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Description about the development of the full demonstrator of DiCiM, a set of integrated digital solutions that makes use of Internet of Things (IoT), Machine Learning (ML) based Artificial Intelligence (AI), Big Data
 Initial data management plan Result title Initial data management plan Result description project what data will be collected processed and generated which methodology standards will be applied whether data will be sharedmade open access and how data will be curated preserved including after
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Comments storage and information mining Technologies and enablers Data storage Data collection, storage, analytics, processing and AI Information and communication technologies Standards Standards and standardisation
 Improvement on ยต-injection process Result description Thanks to this system, it is possible to automatically link the process data with the obtained part quality for the generation of an extensive manufacturing data log for its later treatment.
 ICT solutions for next generation data storage and information mining Taxon title ICT solutions for next generation data storage and information mining
 RP 1.1 Manufacturing for custom made parts Taxon description Research should also address the need for seamless data integration across the process chain (e.g. CAD, production planning, simulation and process).
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Description LinkedDesign is intended to boost today’s engineers by providing an integrated, holistic view on data, persons and processes across the full product lifecycle as vital resource for the outstanding
Comments Information and communication technologies Technologies and enablers ICT solutions for next generation data storage and information mining Technologies and enablers Data storage Data collection, storage
 ICT solutions for next generation data storage and information mining Taxon title ICT solutions for next generation data storage and information mining
 RP 5.8 Enhanced Visualisation of complex Manufacturing and Production data Taxon description Aspects of data mining and data management have to be considered in the context of this process.
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Description Data mining in combination with OLAP can support problems with diagnosis and resolution.
Comments storage and information mining Technologies and enablers Data storage Data collection, storage, analytics, processing and AI Information and communication technologies Domain 2: Adaptive and smart manufacturing
 Production Optimisation Data and Charters Result title Production Optimisation Data and Charters
 Optimizing Queries and Expressiveness Result description Therefore, the prediction is developed and trained by some given data. In combination with the prediction model the features can predict if processing data are abnormal or normal. 2.
 ICT solutions for next generation data storage and information mining Taxon title ICT solutions for next generation data storage and information mining
 Domain 3: Digital, virtual and resource-efficient factories Taxon description granularity, zoom in and out functionalities, and real-time data acquisition from all the factory resources (i.e. assets, machines, workers and objects).
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Description . - In many cases information infrastructure fails to successfully aggregate and manage data from factory-wide sensor networks as well as from various data sources such as MES or ERP, analyse such data
Comments ICT solutions for next generation data storage and information mining Technologies and enablers Data storage Data collection, storage, analytics, processing and AI Information and communication technologies
 Operator Support Result description This information consists by historical data from similar breakdowns as well as current data from applicable sensors.
 ICT solutions for next generation data storage and information mining Taxon title ICT solutions for next generation data storage and information mining
 Domain 5: Human-centric manufacturing Taxon description At the core of future manufacturing is the information generated in the factory environment, which needs to be managed and adequately transformed from the data level to the knowledge level.