The Atenea project seeks the optimisation of productive processes, in such a way as to transmit automatically and immediately the information created during manufacture (workshop) to the upper management systems. With the foregoing in mind, the aim pursued is to accelerate the decision-making process, minimising thus response and reaction times for the carrying out of a task, enhancing the application of technology related to communications, connectivity, exploitation of information with immersive means and smart information analysis.

Thus, Atenea is focused on the development of a system that is able to interrelate between the factory’s physical and management layers with the following technical aims:

  • The combination of industrial means for their integration into the Factory of Thing
  • The creation of ‘Big Data of Factory’ where the information obtained from industrial means is stored.
  • The integration with advanced design systems.
  • The development of an analysis platform for data stored by industrial means (data mining of physical means).
  • Creation of management applications for data on smart means, exploitation, creation of indicators and automated decision-making processes.

 Ayesa’s role is focused on two fundamental components:

  • Support tool for aeronautical manufacture. In this component, all the tasks that allow for the provision of support to several aeronautical manufacture processes are encompassed. Amongst these, worthy of highlighting is the creation of a virtual production assistant that will be capable of interpreting natural language. This tool will interpret in a swift and streamlined manner the needs of the stakeholders involved in the production process, offering them personalised and adapted to the specific needs related to the re-assigment of tasks, consuming information pertaining to the different systems that are involved in the manufacture of aircraft while bearing in mind the restrictions and limitations of the aeronautical industry.
  • Assistance for the troubleshooting of electrical manufacturing issues. An application is being devised to offer automatic learning technologies to provide support in different aspects of an electrical workshop. For example, the written incident sheets that workshop operators need to draft. Thanks to recent advances made in this field, the extraction of knowledge from underlying text chains is starting to become possible. The aim is to study hidden patterns in incidents to discover how the same are grouped. The revelation of these patterns allows us to automatically identify to which group an incident belongs, and permits, for example, the proposal of previously applied solutions.

This project has been co-financed by the European Fund for Regional Development (ERFD), through the “Multiregional OP for Spain” as part of the specific aim numbered “OE.1.2.1. Boosting and promotion of R&D+I activities led by companies and support in the creation and strengthening of innovative companies” and the Ministry of Science, Innovation and Universities, through the Centre for Industrial Technological Development (CDTI)-E.P.E., under the auspice  of Order ECC/1780/2013, passed on September 30th, through which the regulations governing the awarding of public aid for the State Programme for the Research, Development and Innovation Aimed at the Challenges of Society are set out, within the framework of the State Plan for Scientific and Technical Research and Innovation 2013-2016, modified through Order ECC/2483/2014, passed on December 23rd.


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