Work

Enhanced robotic cross-laminated timber panel assembly process

Year: 2025

Type: article

Abstract: The use of Cross-Laminated Timber (CLT) panels in construction is often constrained by their weight, making handling and installation challenging. These limitations frequently result in on-site planning and manual assembly, increasing risks and inefficiencies. This study proposes an integrated framework that combines Building Information Modeling (BIM), discrete event simulation, and robotic assembly to optimize the installation of CLT structures within the built environment. By leveraging these technologies, the methodology addresses material handling challenges while enhancing construction efficiency and adaptability to urban and prefabricated settings. Numerical simulations and robotic assembly experimental tests were conducted to evaluate the framework’s performance. Results demonstrate an improvement in assembly efficiency, reducing both accident risks and installation time compared to manual methods. Strong agreement between numerical and experimental findings underscores the potential of computational tools in advancing automated construction practices. This research provides actionable recommendations to promote the broader adoption of automated processes in CLT construction, contributing to safer, more efficient, and sustainable building practices within the evolving built environment. • Develops a novel framework for the robotic assembly of CLT panels to enhance efficiency in modern construction. • Conducts discrete event simulations (DES) to optimize robotic workflows in CLT panel assembly within the built environment. • Performs experimental tests on robotic assembly of CLT panels, contributing to automation in off-site construction. • Proposes an integrated methodology for BIM and DES to streamline robotic programming for CLT panel fabrication. • Demonstrates improved CLT panel assembly processes, reducing accident risks and assembly time in timber construction.

Source: Developments in the Built Environment

DOI: 10.1016/j.dibe.2025.100667