@inproceedings{WiedererHoengEder, author = {Wiederer, Jonas and H{\"o}ng, Simon and Eder, Friedrich}, title = {Konzept zur KI-gest{\"u}tzten parametrischen Br{\"u}ckenmodellierung f{\"u}r ressourcen- und kostenoptimierte Bauwerksentw{\"u}rfe}, series = {Tagungsband 35. Forum Bauinformatik, 2024, Hamburg}, booktitle = {Tagungsband 35. Forum Bauinformatik, 2024, Hamburg}, editor = {St{\"u}hrenberg, Jan and Al-Zuriqat, Thamer and Chillon Geck, Carlos}, publisher = {Technische Universit{\"a}t Hamburg, Institut f{\"u}r Digitales und Autonomes Bauen}, address = {Hamburg}, doi = {10.15480/882.13506}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-77922}, pages = {50 -- 57}, abstract = {Br{\"u}ckenbauwerke stellen eine wesentliche Komponente einer soliden Infrastruktur dar. Wegen vernachl{\"a}ssigter Instandsetzungsmaßnahmen und sich ver{\"a}ndernder Anforderungen sind f{\"u}r eine Vielzahl dieser Bauwerke in Deutschland Ersatzneubauten notwendig. Diese Arbeit adressiert die Herausforderungen der Ressourcenverschwendung durch wiederholten Arbeitsaufwand bei individuellen Br{\"u}ckenentw{\"u}rfen f{\"u}r die angesprochenen Bauwerke. Es wird ein parametrisches Entwurfsmodells in Siemens NX entwickelt, um den Entwurfsprozess zu beschleunigen und eine einfache Anpassung an die entsprechenden Rahmenbedingungen zu erm{\"o}glichen. Zudem wird eine effektive Methode zur Anbindung an die Kostenermittlungssoftware RIB iTWO vorgestellt, die eine nachgelagerte Kostenkalkulation nach DIN 276 erm{\"o}glicht. Aufbauend darauf wird ein Optimierungsworkflow vorgestellt, welcher verschiedene Faktoren einbindet, um einen hochwertigen Bauwerksentwurf zu erzielen. Hierbei wird die Einbindung von Techniken aus dem Bereich der K{\"u}nstlichen Intelligenz angestrebt. Die vorgestellte Methodik soll die Wirtschaftlichkeitsbewertung und Entscheidungsfindung f{\"u}r die Realisierung der Br{\"u}ckenentw{\"u}rfe erleichtern und somit zu einer effizienteren Nutzung von Ressourcen im Br{\"u}ckenbau beitragen.}, language = {de} } @inproceedings{HoengWiedererEderetal., author = {H{\"o}ng, Simon K. and Wiederer, Jonas and Eder, Friedrich and Obergriesser, Mathias and Linner, Thomas}, title = {Towards AI-enhanced facade planning : integrating human expertise with machine learning-driven parametric modeling}, series = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, volume = {6}, booktitle = {EC³ \& CIB W78 : 2025 European Conference on Computing in Construction \& 42nd CIB W78 IT in Construction Conference}, publisher = {European Council for Computing in Construction}, isbn = {978-9-083451-31-2}, issn = {2684-1150}, doi = {10.35490/EC3.2025.320}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-84862}, pages = {192 -- 199}, abstract = {Planning modern facade systems is complex, requiring optimization across multiple domains.This paper proposes an AI-enhanced workflow for facade planning, harnessing computer vision and human input via a Large Language Model.A generative AI system then guides a parametric model to produce 3D facade designs. Automated checks provide feedback to a Reinforcement Learning system, to iteratively determine optimal solutions.These solutions are verified and finalized by human expertise, ensuring improved outcomes with reduce planning time and effort.The approach illustrates how combining advanced AI methods with human expertise can address the multifactorial challenges of facade design within current industry practices.}, language = {en} } @inproceedings{SaffertWiedererHoengetal., author = {Saffert, Anne-Sophie and Wiederer, Jonas and H{\"o}ng, Simon and Linner, Thomas and Obergrießer, Mathias and Neumann, Patrick}, title = {Towards AI-based optimization of human-centered and robot-assisted construction processes}, series = {Proceedings of the 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, Canada July 28-31, 2025}, booktitle = {Proceedings of the 42nd International Symposium on Automation and Robotics in Construction (ISARC), Montreal, Canada July 28-31, 2025}, publisher = {IAARC}, isbn = {978-0-6458322-2-8}, issn = {2413-5844}, doi = {10.22260/ISARC2025/0112}, pages = {861 -- 868}, abstract = {This research explores an innovative AI-driven approach to optimizing construction processes with a focus on humancentered design, addressing key challenges in the construction industry, such as skilled labor shortages and ergonomic risks associated withwork-related musculoskeletal disorders. By integrating process design with AI-based algorithms into simulation tools, various construction process layout variants including robot-assisted scenarios can be simulated and evaluated based on user-specific key performance indicators (e.g., ergonomic score, layouting parameters) to identify optimized solutions. A data processing algorithm automates the process, eliminating the need for manual simulation variations and resulting in increased operational productivity. The AI-based system evaluates and optimizes process layouts by adjusting control parameters. A case study on a brick laying process serves as an exemplary use case, highlighting the necessity and impact of adopting process optimization. The findings emphasize the transformative potential of automated process optimization within simulation environments to rethink existing construction practices, enhance worker well-being, and boost operational productivity.}, language = {en} }