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Integrative Computational Design and Construction for Architecture (T3.0)
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RP 9-2 – Data Processing and AI for Predictive, Adaptive Co-Design

Data Processing and AI for Predictive, Adaptive Co-Design

Research Project 9-2 (RP 9-2)

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Research Project 9-2 – Data Processing and AI for Predictive and Adaptive Co-Design

DATA PROCESSING AND AI FOR PREDICTIVE AND ADAPTIVE CO-DESIGN IN PREFABRICATION AND ON-SITE CONSTRUCTION

A major challenge for the cluster's Co-Design approach is integrative data management across all phases of building processes. While this challenge has been targeted from different perspectives, utilising data models and formats specific to different domains (e.g. building engineering, mechanical and plant engineering), it has not yet been overcome. The models typically represent the flow along the process chain and have limited interoperability. A broader view based on combined data from different phases and backflow of information is not well supported. This project addresses these shortcomings by creating a central data management (CDM) platform that integrates data from multiple phases of the building process, supports Co-Design based on artificial intelligence (AI) by jointly analysing these data, and provides data-derived feedback to various parties involved. Having defined the CDM software architecture and implemented a first Co-Design application in the previous Research Project RP 9-1, we are now focusing on data integration algorithms embedded in predictive and adaptive Co-Design, applying AI methods to prefabrication and on-site construction.

PRINCIPAL INVESTIGATORS

Prof. Dr. Melanie Herschel
Institute for Parallel and Distributed Systems (IPVS), University of Stuttgart
Tenure-Track Prof. Dr. Thomas Wortmann
Chair for Computing in Architecture, Institute for Computational Design and Construction (ICD), University of Stuttgart
Prof. Dr.-Ing. Cristina Tarín Sauer
Institute for System Dynamics (ISYS), University of Stuttgart

TEAM

Lior Skoury (ICD)
Charlotte Stein (ISYS)

