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The construction industry faces significant challenges, including labor shortages and the demand for sustainable, efficient building methods. Prefabrication in timber construction offers a solution, but many companies struggle with integrating more advanced and efficient technologies into their workflows. This study presents a cyber-physical system for batch size one timber element production, integrating robotics, artificial intelligence, and digital twin technology. A six-axis articulated robot performs vertical wall panel cladding, leveraging AI-driven CAD analysis for optimized gripping positions and process reliability. The system employs deep learning-based feature recognition for enhanced process reliability and a Unity-simulated digital robot twin for precise path planning. A custom gripper and automated material supply ensure high position precision of the production materials. Combining AI, robotics, and Industry 5.0 principles enhances efficiency and sustainability in timber construction, addressing key industry challenges and paving the way for fully integrated, intelligent manufacturing workflows.

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Efficient Timber Construction: Application of Cyber-Physical Systems for Batch Size One Manufacturing

  • 会议论文

  • 发表日期：

    2026年

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  • Stefan Andreas Böhm,
  • Daniel Schulz,
  • Sebastian Bitzan,
  • Lucas Heider,
  • Lars Jonas,
  • Niklas Leinz,
  • Fabian Riß,
  • Alois Knoll

摘要

The construction industry faces significant challenges, including labor shortages and the demand for sustainable, efficient building methods. Prefabrication in timber construction offers a solution, but many companies struggle with integrating more advanced and efficient technologies into their workflows. This study presents a cyber-physical system for batch size one timber element production, integrating robotics, artificial intelligence, and digital twin technology. A six-axis articulated robot performs vertical wall panel cladding, leveraging AI-driven CAD analysis for optimized gripping positions and process reliability. The system employs deep learning-based feature recognition for enhanced process reliability and a Unity-simulated digital robot twin for precise path planning. A custom gripper and automated material supply ensure high position precision of the production materials. Combining AI, robotics, and Industry 5.0 principles enhances efficiency and sustainability in timber construction, addressing key industry challenges and paving the way for fully integrated, intelligent manufacturing workflows.