EASI: Cloud-based, real-time data analysis through simulation and iteration

© Fraunhofer IPA, Photo: Rainer Bez
In the EASI project, real machine data are compared with simulation data from the same machine in order to detect functional discrepancies.

In Short

In a cooperative practical project with the companies Virtual Fort Knox AG and Lexer Research Inc., the real data from a Festo machine was compared with the target data from the simulation. This enables the learning factory to be implemented, which opens up new optimization possibilities for increasing productivity.

In Detail

The EASI project implements the digital PDCA (Plan-Do-Check-Act) cycle with real-time data acquisition by integrating Virtual Fort Knox's IoT solution and Lexer Research's cloud-based production simulator GDfindi.

Via the Manufacturing Service Bus (MSB), Virtual Fort Knox collects and transmits data to a simulation controller using the Virtual Fort Knox Cloud real-time data transmission service. The MSB and the GDfindi simulator are integrated via the Virtual Fort Knox Research Platform. For this purpose, the data from a Festo machine set up at Fraunhofer IPA are recorded and compared with the simulation data from GDfindi via a simulation controller. This allows conclusions to be drawn about discrepancies between the real data and the simulation data.

The EASI solution is primarily aimed at small and medium-sized manufacturing companies who are able to set up a cloud environment and network their systems appropriately.

In general, this enables the advantages of a learning and transparent production to be exploited:

“What can be learned from the differences between target and real data?”

and production to be anticipated:

“What does the emerging difference between target and real data mean for the planned daily production? Does action need to be taken?”

Insight into the project

Cloud Mall BW

EASI was carried out as part of joint project Cloud Mall Baden-Württemberg (Cloud Mall BW). Cloud Mall BW is concerned with identifying and exploiting the potential and possibilities of cloud computing for medium-sized enterprises in Baden-Württemberg. The project offers a framework for small and medium-sized cloud service providers and users to enter into cooperative ventures with one another, strengthen their own networks and thereby actively increase their competitive advantages. Cooperative ideas from small and medium-sized cloud service or cloud platform providers are specifically promoted in practical pilot projects with support from the Cloud Mall BW project team in the form of personnel and expertise.

The joint project is funded by the Baden-Württemberg Ministry of Economics, Labor and Housing. Participants are the Fraunhofer Institute for Industrial Engineering IAO, the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, the Institute for Enterprise Systems at the University of Mannheim InES and bwcon research GmbH.

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