PEER-REVIEWED PUBLICATIONS

2024
1. Gienger, A., Stein, C., Lauer, A. P. R., Sawodny, O., & Tarín, C. (2024). Data-Based Reachability Analysis and Optimized Robot Positioning for Co-Design of Construction Processes. 2024 IEEE/SICE International Symposium on System Integration (SII).
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  @conference{noauthororeditor, author = {Gienger, Andreas and Stein, Charlotte and Lauer, Anja Patricia Regina and Sawodny, Oliver and Tarín, Cristina}, booktitle = {2024 IEEE/SICE International Symposium on System Integration (SII)}, title = {Data-Based Reachability Analysis and Optimized Robot Positioning for Co-Design of Construction Processes}, year = 2024 }
2. Herschel, M., Gienger, A., Lauer, A. P. R., Stein, C., Skoury, L., Lässig, N., Ellwein, C., Verl, A., Wortmann, T., & Tarin Sauer, C. (2024). Putting Co-Design-Supporting Data Lakes to the Test: An Evaluation on AEC Case Studies. International Conference on Big Data Analytics and Knowledge Discovery (DAWAK).
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  @inproceedings{herschel2024putting, author = {Herschel, Melanie and Gienger, Andreas and Lauer, Anja P. R. and Stein, Charlotte and Skoury, Lior and Lässig, Nico and Ellwein, Carsten and Verl, Alexander and Wortmann, Thomas and Tarin Sauer, Cristina}, booktitle = {International Conference on Big Data Analytics and Knowledge Discovery (DAWAK)}, title = {Putting Co-Design-Supporting Data Lakes to the Test: An Evaluation on AEC Case Studies}, year = 2024 }
3. Lässig, N., & Herschel, M. (2024). FALCC: Efficiently performing locally fair and accurate classifications. International Conference on Extending Database Technology (EDBT). https://openproceedings.org/2024/conf/edbt/paper-59.pdf
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  @conference{lassig2024falcc, author = {Lässig, Nico and Herschel, Melanie}, booktitle = {International Conference on Extending Database Technology (EDBT)}, publisher = {OpenProceedings}, title = {FALCC: Efficiently performing locally fair and accurate classifications}, url = {https://openproceedings.org/2024/conf/edbt/paper-59.pdf}, year = 2024 }
4. Lässig, N., Nies, O., & Herschel, M. (2024). FairCR - An Evaluation and Recommendation System for Fair Classification Algorithms. Proceedings of the International Conference on Data Engineering (ICDE).
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  @inproceedings{lassig2024faircr, author = {Lässig, Nico and Nies, Ole and Herschel, Melanie}, booktitle = {Proceedings of the International Conference on Data Engineering (ICDE)}, title = {FairCR - An Evaluation and Recommendation System for Fair Classification Algorithms}, year = 2024 }
5. Opgenorth, N., Cheng, T., Lauer, P. R. A., Stark, T., Tahouni, Y., Treml, S., Göbel, M., Kiesewetter, L., Schlopschnat, C., Zorn, M. B., Yang, X., Amtsberg, F., Wagner, H. J., Wood, D., Sawodny, O., Wortmann, T., & Menges, A. (2024). Multi-scalar computational fabrication and construction of bio-based building envelopes – the livMatS biomimetic shell. Fabricate 2024: Creating Resourceful Futures, 22–31. https://doi.org/10.2307/jj.11374766.7
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  @inproceedings{noauthororeditor, author = {Opgenorth, Nils and Cheng, Tiffany and Lauer, Patricia Regina Anja and Stark, Tim and Tahouni, Yasaman and Treml, Simon and Göbel, Monika and Kiesewetter, Laura and Schlopschnat, Christoph and Zorn, Max Benjamin and Yang, Xiliu and Amtsberg, Felix and Wagner, Hans Jakob and Wood, Dylan and Sawodny, Oliver and Wortmann, Thomas and Menges, Achim}, booktitle = {Fabricate 2024: Creating Resourceful Futures}, doi = {10.2307/jj.11374766.7}, isbn = {9781800086357}, pages = {22-31}, publisher = {UCL Press}, title = {Multi-scalar computational fabrication and construction of bio-based building envelopes – the livMatS biomimetic shell}, url = {http://www.jstor.org/stable/jj.11374766.7}, year = 2024 }
6. Skoury, L., Leder, S., Menges, A., & Wortmann, T. (2024). Digital twin architecture for the AEC Industry : A case study in collective robotic construction. Inproceeding Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, 413–418. https://doi.org/10.1145/3652620.3688255
