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26-tik 21-26 emaitza erakusten
A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes
(Elsevier, 2023)
For Industry 4.0, tool condition monitoring (TCM) of machining processes aims to increase process efficiency and quality and lower tool maintenance costs. To this end, TCM systems monitor variables of interest, such as ...
Data Sovereignty for AI Pipelines: Lessons Learned from an Industrial Project at Mondragon Corporation
(ACM, 2022)
The establishment of collaborative AI pipelines, in which multiple organizations share their data and models, is often complicated by lengthy data governance processes and legal clarifications. Data sovereignty solutions, ...
Towards Standardized Manufacturing as a Service through Asset Administration Shell and International Data Spaces Connectors
(IEEE, 2022)
This paper presents an industrial scenario that simulates a Manufacturing as a Service system for the execution of remote production orders built upon the implementation of emerging Asset Administration Shell (AAS) ...
Towards an Asset Administration Shell scenario: a use case for interoperability and standardization in Industry 4.0
(IEEE, 2020)
The new paradigm of the Industry 4.0 centers on the digitalization of assets to realize a new industrial revolution. Standardization and interoperability are key for the successful implementation of this digitalization ...
Data-driven energy resource planning for Smart Cities
(IEEE, 2020)
Cities are growing and, therefore, the primary needs, such as the energy resources. Hence, managing them in the proper way becomes essential for a sustainable growth. This paper proposes a data-driven tool based on IoT ...
Monitorización de estado de la herramienta en mecanizado mediante redes neuronales residuales robustas
(Cluster for Advanced & Digital Manufacturing, 2023)
La monitorización del estado de la herramienta (TCM) tiene como objetivo mejorar la eficiencia del proceso, la calidad y los costos de mantenimiento de las herramientas mediante la supervisión de variables críticas como ...