systems for Quality Control task in Industry 4.0
R Rosati - 2023 - iris.univpm.it
In the context of Industry 4.0, the increasing amount of data in combination with novel
disruptive Machine Learning (ML) and Deep Learning (DL) methodologies lied the …
disruptive Machine Learning (ML) and Deep Learning (DL) methodologies lied the …
Data analysis in the production process of electrical drive systems
T Herold, S Böhmer, D Franck… - 6. Conference on …, 2017 - mediatum.ub.tum.de
In a classical production process of electrical machines, the individual components are
usually regarded as mechanical components. In this case, the process monitoring is …
usually regarded as mechanical components. In this case, the process monitoring is …