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  @conference{skoury2024digital, abstract = {The Architecture, Engineering, and Construction (AEC) industry faces increasing demand for customized products and is undergoing transformation through Industry 4.0, necessitating adaptable production systems. Digital twins---virtual counterparts of physical systems---enable real-time synchronization, monitoring, and optimization of construction processes, addressing limitations of manual, fragmented methods. This research presents a digital twin architecture designed to improve digital fabrication in the AEC sector. The architecture includes action modelling, virtual actor modelling, and service modelling, all coordinated by a central engine integrating a Cyber-Physical System (CPS) with its digital twin. The proposed approach standardizes data flow, integrates various fabrication methods, and supports rapid prototyping, tackling complexities in modern AEC environments. A case study from a Collective Robotic Construction (CRC) workshop demonstrates the architecture's practical application, showcasing its ability to streamline workflows, enhance scalability, and improve collaboration. Key findings indicate that this digital twin architecture effectively integrates digital twins into fabrication processes, offering a scalable and reliable solution that enhances adaptability and innovation in construction practices.}, author = {Skoury, Lior and Leder, Samuel and Menges, Achim and Wortmann, Thomas}, booktitle = {inproceeding Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems}, doi = {10.1145/3652620.3688255}, eventtitle = {MODELS Companion '24: ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems}, isbn = {9798400706226}, pages = {413-418}, publisher = {ACM}, title = {Digital twin architecture for the AEC Industry : A case study in collective robotic construction}, url = {https://dl.acm.org/doi/10.1145/3652620.3688255}, venue = {Linz Austria}, year = 2024 }
7. Skoury, L., Treml, S., Opgenorth, N., Amtsberg, F., Wagner, H. J., Menges, A., & Wortmann, T. (2024). Towards data-informed co-design in digital fabrication. Automation in Construction, 158, 105229. https://doi.org/10.1016/j.autcon.2023.105229
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  BibTeX
  @article{Skoury_2024, author = {Skoury, Lior and Treml, Simon and Opgenorth, Nils and Amtsberg, Felix and Wagner, Hans Jakob and Menges, Achim and Wortmann, Thomas}, doi = {10.1016/j.autcon.2023.105229}, issn = {0926-5805}, journal = {Automation in Construction}, month = {02}, pages = 105229, publisher = {Elsevier BV}, title = {Towards data-informed co-design in digital fabrication}, url = {http://dx.doi.org/10.1016/j.autcon.2023.105229}, volume = 158, year = 2024 }
8. Skoury, L., & Wortmann, T. (2024). Prediction Models for Co-Design in Industry 4.0. In P. Eversmann, C. Gengnagel, J. Lienhard, M. Ramsgaard Thomsen, & J. Wurm (Eds.), Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024) (pp. 507–519). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-68275-9_41
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  @conference{skoury2024bridging, abstract = {In the realm of Industry 4.0, significant changes have unfolded across various sectors, notably in construction, driven by the adoption of digitisation and automation. This transformation demands a reassessment of traditional practices within the Architectural, Engineering, and Construction (AEC) industry. In response, the concept of Co-Design has emerged, offering a promising avenue to integrate diverse expertise and stakeholders throughout the construction process. This study explores the fusion of Co-Design principles with ML techniques to elevate fabrication processes and project outcomes within the AEC industry. The research introduces a workflow that intertwines design, fabrication, and data analysis by implementing a fabrication prediction ML model. By harnessing real-world data from timber additive construction processes, the model is trained to predict task durations accurately. This not only tackles the inherent complexities of fabrication processes but also provides flexibility across different design scenarios and fabrication environments. Through systematic evaluation and testing, the study identifies the most effective ML algorithms for predicting fabrication times. Furthermore, it showcases the practical application of the prediction model in optimising fabrication setups, ultimately resulting in tangible enhancements in efficiency and productivity.}, author = {Skoury, Lior and Wortmann, Thomas}, booktitle = {Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024)}, doi = {10.1007/978-3-031-68275-9_41}, editor = {Eversmann, Philipp and Gengnagel, Christoph and Lienhard, Julian and Ramsgaard Thomsen, Mette and Wurm, Jan}, eventdate = {16. — 18. September 2024}, eventtitle = {DESIGN MODELLING SYMPOSIUM KASSEL 2024 – SCALABLE DISRUPTORS}, isbn = {978-3-031-68274-2 978-3-031-68275-9}, pages = {507-519}, publisher = {Springer Nature Switzerland}, title = {Prediction Models for Co-Design in Industry 4.0}, url = {https://link.springer.com/10.1007/978-3-031-68275-9_41}, venue = {University of Kassel, Germany}, year = 2024 }
