Issue |
MATEC Web Conf.
Volume 304, 2019
9th EASN International Conference on “Innovation in Aviation & Space”
|
|
---|---|---|
Article Number | 04004 | |
Number of page(s) | 8 | |
Section | Systems | |
DOI | https://doi.org/10.1051/matecconf/201930404004 | |
Published online | 17 December 2019 |
An IIoT-based architecture for decision support in the aeronautic industry
1
Center for Enterprise Systems Engineering, INESC TEC,
4200-425,
Porto,
Portugal
2
Faculty of Science and Technology, Federal University of Goiás,
74968-755
Goiás,
Brazil
3
Embraer SA, Avenida Brigadeiro Faria Lima,
2170, CEP
12227-901
São José dos Campos,
Brazil
The Industry 4.0 movement is driving innovation in manufacturing through the application of digital technologies, leading to solid performance improvements. In this context, this paper introduces a real-time analytical framework based on predictive, simulation and optimization technologies applied to decision support in manufacturing systems, enabled by an underlying reference implementation of an open Industrial Internet of Things (IIoT) platform. This architecture integrates critical equipment, manufacturing and corporate systems through a Unified IIoT Cloud Platform. A real case study on the aeronautic industry demonstrates the proposal feasibility of this architecture to enhance productivity, predict equipment failures and bring agility to react to unexpected events. In this case study, the monitoring tool displays the current status of the critical resources and the predictive tool calculates a probability of failure. When this probability reaches a certain threshold, the simulation tool is triggered to evaluate the impact of the disruption in the system’s productivity. Results from the tools are displayed online through an alert system so that each stakeholder is informed timely and in a contextualized way.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.