The AluTrace project was funded by the german Ministry of Economics, Labor and Tourism Baden-Württemberg (Ministerium für Wirtschaft, Arbeit und Tourismus Baden-Württemberg) from January 21st 2020 through December 31st 2021 under the case number 34-4224.044/21.
The aim of AluTrace was to digitally link data and knowledge silos that arise over industrial product development and manufacturing cycles. This linked data was used in order to answer a particular use case, allowing a design engineer to optimize a component with regard to lightweight design for additive manufacturing.
The project consortium, consisting of the Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Fraunhofer Institute for Mechanics of Materials IWM and fem Research Institute for Precious Metals and Metal Chemistry used legacy data and supplemented it specifically to generate semantic data, which is provided decentrally via the very first implementation of the Materials Data Space.
The semantic data created in AluTrace and provided via the Materials Data Space is additionaly provided as research data in this repository. Every release is automatically published via Zenodo using the DOI: 10.5281/zenodo.7417560.
The design algorithm developed in AluTrace to optimize lightweight design makes use of the semantic data provided via the Materials Data Space. The simulation data created by this design algorithm is published separately using the DOI: 10.5281/zenodo.7462692.
https://creativecommons.org/licenses/by-sa/4.0
Due to the great freedom of design, additive manufacturing (AM) offers enormous potential for lightweight construction. In order to harness this potential, it is crucial to integrate knowledge between the individual stages of the AM value chain. By digitally linking AM process and product data, lightweight design and production can be further optimized in economical and ecological terms.
The use case discussed here describes a design engineer who optimizes an aluminum component originally manufactured by casting with regard to lightweight design by means of topology optimization for AM. A process-specific topology optimization algorithm (PSTO) provides an optimized design and also knowledge about the best suited combination of AM-machine and corresponding process parameters. As input for this design algorithm, data about mechanical material characteristics, AM process parameters and post-processing information is required. Such heterogeneous data needs to be automatically integrated after being retrieved from a cross-institutional data space.
Since the heterogeneous data is provided by different actors, compliance with the FAIR principles is paramount. To meet this need, a data space architecture based on the International Data Spaces (IDS) Reference Architecture Model was designed and implemented. By doing so, the authors create the very first instance of the Materials Data Space® (MDS). Using the MDS in this context ensures findability (F) of the decentralized data, secure access (A) to the data via standardized protocols and a trustful ecosystem, data and systems interoperability (I) for multilateral data sharing and reusability (R) of the data due to rich metadata in form of knowledge graphs. The knowledge graphs describe the entire AM process chain semantically and embed the resulting data in its context through an ontology-based process model. This semantic metadata enables data linking in the sense of a cross-institutional data mesh with the aim of automated analysis for an intelligent lightweight design via the PSTO design algotirhtm.
When using the decentralized data from the MDS, the design engineer is empowered to provide an optimized lightweight design that results in a weight reduction of 23 percent in comparison to the cast component. Furthermore, the lightweight design demonstrates significantly improved properties compared to a geometry designed according to the previous state-of-the-art in topology optimization without linkage of material and process data via the MDS. The AluTrace use case demonstrates the benefits of a cross-institutional data space in a real-world scenario that further exploits the AM lightweight potential.
- Position paper and corresponding lightning talk on the implementation of the cross-institutional data space
- Conference presentation slides on harnessing lightweight potentials via the materials data space®
- Final project report (german)
- Technical article (german) with focus on the design algorithm
- Journal paper on the additive manufacturing process and parameters used within the Web4GenMet project
- Conference paper on the experimental investigation within the Web4GenMet project
This repository is organized as follows:
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src:
- the RDF data and ontologies, ->What data is provied?, ->How to use this data for different purposes?
- the SPARQL queries written for the project along with the returns of those SPARQL queries, ->What do the queries describe?
- the process models as templates for the individual RDF data, ->What is the process model useful for?
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doc:
- Michael Dlugosch, Fraunhofer EMI
- Valerie Friedmann, Fraunhofer IWM
- Elena Garcia Trelles, Fraunhofer IWM
- Klaus Hoschke, Fraunhofer EMI
- Martin Huschka, Fraunhofer EMI
- Ulrich Klotz, fem
- Sankalp Patil, Fraunhofer EMI
- Johannes Preußner, Fraunhofer IWM
- Christoph Schweizer, Fraunhofer IWM
- Dario Tiberto, fem
If you have any questions or feedback please don't hesitate to contact us!
Martin Huschka, Michael Dlugosch, Klaus Hoschke, Sankalp Patil
Fraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI
Ernst-Zermelo-Str. 4, 79104 Freiburg, Germany
first-name [dot] last-name [at] emi [dot] fraunhofer [dot] de
www.emi.fraunhofer.de
Christoph Schweizer, Valerie Friedmann, Johannes Preußner, Elena Garcia Trelles
Fraunhofer Institute for Mechanics of Materials IWM
Wöhlerstr. 11, 79108 Freiburg, Germany
first-name [dot] last-name [at] iwm [dot] fraunhofer [dot] de
www.iwm.fraunhofer.de
Ulrich Klotz, Dario Tiberto
fem Research Institute for Precious Metals and Metal Chemistry
Katharinenstr. 17, 73525 Schwäbisch Gmünd, Germany
last-name [at] fem-online [dot] de
www.fem-online.de