BDIH - Aernnova

Aernnova is a top level supplier of aeronautical structures for major manufacturers such as Airbus, Embraer, Boeing. We are the main Tier 1 supplier in Spain and the tenth in the world. Burulan is Aernnova’s mechanised centre of excellence located in the Miñano Technology Park where small and medium size aluminium and titanium metallic components are manufactured. For this, the centre possesses the right technology to meet the demands of our customers: multipallet machining centres, FMSs in 4 and 5 axes, conventional machining, shot peening, surface treatments and all the necessary equipment. All this encompassed within digital and connected factory.

01:03 - In the aeronautical sector, products are often manufactured in a short series with a high number of units, which requires us to have a highly efficient production line. The project focuses on the area of industrialisation and improving productivity, as well as the continuous improvement of manufacturing processes in a robust and efficient manner, with the end goal of obtaining a flexible, intelligent and efficient manufacturing system. The budget of this project was 50,000 to 100,000 euros with an implementation period of maximum 16 months. Throughout the project, we analysed the milling of a series of parts with low rigidity. To carry out this analysis, we integrated the mechanisation centres with all the necessary sensors.

01:52 - A data acquisition system was deployed during the mechanisation, containing a web storage and data processing solution to identify the process variables, including the monitoring of signals from the CNC and other sensors. Advanced design tools have been applied, which integrate force and dynamic models to identify the model, part, tooling and machine, also characterising the most significant tools in the process, in order to obtain more stable and productive cutting conditions reliably from the initial approach. From a web environment, the application shows the equipment in real time. A series of specific utilities have been developed, through self-learning techniques that allow for the analysis and extraction of useful information from the machining process, visualising the evolution of the variables and allowing for the optimisation of the machining process and an analysis of any arising incidents. This project has allowed us to significantly reduce mechanisation times for the types of parts considered with the proposed universal clamping system.

03:08 - By using these process models, the times for defining and fine-tuning new references have been reduced, making it possible to identify the optimum conditions in advance and reduce the vibrations produced during the mechanisation process. A particular focus was placed on the characterisation of cutting tools. By applying new conditions, we were able to obtain an increase in productivity and useful life of the tools, resulting in a lower wear of the machine in the long term. We are now able to monitor the stable machining processes, having established specific process patterns that can be consulted from any connected device through an agile web solution. .