9. Skoury, L., & Wortmann, T. (2024). Bridging the Gap between Design and Fabrication: Prediction Models for Co-Design in the Era of Industry 4.0. In P. Eversmann, C. Gengnagel, J. Lienhard, M. Ramsgaard Thomsen, & J. Wurm (Eds.), Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024) (pp. 507–519). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-68275-9_41
  - BibTeX
  BibTeX
  @conference{skoury2024bridging, abstract = {In the realm of Industry 4.0, significant changes have unfolded across various sectors, notably in construction, driven by the adoption of digitisation and automation. This transformation demands a reassessment of traditional practices within the Architectural, Engineering, and Construction (AEC) industry. In response, the concept of Co-Design has emerged, offering a promising avenue to integrate diverse expertise and stakeholders throughout the construction process. This study explores the fusion of Co-Design principles with ML techniques to elevate fabrication processes and project outcomes within the AEC industry. The research introduces a workflow that intertwines design, fabrication, and data analysis by implementing a fabrication prediction ML model. By harnessing real-world data from timber additive construction processes, the model is trained to predict task durations accurately. This not only tackles the inherent complexities of fabrication processes but also provides flexibility across different design scenarios and fabrication environments. Through systematic evaluation and testing, the study identifies the most effective ML algorithms for predicting fabrication times. Furthermore, it showcases the practical application of the prediction model in optimising fabrication setups, ultimately resulting in tangible enhancements in efficiency and productivity.}, author = {Skoury, Lior and Wortmann, Thomas}, booktitle = {Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024)}, doi = {10.1007/978-3-031-68275-9_41}, editor = {Eversmann, Philipp and Gengnagel, Christoph and Lienhard, Julian and Ramsgaard Thomsen, Mette and Wurm, Jan}, eventdate = {16. — 18. September 2024}, eventtitle = {DESIGN MODELLING SYMPOSIUM KASSEL 2024 – SCALABLE DISRUPTORS}, isbn = {978-3-031-68274-2 978-3-031-68275-9}, pages = {507-519}, publisher = {Springer Nature Switzerland}, title = {Bridging the Gap between Design and Fabrication: Prediction Models for Co-Design in the Era of Industry 4.0}, url = {https://link.springer.com/10.1007/978-3-031-68275-9_41}, venue = {University of Kassel, Germany}, year = 2024 }
2023
1. Amtsberg, F., Yang, X., Skoury, L., Ron, G., Kaiser, B., Calepso, A. S., Sedlmair, M., Verl, A., Wortmann, T., & Menges, A. (2023). Multi-Akteur-Fabrikation im Bauwesen. Bautechnik, 100, Article 10. https://doi.org/10.1002/bate.202300070
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  @article{Amtsberg_2023, author = {Amtsberg, Felix and Yang, Xiliu and Skoury, Lior and Ron, Gili and Kaiser, Benjamin and Calepso, Aim{\'{e}}e Sousa and Sedlmair, Michael and Verl, Alexander and Wortmann, Thomas and Menges, Achim}, doi = {10.1002/bate.202300070}, journal = {Bautechnik}, month = {09}, number = 10, pages = {637--647}, publisher = {Wiley}, title = {Multi-Akteur-Fabrikation im Bauwesen}, url = {https://doi.org/10.1002%2Fbate.202300070}, volume = 100, year = 2023 }
2. Gazzarri, L., & Herschel, M. (2023). Progressive Entity Resolution over Incremental Data. In J. Stoyanovich, J. Teubner, N. Mamoulis, E. Pitoura, & J. Mühlig (Eds.), Proceedings 26th International Conference on Extending Database Technology, EDBT 2023, Ioannina, Greece, March 28-31, 2023 (pp. 80–91). OpenProceedings.org. https://doi.org/10.48786/edbt.2023.07
