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Technical Workshop | TUM Germany & ETH Zürich

Dr. Li was invited to give a technical workshop on the “Collaborative intelligence in industrialized construction” at the Technical University of Munich April 15 2024, and at ETH Zürich on 16 April 2024.

Our proposed research focuses on advancing mass customization methodologies (MCM) for high-rise modular buildings (HMB) through innovative technologies and applications. The project aims to achieve three primary objectives: (1) creating a mass customization (MC) model and calibration framework for HMB, (2) establishing an MCM with novelties in adaptive platforms, interactive configurators, and decentralized processes, and (3) developing and validating practical solutions for MCM in different HMB projects. To further these objectives, our team recently traveled to Europe, where we participated in significant events related to our research.

On April 15, at the Technical University of Munich, Dr. Li and his team convened for a joint project meeting with our German counterparts. This meeting facilitated discussions on intelligent design, BIM interaction, and construction robotics aimed at enabling mass customization of HMB. Additionally, we engaged in a LOC Talk focused on "Neuro-Symbolic Artificial Intelligence in AEC," exploring its potential applications in our field.

Subsequently, at ETH Zurich, we participated in a technical workshop organized by the National Centre of Competence in Research (NCCR) Digital Fabrication. Here, Dr.  Li presented on "Collaborative Intelligence in Industrialized Construction," showcasing our research's breadth. Our team members, Mr. Ruiqi Jiang and Mr. Yinyi Wei, presented their recent advancements in robotic arm kinematics and natural language interfaces for BIM data management. These interactions with international experts in robotics, digital fabrication, and human-computer interaction directly contributed to refining our theoretical model and exploring potential solutions for adaptive platforms and interactive configurators within our proposed mass customization methodology.

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