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Integrative Computational Design and Construction for Architecture (T3.0)
Research
Research Projects
RP 15-1 – Data Management and Artificial Intelligence Approaches

Data Management and Artificial Intelligence Approaches

Research Project 15-1 (RP 15-1)

DATA MANAGEMENT AND ARTIFICIAL INTELLIGENCE APPROACHES FOR DATA-INTEGRATED COMPUTATIONAL DESIGN, SIMULATION, AND FABRICATION

The overarching goal of this project is to develop novel methods to capture and leverage various forms of data to enable co-design between different phases of building individual fiber-based modules to be used as part of long-span buildings. Towards reaching this goal, the research project first focuses on data-based co-design for the structural long-span building design, simulation, and manufacturing of the aforementioned components. As of today, these different specialist divisions are typically performed sequentially and no data is systematically captured, transferred, or analyzed between these for (subsequent) optimization of the production process of similar modules.
In tight collaboration with further projects of this research network, the project will investigate how to model and integrate data about design criteria of the fabrication process and simulated material properties, structural data for transfer into instructions for fabrication, and fabrication constraints and fabrication data obtained through sensors. The research project will then explore how to use these data to bootstrap simulations and planning algorithms to improve the overall efficiency and quality of the fabrication process. This project will result in novel techniques for data processing coupled with artificial intelligence for efficient and effective co-design, applied in the context of constructing long-span buildings.

PRINCIPAL INVESTIGATORS

Prof. Dr.-Ing. Peter Middendorf
Institute for Aircraft Design (IFB), University of Stuttgart
Prof. Dr.-Ing. Alexander Verl
Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW), University of Stuttgart

PARTICIPATING RESEARCHER

Prof. Dr.-Ing. Cristina Tarín Sauer (ISYS)

TEAM
Dr.-Ing. Stefan Carosella (IFB)
Dr.-Ing. Andreas Gienger (ISYS)
Dr.-Ing. Armin Lechler (ISW)
Jörg Dittmann (IFB)
Carsten Ellwein (ISW)
Sebastian Hügle (IFB)
Alexander Reichle (ISW)

