Authors: Arantza Illarramendi, Idoia Berges
Tags: 2019, conceptual modeling, Víctor Julio Ramírez-Durán
Industrial Internet of Things (IIoT) devices operating in manufacturing plants allow capturing raw data generated by machines, regarding some indicators of interest. Multi-purpose dashboards facilitate a real-time visualization of all those raw data captured, and thus provide knowledge of each indicator. However, sometimes, domain experts interested in analyzing data belonging to specific domains find those dashboards too rigid. In this paper, we present a proposal that we have developed in a real Industry 4.0 scenario. Due to the customized visualizations that it provides, it enables domain experts to gain a greater value and insights out of the captured data. The core of the system is a new ontology that we have built, where, among others, the sensors used to capture indicators about the performance of a machine have been modeled. This semantic description allows to provide customized representations of the manufacturing machine, query formulation at a higher level of abstraction and customized graphical visualizations of the results.Read the full paper here: https://link.springer.com/chapter/10.1007/978-3-030-34146-6_11
