TY - GEN
T1 - Manufacturing Data Analytics for Manufacturing Quality Assurance
AU - Lourenço, Luís Carlos Guimarães
AU - Figueiras, Paulo Alves
AU - Costa, Ruben
AU - Ntemi, Myrsini
AU - Mandler, Benjamin
AU - Tsanousa, Athina
AU - Gialampoukidis, Ilias
AU - Gomez, Ana
AU - Urko, Leturiondo
AU - Vrochidis, Stefanos
AU - Gálvez-Settier, Santiago
AU - Poler, Raul
N1 - The authors acknowledge the European Commission for the support and funding under the scope of Horizon2020 i4Q Innovation Project (Agreement Number 958205) and the remaining partners of the i4Q Project Consortium.
PY - 2022/9
Y1 - 2022/9
N2 - Nowadays, manufacturing companies are eager to access insights from advanced analytics, without requiring them to have specialized IT workforce or data science advanced skills. Most of current solutions lack of easy-to-use advanced data preparation, production reporting and advanced analytics and prediction. Thanks to the increase in the use of sensors, actuators and instruments, European manufacturing lines collect a huge amount of data during the manufacturing process, which is very valuable for the improvement of quality in manufacturing, but analyzing huge amounts of data on a daily basis, requires heavy statistical and technology training and support, making them not accessible for SMEs. The European i4Q Project, aims at providing an IoT-based Reliable Industrial Data Services (RIDS), a complete suite consisting of 22 i4Q Solutions, able to manage the huge amount of industrial data coming from cheap cost-effective, smart, and small size interconnected factory devices for supporting manufacturing online monitoring and control. This paper will present a set of i4Q services, for data integration and fusion, data analytics and data distribution. Such services, will be responsible for the execution of AI workloads (including at the edge), enabling the dynamic deployment industrial scenarios based on a cloud/edge architecture. Monitoring at various levels is provided in i4Q through scalable tools and the collected data, is used for a variety of activities including resource monitoring and management, workload assignment, smart alerting, predictive failure and model (re)training.
AB - Nowadays, manufacturing companies are eager to access insights from advanced analytics, without requiring them to have specialized IT workforce or data science advanced skills. Most of current solutions lack of easy-to-use advanced data preparation, production reporting and advanced analytics and prediction. Thanks to the increase in the use of sensors, actuators and instruments, European manufacturing lines collect a huge amount of data during the manufacturing process, which is very valuable for the improvement of quality in manufacturing, but analyzing huge amounts of data on a daily basis, requires heavy statistical and technology training and support, making them not accessible for SMEs. The European i4Q Project, aims at providing an IoT-based Reliable Industrial Data Services (RIDS), a complete suite consisting of 22 i4Q Solutions, able to manage the huge amount of industrial data coming from cheap cost-effective, smart, and small size interconnected factory devices for supporting manufacturing online monitoring and control. This paper will present a set of i4Q services, for data integration and fusion, data analytics and data distribution. Such services, will be responsible for the execution of AI workloads (including at the edge), enabling the dynamic deployment industrial scenarios based on a cloud/edge architecture. Monitoring at various levels is provided in i4Q through scalable tools and the collected data, is used for a variety of activities including resource monitoring and management, workload assignment, smart alerting, predictive failure and model (re)training.
M3 - Conference contribution
T3 - CEUR Workshop Proceedings
BT - Proceedings of Interoperability for Enterprise Systems and Applications Workshops co-located with 11th International Conference on Interoperability for Enterprise Systems and Applications (I-ESA 2022)
A2 - Zelm, Martin
A2 - Boza, Andrés
A2 - León, Ramona-Diana
A2 - Rodriguez-Rodriguez, Raul
T2 - 2022 Interoperability for Enterprise Systems and Applications Workshops, I-ESA Workshops 2022
Y2 - 23 March 2022 through 25 March 2022
ER -