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  @inproceedings{DBLP:conf/edbt/GazzarriH23, author = {Gazzarri, Leonardo and Herschel, Melanie}, bibsource = {dblp computer science bibliography, https://dblp.org}, booktitle = {Proceedings 26th International Conference on Extending Database Technology, {EDBT} 2023, Ioannina, Greece, March 28-31, 2023}, doi = {10.48786/edbt.2023.07}, editor = {Stoyanovich, Julia and Teubner, Jens and Mamoulis, Nikos and Pitoura, Evaggelia and M{\"{u}}hlig, Jan}, pages = {80--91}, publisher = {OpenProceedings.org}, title = {Progressive Entity Resolution over Incremental Data}, url = {https://doi.org/10.48786/edbt.2023.07}, year = 2023 }
3. Lässig, N. (2023). Towards an AutoML System for Fair Classifications. International Conference on Data Engineering (ICDE), 3913–3917. https://doi.org/10.1109/ICDE55515.2023.00380
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  BibTeX
  @inproceedings{DBLP:conf/icde/Lassig23, author = {Lässig, Nico}, booktitle = {International Conference on Data Engineering (ICDE)}, doi = {10.1109/ICDE55515.2023.00380}, pages = {3913--3917}, publisher = {IEEE}, title = {Towards an AutoML System for Fair Classifications}, url = {https://doi.org/10.1109/ICDE55515.2023.00380}, year = 2023 }
4. Sherkat, S., Skoury, L., Wortmann, A., & Wortmann, T. (2023). Artificial Intelligence Automated Task Planning for Fabrication. In K. Dörfler, J. Knippers, A. Menges, S. Parascho, H. Pottmann, & T. Wortmann (Eds.), Advances in Architectural Geometry 2023 (pp. 249–260). De Gruyter. https://doi.org/doi:10.1515/9783111162683-019
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  @inbook{SherkatSkouryWortmannWortmann+2023+249+260, address = {Berlin, Boston}, author = {Sherkat, Shermin and Skoury, Lior and Wortmann, Andreas and Wortmann, Thomas}, booktitle = {Advances in Architectural Geometry 2023}, doi = {doi:10.1515/9783111162683-019}, editor = {Dörfler, Kathrin and Knippers, Jan and Menges, Achim and Parascho, Stefana and Pottmann, Helmut and Wortmann, Thomas}, isbn = {9783111162683}, pages = {249--260}, publisher = {De Gruyter}, title = {Artificial Intelligence Automated Task Planning for Fabrication}, url = {https://doi.org/10.1515/9783111162683-019}, year = 2023 }
2022
1. Lässig, N., Herschel, M., Reichle, A., Ellwein, C., & Verl, A. (2022). The ArchIBALD Data Integration Platform: Bridging Fragmented Processes in the Building Industry. In J. D. Weerdt & A. Polyvyanyy (Eds.), Intelligent Information Systems - CAiSE Forum 2022 (Vol. 452, pp. 45–54). Springer. https://doi.org/10.1007/978-3-031-07481-3_6
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  @inproceedings{DBLP:conf/caise/LassigHREV22, author = {Lässig, Nico and Herschel, Melanie and Reichle, Alexander and Ellwein, Carsten and Verl, Alexander}, bibsource = {dblp computer science bibliography, https://dblp.org}, booktitle = {Intelligent Information Systems - CAiSE Forum 2022}, doi = {10.1007/978-3-031-07481-3_6}, editor = {Weerdt, Jochen De and Polyvyanyy, Artem}, eventdate = {June 6-10, 2022}, pages = {45--54}, publisher = {Springer}, series = {Lecture Notes in Business Information Processing}, title = {The ArchIBALD Data Integration Platform: Bridging Fragmented Processes in the Building Industry}, url = {https://doi.org/10.1007/978-3-031-07481-3_6}, venue = {Leuven, Belgium}, volume = 452, year = 2022 }
2. Lässig, N., Oppold, S., & Herschel, M. (2022). Metrics and Algorithms for Locally Fair and Accurate Classifications using Ensembles. Datenbank-Spektrum, 22, Article 1. https://doi.org/10.1007/s13222-021-00401-y
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  @article{lassig2022metrics, author = {Lässig, Nico and Oppold, Sarah and Herschel, Melanie}, doi = {10.1007/s13222-021-00401-y}, journal = {Datenbank-Spektrum}, number = 1, pages = {23 - 43}, refid = {Lässig2022}, title = {Metrics and Algorithms for Locally Fair and Accurate Classifications using Ensembles}, url = {https://doi.org/10.1007/s13222-021-00401-y}, volume = 22, year = 2022 }
3. Skoury, L., Amtsberg, F., Yang, X., Wagner, H. J., Menges, A., & Wortmann, T. (2022). A Framework for Managing Data in Multi-actor Fabrication Processes. In C. Gengnagel, O. Baverel, G. Betti, M. Popescu, M. R. Thomsen, & J. Wurm (Eds.), Towards Radical Regeneration (pp. 601–615). Springer International Publishing. https://doi.org/10.1007/978-3-031-13249-0_47
