Engineering: leader della Digital Transformation

Engineering Innovation In

Digital Industry

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Big Data for Industry 4.0

Centro Ricerche Fiat:
Industry 4.0

A business intelligence platform for the collection, management and visualisation of big data derived directly from IoT sensors installed on production lines.

Approach & Solution

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Approach

DIDA (Digital Industry Data Analytics) is a platform for analysing shop floor data, developed by Engineering and tested by the FIAT Research Centre as part of the OEDIPUS project. OEDIPUS (Operated European Digital Industry with Products and Services) is part of EIT Digital’s Digital Industry Action Line and focuses on creating innovative solutions for European actors in the manufacturing sector.

The DIDA Platform makes it possible to collect, store, analyse, filter and visualise a substantial amount of big data from a variety of sensors located on the production lines (e.g. from sensor-equipped welding cells) within an FCA factory.

Solution

The platform allows:
  • for the management of data from different sources;
  • production line events to be monitored and identified (for example, machine failures or quality issues);
  • the progress of relevant parameters to be visualised and support to be given to the decision-making process (such as updating the maintenance plan);
  • different applications to be developed, aimed for example at monitoring the operation of the production system and controlling and managing product quality.

DIDA adheres to the platform approaches set down in the Industry 4.0 model (Platform I4.0) and the RAMI 4.0 architectural model. In addition, the OEDIPUS DIDA platform takes advantage of the existing open source components of the ecosystem built around FIWARE and Knowage, which supports business Intelligence, big data analysis and advanced data visualisation functions.

Results

Thanks to the intuitive and dynamic interface provided by Knowage, DIDA enables users who lack specific IT skills, such as analysts and managers, to create their own analyses easily, using data from production lines. This facilitates and speeds up the decision-making process, thus helping to help prevent failures and stop them from spreading.
The project will soon be further expanded by integrating additional features for predictive analysis.

Project Value

Cost cutting
Process performance
Visibility

Enabling Technologies

Cloud
AI & Advanced Analytics
IoT

Our Products & Other Technologies

Knowage

Project Team

Knowage Labs (Research & Innovation)

Engineering Manufacturing & Automation Business Unit