Data Backbone

Data Backbone

Data infrastructure for continuous production without system interruptions

Data Backbone

Data Backbone is integrated digital engineering from the production order to the executable robot program based on an infrastructure that unites process data and relevant data models from all areas of the company.

Project description

Access to digital process data

Do you have lots of data formats that are incompatible because they originate from different domains? Are system interruptions keeping you from automating your production platforms? There is a solution. In the Data Backbone project, fortiss is developing an infrastructure that combines data models and provides access to digital process data. The vision is to be able to automatically create the production process and the robot programming from one production order.

Seamless data exchange

The prerequisite for this vision is a process description with analyzable content that is digitally available regardless of the programming language. Data Backbone provides access to all of the data relevant to the entire value chain and ensures the uninterrupted exchange of data between the systems, thus making it possible to have a continuous, automated production environment that is efficient and transparent.

Funding

Bavarian Ministry of Economic Affairs, Regional Development and Energy (STMWI) with project support by Bayern Innovativ former ZentrumDigitalisierung Bayern (ZD.B).

Project duration

01.01.2018 - 31.03.2020

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Toward a Knowledge-Based Data Backbone for Seamless Digital Engineering in Smart Factories
Alexander Perzylo

Your contact

Alexander Perzylo

+49 89 3603522 531
perzylo@fortiss.org

Project partner

DRÄXLMAIER

Publications

  • 2020 Toward a Knowledge-Based Data Backbone for Seamless Digital Engineering in Smart Factories Alexander Perzylo , Ingmar Kessler , Stefan Profanter and Markus Rickert In Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), pages 164–171, Vienna, Austria, 2020. Details URL DOI BIB
  • 2019 A Hardware-Agnostic OPC UA Skill Model for Robot Manipulators and Tools Stefan Profanter , Ari Breitkreuz , Markus Rickert and Alois Knoll In Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), Zaragoza, Spain, 2019. Details BIB
  • 2019 OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources Alexander Perzylo , Stefan Profanter , Markus Rickert and Alois Knoll In Proceedings of the IEEE International Conference on Emerging Technologies And Factory Automation (ETFA), pages 1085–1092, Zaragoza, Spain, 2019. Details URL DOI BIB