PEER-REVIEWED PUBLICATIONS

2022
1. Gil Pérez, M., Zechmeister, C., Kannenberg, F., Mindermann, P., Balangé, L., Guo, Y., Hügle, S., Gienger, A., Forster, D., Bischoff, M., Tarín, C., Middendorf, P., Schwieger, V., Gresser, G. T., Menges, A., & Knippers, J. (2022). Computational co-design framework for coreless wound fibre-polymer composite structures. Journal of Computational Design and Engineering, 9(2), Article 2. https://doi.org/10.1093/jcde/qwab081
  - BibTeX
  BibTeX
  @article{Gil_Perez_2022, abstract = {In coreless filament winding, resin-impregnated fibre filaments are wound around anchor points without an additional mould. The final geometry of the produced part results from the interaction of fibres in space and is initially undetermined. Therefore, the success of large-scale coreless wound fibre composite structures for architectural applications relies on the reciprocal collaboration of simulation, fabrication, quality evaluation, and data integration domains. The correlation of data from those domains enables the optimization of the design towards ideal performance and material efficiency. This paper elaborates on a computational co-design framework to enable new modes of collaboration for coreless wound fibre–polymer composite structures. It introduces the use of a shared object model acting as a central data repository that facilitates interdisciplinary data exchange and the investigation of correlations between domains. The application of the developed computational co-design framework is demonstrated in a case study in which the data are successfully mapped, linked, and analysed across the different fields of expertise. The results showcase the framework’s potential to gain a deeper understanding of large-scale coreless wound filament structures and their fabrication and geometrical implications for design optimization.}, author = {Gil Pérez, M and Zechmeister, C and Kannenberg, F and Mindermann, P and Balangé, L and Guo, Y and Hügle, S and Gienger, A and Forster, D and Bischoff, M and Tarín, C and Middendorf, P and Schwieger, V and Gresser, G T and Menges, A and Knippers, J}, doi = {10.1093/jcde/qwab081}, journal = {Journal of Computational Design and Engineering}, month = {04}, note = {M. Gil Perez and C. Zechmeister: first authors equal contribution. F. Kannenberg and P. Mindermann: second authors equal contribution.}, number = 2, pages = {310--329}, publisher = {Oxford University Press ({OUP})}, title = {Computational co-design framework for coreless wound fibre-polymer composite structures}, url = {https://doi.org/10.1093%2Fjcde%2Fqwab081}, volume = 9, year = 2022 }
2. Kaiser, B., Reichle, A., & Verl, A. (2022). Model-based automatic generation of digital twin models for the simulation of reconfigurable manufacturing systems for timber construction. Procedia CIRP, 107, 387--392. https://doi.org/10.1016/j.procir.2022.04.063
  - BibTeX
  BibTeX
  @inproceedings{Kaiser_2022, author = {Kaiser, Benjamin and Reichle, Alexander and Verl, Alexander}, doi = {10.1016/j.procir.2022.04.063}, journal = {Procedia {CIRP}}, pages = {387--392}, publisher = {Elsevier {BV}}, title = {Model-based automatic generation of digital twin models for the simulation of reconfigurable manufacturing systems for timber construction}, url = {https://doi.org/10.1016%2Fj.procir.2022.04.063}, volume = 107, year = 2022 }
3. Reichle, A., Ellwein, C., & Verl, A. (2022). Adaptive CAM planning to support co-design in the building industry. In N. Anwer (Ed.), Procedia CIRP (Vol. 109, pp. 78–83). https://doi.org/10.1016/j.procir.2022.05.217
  - BibTeX
  BibTeX
  @inproceedings{reichle2022adaptive, address = {Elsevier {BV}}, author = {Reichle, Alexander and Ellwein, Carsten and Verl, Alexander}, doi = {10.1016/j.procir.2022.05.217}, editor = {Anwer, Nabil}, journal = {Procedia {CIRP}}, pages = {78-83}, title = {Adaptive CAM planning to support co-design in the building industry}, url = {https://doi.org/10.1016/j.procir.2022.05.217}, volume = 109, year = 2022 }
2021
1. Ellwein, C., Reichle, A., Herschel, M., & Verl, A. (2021). Integrative data processing for cyber-physical off-site and on-site construction promoting co-design. Procedia CIRP, 100, 451–456. https://doi.org/10.1016/j.procir.2021.05.103
  - BibTeX
  BibTeX
  @article{Ellwein_2021, abstract = {The term co-design describes a collaborative design process, usually across the boundaries of individual areas. A major aspect, and often an obstacle in the implementation of the co-design approach, is the establishment of a centralized data management system. In the past, the data management concept has been approached from different perspectives. Current approaches usually are oriented along the process chain and thus reflect a unidirectional flow of information. Neither the information feedback nor the reaction to adjustments in upstream model steps is supported, which makes continuous collaboration more difficult and at best reduces the co-design approach for continuous data usage. This paper addresses these weaknesses while outlining an integrative data processing concept enabling co-design between the domains of construction and industrial prefabrication. Geometrical information generated during architectural design and construction planning is reused for the production of components, manufacturing-related design adjustments are transferred back into the domain of construction. Changes throughout the entire process are centrally recorded. To ensure independence from the software tools used and to consider their great diversity, data exchange is largely based on standards, namely industry foundation classes and the standard for the exchange of product model data. In order to counteract the sequential processing according to a waterfall model and to support the co-design approach, the industrial prefabrication toolchain, consisting of computer-aided manufacturing software and downstream postprocessors, is largely automated, so that reprocessing of a workpiece for minor geometric adjustments no longer requires any interaction of the production planner.}, author = {Ellwein, Carsten and Reichle, Alexander and Herschel, Melanie and Verl, Alexander}, doi = {10.1016/j.procir.2021.05.103}, journal = {Procedia CIRP}, note = {31st CIRP Design Conference 2021 (CIRP Design 2021)}, pages = {451-456}, publisher = {Elsevier {BV}}, title = {Integrative data processing for cyber-physical off-site and on-site construction promoting co-design}, url = {https://www.sciencedirect.com/science/article/pii/S2212827121005746}, volume = 100, year = 2021 }

OTHER PUBLICATIONS

DATA SETS

Prof. Dr.-Ing. Peter Middendorf

Principal Investigator

Phone: +49 711 685 62411

E-Mail

Prof. Dr.-Ing. Cristina Tarín Sauer

Participating Researcher

Phone: +49 711 685 83253

E-Mail

Prof. Dr.-Ing. Alexander Verl

Principal Investigator

Phone: +49 711 685 82422

E-Mail