Application of machine learning methods for asset management on power distribution networks
GLL Rajora, MÁ Sanz Bobi, C Mateo Domingo - 2022 - repositorio.comillas.edu
This study aims to study the different kinds of Machine Learning (ML) models and their
working principles for asset management in power networks. Also, it investigates the …
working principles for asset management in power networks. Also, it investigates the …
Augmented asset management in railways–Issues and challenges in rolling stock
Managing assets in railway, including infrastructure and rolling stock, efficiently and
effectively is challenging. The emerging digital technologies and Artificial Intelligence (AI) …
effectively is challenging. The emerging digital technologies and Artificial Intelligence (AI) …
Empowering process and control in lean 4.0 with artificial intelligence
P Perico, J Mattioli - … on artificial intelligence for industries (ai4i), 2020 - ieeexplore.ieee.org
Lean Manufacturing is well known as an effective means to improve productivity and
decrease costs of operations, using a series of management practices developed first in …
decrease costs of operations, using a series of management practices developed first in …
A data-driven prioritisation framework to mitigate maintenance impact on passengers during metro line operation
A Consilvio, G Vignola, P López Arévalo… - European Transport …, 2024 - Springer
The application of artificial intelligence (AI) techniques may lead to significant improvements
in different aspects of rail sector. Considering asset management and maintenance, AI can …
in different aspects of rail sector. Considering asset management and maintenance, AI can …
Improve total production maintenance with artificial intelligence
J Mattioli, P Perico, PO Robic - 2020 Third International …, 2020 - ieeexplore.ieee.org
With Lean 4.0, Symbolic AI (Artificial Intelligence) and data-driven AI are becoming a
cornerstone to Total production Maintenance (TMP). We present in this paper is a brief …
cornerstone to Total production Maintenance (TMP). We present in this paper is a brief …
The role of artificial intelligence in Latin Americas energy transition
VMM Jimenez, EP Gonzalez - IEEE Latin America Transactions, 2022 - ieeexplore.ieee.org
Latin Americas energy transition involves the massive integration of sustainable energy,
different than hydro, at large and small scale, consumer empowerment, and the adoption of …
different than hydro, at large and small scale, consumer empowerment, and the adoption of …
Smart or intelligent assets or infrastructure: Technology with a purpose
W Serrano - Buildings, 2023 - mdpi.com
Smart or intelligent built assets including infrastructure, buildings, real estate, and cities
provide enhanced functionality to their different users such as occupiers, passengers …
provide enhanced functionality to their different users such as occupiers, passengers …
Integrated prescriptive maintenance and production planning: a machine learning approach for the development of an autonomous decision support agent
Abstract Machine Learning (ML) practice represents a vital construct for developing
intelligent Cyber-Physical Production Systems (CPPS) capable of making timely …
intelligent Cyber-Physical Production Systems (CPPS) capable of making timely …
[HTML][HTML] Information Quality: the cornerstone for AI-based Industry 4.0
J Mattioli, PO Robic, E Jesson - Procedia Computer Science, 2022 - Elsevier
AI becomes a key enabler for Industry 4.0. Data/information quality become a real
cornerstone on the overall process from user expectation to products/systems/solutions in a …
cornerstone on the overall process from user expectation to products/systems/solutions in a …
Machine failure prediction using joint reserve intelligence with feature selection technique
A Shaheen, M Hammad, W Elmedany… - … Journal of Computers …, 2023 - Taylor & Francis
A model with high accuracy of machine failure prediction is important for any machine life
cycle. In this paper, a prediction model based on machine learning methods is proposed …
cycle. In this paper, a prediction model based on machine learning methods is proposed …