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  @conference{skoury2022framework, abstract = {This research proposes a design to fabrication data framework for multi-actor fabrication environments with robotic and human actors. The framework generates and exchanges fabrication data between the design elements and the fabrication environment. It features a uniform task data model to represent all processes in the fabrication procedure and link them to the design elements. The framework is demonstrated with a timber slab case study that shows the fabrication data generation, assignment to actors and ordering for execution with a multi-actor fabrication environment involving industrial robots and human workers. This framework opens new opportunities for continuous digital data exchange and feedback between the design and fabrication and allows for rapid changes in both the fabrication environment and the design.}, author = {Skoury, Lior and Amtsberg, Felix and Yang, Xiliu and Wagner, Hans Jakob and Menges, Achim and Wortmann, Thomas}, booktitle = {Towards Radical Regeneration}, doi = {10.1007/978-3-031-13249-0_47}, editor = {Gengnagel, Christoph and Baverel, Olivier and Betti, Giovanni and Popescu, Mariana and Thomsen, Mette Ramsgaard and Wurm, Jan}, eventdate = {09/2022}, eventtitle = {Design Modelling Symposium}, isbn = {978-3-031-13248-3 978-3-031-13249-0}, language = {en}, pages = {601-615}, publisher = {Springer International Publishing}, title = {A Framework for Managing Data in Multi-actor Fabrication Processes}, url = {https://link.springer.com/10.1007/978-3-031-13249-0_47}, venue = {Berlin}, year = 2022 }
4. Wortmann, T., Herschel, M., Staab, S., & Tarín, C. (2022). AI for AEC: KI für Bauplanung und Bau. Bautechnik, 99, Article 10. https://doi.org/10.1002/bate.202200070
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  @article{wortmann2022bauplanung, author = {Wortmann, Thomas and Herschel, Melanie and Staab, Steffen and Tarín, Cristina}, doi = {https://doi.org/10.1002/bate.202200070}, journal = {Bautechnik}, number = 10, title = {AI for AEC: KI für Bauplanung und Bau}, volume = 99, year = 2022 }
2021
1. Diestelkamper, R., Lee, S., Glavic, B., & Herschel, M. (2021). Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb. Proceedings of the VLDB Endowment (PVLDB). https://doi.org/10.14778/3476311.3476331
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  @article{diestelkamper2021debugging, author = {Diestelkamper, Ralf and Lee, Seokki and Glavic, Boris and Herschel, Melanie}, doi = {10.14778/3476311.3476331}, journal = {Proceedings of the VLDB Endowment (PVLDB)}, title = {Debugging Missing Answers for Spark Queries over Nested Data with Breadcrumb}, year = 2021 }
2. 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
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  @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 }
3. Gazzarri, L., & Herschel, M. (2021). End-to-end Task Based Parallelization for Entity Resolution on Dynamic Data. Proceedings of the IEEE International Conference on Data Engineering (ICDE).
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  @inproceedings{gazzarri2021endtoend, author = {Gazzarri, Leonardo and Herschel, Melanie}, booktitle = {Proceedings of the IEEE International Conference on Data Engineering (ICDE)}, title = {End-to-end Task Based Parallelization for Entity Resolution on Dynamic Data}, year = 2021 }
4. Lässig, N., Oppold, S., & Herschel, M. (2021). Using FALCES against bias in automated decisions by integrating fairness in dynamic model ensembles. In Proceedings of Database Systems for Business, Technology, and Web (BTW).
  - BibTeX
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  @inproceedings{lssig2021using, author = {Lässig, Nico and Oppold, Sarah and Herschel, Melanie}, booktitle = {In Proceedings of Database Systems for Business, Technology, and Web (BTW)}, title = {Using FALCES against bias in automated decisions by integrating fairness in dynamic model ensembles}, year = 2021 }
2019
1. Diestelkämper, R., & Herschel, M. (2019). Capturing and Querying Structural Provenance in Spark with Pebble. In ACM International Conference on Management of Data (SIGMOD), 1893–1896. https://doi.org/10.1145/3299869.3320225
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  @inproceedings{diestelkmper2019capturing, author = {Diestelkämper, Ralf and Herschel, Melanie}, booktitle = {In ACM International Conference on Management of Data (SIGMOD)}, ee = {https://doi.org/10.1145/3299869.3320225}, isbn = {978-1-4503-5643-5}, pages = {1893-1896}, title = {Capturing and Querying Structural Provenance in Spark with Pebble}, url = {https://doi.org/10.1145/3299869.3320225}, year = 2019 }

