<p>This research develops a structured framework and an associated planning tool to design human–robot collaborative (HRC) processes for robotic building prefabrication. The proposed five-stage framework: Analysis, Preliminary Design, Detailed Design, Testing, and Implementation, can guide prefabrication designers without a robotics background to systematically identify tasks, allocate responsibilities between humans and robots, simulate collaborative workflows, and validate safety and performance. A web-based design-assisting tool stepwise operationalizes the framework, integrating decision models, discrete-event simulation, and human–robot interaction analysis within a unified interface. The practical implementation of the framework was demonstrated in a timber wall panel fabrication process. The iterative design and testing cycles of the framework improved the overall process by 34% in the first iteration and 13% in the second, validating both productivity gains and process adaptability. The framework and the tool provide a practical method for engineers, particularly those without robotics expertise, to plan, test, and refine HRC processes, enabling safer and more efficient robotic prefabrication processes.</p>

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Development of a human–robot collaborative process design framework and an associated planning tool for robotic building prefabrication

  • Liang-Ting Tsai,
  • Cheng-Hsuan Yang,
  • Yuxiang Chen,
  • Ying Hei Chui

摘要

This research develops a structured framework and an associated planning tool to design human–robot collaborative (HRC) processes for robotic building prefabrication. The proposed five-stage framework: Analysis, Preliminary Design, Detailed Design, Testing, and Implementation, can guide prefabrication designers without a robotics background to systematically identify tasks, allocate responsibilities between humans and robots, simulate collaborative workflows, and validate safety and performance. A web-based design-assisting tool stepwise operationalizes the framework, integrating decision models, discrete-event simulation, and human–robot interaction analysis within a unified interface. The practical implementation of the framework was demonstrated in a timber wall panel fabrication process. The iterative design and testing cycles of the framework improved the overall process by 34% in the first iteration and 13% in the second, validating both productivity gains and process adaptability. The framework and the tool provide a practical method for engineers, particularly those without robotics expertise, to plan, test, and refine HRC processes, enabling safer and more efficient robotic prefabrication processes.