Results:

The smart service description format for smart service defined in the framework of SePiA.Pro based on the TOSCA cloud standard, the connection of CPS and the language for specifying security guidelines for data processed by smart services are made freely available.

The entire Industrial Smart Service platform, consisting of Smart Service Design Platform, Smart Service Repository, Self Service Portal and Smart Service Provisioning Engine, is freely made available as open source logosepiapro_zahnraeder_rgbtogether with corresponding documentation. Furthermore, administrative tools are created to simplify the installation and configuration of the platform. The platform is used within the framework of the evaluation in the project consortium and made available to project researchers.

In the course of the project, the first smart service archives will be developed for the implementation of the two demonstration scenarios. All parts which do not contain any company-critical know-how of the consortium partners in terms of production processes and related metadata are also made freely available and can thus be used by interested parties as a point of entry into the Industrial Smart Service platform of SePiA.Pro.

A service for data integration and data transfer is to be developed, including the technical connection of this service to real cyber-physical systems as well as its integration into the TOSCA technology. This service is intended to use and process both historical and live data from cyber-physical systems for evaluation. In order to ensure compatibility with currently existing and newly developed standards, the close coordination of the service is aimed at the work of the University of Stuttgart.

The Smart Prediction Services, developed within the framework of SePiA.Pro, will build on established Open Source Machine Learning libraries and provide predictions for production process critical parameters on the basis of which intelligent system optimization can be implemented.

Development of the Industrial Analytics platform based on Apache Flink. Adaptation of the functionality to the requirements arising from the pilot demonstration scenarios. Definition and implementation of data import and export interfaces. Software integration into the overall system. Modeling and integration of the Industrial Analytics platform into a Smart Service archive. Benchmarking the performance of the platform.

Proof of the functionality and applicability of the developed Industrial Smart Service platform as well as the data integration, switching and processing by associated services in the real production environment (Daimler) and in the fleet management of machines (TRUMPF).

 

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