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The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process
(Springer Verlag, 2019)
Industrial processes are being developed under a new scenario based on the digitalisation of manufacturing processes.Through this, it is intended to improve the management of resources, decision-making, ...
Automatic Web Navigation Problem Detection Based on Client-Side Interaction Data
(Korea Information Processing Society-Computer Software Research Group, 2021)
The current importance of digital competence makes it essential to enable people with disabilities to use digital devices and applications and to automatically adapt site interactions to their needs. Although most of the ...
Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
(Taylor & Francis, 2021)
Tool condition monitoring have an important role in machining processes to reduce defective component and ensure quality requirements. Stopping the process before the tool breaks or an excessive tool wear is reached can ...
A maturity model for the autonomy of manufacturing systems
(Springer, 2023)
Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require ...
Survey on decentralized congestion control methods for vehicular communication
(Elsevier Ltd., 2022)
Vehicular communications have grown in interest over the years and are nowadays recognized as a pillar for the Intelligent Transportation Systems (ITSs) in order to ensure an efficient management of the road traffic and ...
Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks
(Elsevier, 2023)
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover, the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse hardware and software, and being ...
Probabilistic feature selection for improved asset lifetime estimation in renewables. Application to transformers in photovoltaic power plants
(Elsevier, 2024)
The increased penetration of renewable energy sources (RESs) as an effective mechanism to reduce carbon emissions leads to an increased weather dependency for power and energy systems. This has created dynamic operation ...
Data-Driven Fault Diagnosis for Electric Drives: A Review
(MDPI, 2021)
The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has ...
Integrated machine learning and probabilistic degradation approach for vessel electric motor prognostics
(Elsevier, 2023)
In the transition towards more sustainable ships, electric motors (EM) are being used in ship propulsion systems to reduce emissions and increase efficiency. The safe operation of ships is crucial, and prognostics and ...
A data-driven long-term metocean data forecasting approach for the design of marine renewable energy systems
(Elsevier, 2022)
The potential of Marine Renewable Energy (MRE) systems is usually evaluated based on recent metocean data and assuming the stationarity of the MRE resource. Yet, different studies in the literature have shown long-term ...