DATA SETS

2024
1. Skoury, L., & Wortmann, T. (2024). Multi-protocol Messaging and Streaming Broker for Grasshopper (RabbitMQ_GH) [DaRUS]. https://doi.org/10.18419/darus-4193
  - BibTeX
  BibTeX
  @dataset{darus-4193_2024, abstract = {RabbitMQ GH is a Grasshopper plugin for implementing RabbitMQ messaging capabilities to exchange data between external applications and Grasshopper scripts in real time, with a high degree of flexibility and scalability. INSTALLATION Erlang installation Download the current Erlang version installer and follow the default setup in the installation wizard. Add Erlang to the Environment variables. To do it, go to Control Panel>System and Security>System. A new window will open. Click on Advanced system settings under the Device specifications collapsable panel. When the System Properties window appears, click on the Environment Variables button at the bottom of the Advanced tab. On the User variables section use the New... button to add a new variable with ERLANG\_HOME as the Variable name and the installation path as the variable value (By default the installation path should be C:\textbackslashProgram Files\textbackslashErlang OTP). To verify that the variable was correctly added, open a command prompt and enter the ECHO \%ERLANG\_HOME\% command. If the installation path is printed on the screen, the variable is correctly added. RabbitMQ installation On RabbitMQ´s GitHub page go to the Releases section on the right-hand side of the window. Click on the latest release and navigate to the assets section and download the rabbitmq-server-windows-.zip file, where corresponds to the latest release version number. Extract the compressed files to the directory where you want RabbitMQ to be stored. To run RabbitMQ, open a terminal window and go to the installation directory. Once there, run the rabbitmq-server.bat command. The current Erlang version and the plugins being used should be printed on the screen. In Windows, RabbitMQ does not run on startup by default. To change that, the Startup type of the RabbitMQ Server must be set to Automatic If the plugins are not working properly, follow the same procedure described in the following section to activate them. Management plugin activation To activate the management plugin, open a terminal window and go to the installation directory. After that, run the rabbitmq-plugins enable rabbitmq\_management command. This should enable the plugin and it should be working the next time RabbitMQ is launched. The same command works for activating other plugins by replacing rabbitmq\_management with the plugin's name after it has been downloaded into the plugin's directory located on RabbitMQ's installation directory. For further information, follow this link. Grasshopper plugin installation Copy the folder Installation\_Files/Rabbit\_MQ\_GH into your Grasshopper component folder. If you don´t know the location of this folder on your computer, you can find it using Grasshopper's interface. Go to File>Special Folders>Components Folder and a file explorer window will open in the correct directory. In general, downloaded .gha files can be blocked by Windows OS, so verify that all the downloaded files are unblocked. To do so, find each file in the file explorer and right-click on it. In the context menu select Properties. This will open a new window. Go to the lower part of the general tab and check the checkbox labeled Unblock. For the use of the plugin, even after closing the .gh files, the connections created in the session will remain open if the Run toggle is set to True. To prevent this, make sure to set the toggle to False before closing the file. Additional resources Linux machine deployment AWS deployment MANAGEMENT PLUGIN To open the management plugin, in your web browser navigate to localhost:15672 If no credentials have been established, use guest as the default username and password to log in. USE PATTERNS Example files covering several use patterns for Grasshopper, Python, and C\# are located in the folder Tutorial/Examples/. Most of them build on top of the consumer-producer pattern. It has two main components: A producer that sends messages to a RabbitMQ queue and a consumer that receives the messages from the queue and processes them. These are all the patterns covered in the example files with a detailed explanation in Tutorial/Examples/readme.md: Basic consumer Competing consumers Publisher-subscriber Request-reply Basic routing Topic routing.}, author = {Skoury, Lior and Wortmann, Thomas}, doi = {10.18419/darus-4193}, publisher = {DaRUS}, title = {Multi-protocol Messaging and Streaming Broker for Grasshopper (RabbitMQ_GH)}, url = {https://doi.org/10.18419/darus-4193}, version = {V1}, year = 2024 }
2. Skoury, L., & Wortmann, T. (2024). livMats Biomimetic Shell Fabrication Tasks [DaRUS]. https://doi.org/10.18419/darus-3648
  - BibTeX
  BibTeX
  @dataset{darus-3648_2024, author = {Skoury, Lior and Wortmann, Thomas}, doi = {10.18419/darus-3648}, publisher = {DaRUS}, title = {livMats Biomimetic Shell Fabrication Tasks}, url = {https://doi.org/10.18419/darus-3648}, version = {V1}, year = 2024 }

Prof. Dr.-Ing. Cristina Tarín Sauer

Participating Researcher

Phone: +49 711 685 83253

E-Mail

Prof. Dr. Melanie Herschel

Principal Investigator

Phone: +49 711 685 88444

E-Mail

Tenure-Track Prof. Dr. Thomas Wortmann

Cluster Professor

Phone: +49 711 685 81933

E-Mail

Data Processing and AI for Predictive, Adaptive Co-Design

DATA PROCESSING AND AI FOR PREDICTIVE AND ADAPTIVE CO-DESIGN IN PREFABRICATION AND ON-SITE CONSTRUCTION

PRINCIPAL INVESTIGATORS

TEAM

PEER-REVIEWED PUBLICATIONS

2024

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2023

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2022

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2021

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2019

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DATA SETS

2024

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Prof. Dr.-Ing. Cristina Tarín Sauer

Prof. Dr. Melanie Herschel

Tenure-Track Prof. Dr. Thomas Wortmann

Cluster of Excellence IntCDC

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