Zerrendatu honen arabera: egilea "00a8e8f45728506cb8a26c922e89040e"
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Big Data Life Cycle in Shop-floor. Trends and Challenges
Peralta Abadía, José Joaquín; Carrera-Rivera, Angela (IEEE, 2023)Big data is defined as a large set of data that could be structured or unstructured. In manufacturing shop-floor, big data incorporates data collected at every stage of the production process. This includes data from ... -
A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes
Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix (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 ... -
Monitorización de estado de la herramienta en mecanizado mediante redes neuronales residuales robustas
Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix (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 ... -
Monitorización del estado de la herramienta en mecanizado mediante redes neuronales residuales robustas
Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix (Dyna, 2024)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 ... -
Optimal manufacturing configuration selection: sequential decision making and optimization using reinforcement learning
Peralta Abadía, José Joaquín; CUESTA ZABALAJAUREGUI, MIKEL; Larrinaga, Felix; ARRAZOLA, PEDRO JOSE (Elsevier, 2023)In manufacturing, different costs must be considered when selecting the optimal manufacturing configuration. Costs include manufacturing costs, material costs, labor costs, and overhead costs. Optimal manufacturing ... -
OptiTwin: Data-Driven Machining Process Optimization Platform for SMEs
Peralta Abadía, José Joaquín; Larrinaga, Felix; CUESTA ZABALAJAUREGUI, MIKEL; Badiola, Xabier; Duo, Aitor; Olalde Mendia, Gorka (IEEE, 2024)The manufacturing industry is constantly seeking innovative solutions to optimize machining processes. However, there is a lack of efficient digital platforms that fully meet the flexibility, service composition, and ...
