Target-path planning and manufacturability check for robotic CLT machining operations from BIM information

Emanuel Martinez Villanueva, Pablo Rodriguez, Rafiq Ahmad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Mass timber is one of the trending construction styles in the last years thanks to its sustainability and offsite manufacturing properties, where cross laminated timber (CLT) is the most common material used. In an effort to link design and manufacturing information in a single location, this study proposes a generative process planning algorithm for CLT machining in robotic environments. The algorithm focuses on automatic feature-based interpretation of the geometry of CLT panels to obtain the targets required to guide the robots for its machining. The method developed detects primitives geometries of the CLT panels, determines the appropriate operations (either sawing, drilling, or milling), select the robot based on manufacturing capabilities (reach and tool availability), and generates the target-path planning for its machining process. The proposed method is tested in a robotic machining station for CLT panels simulated in RobotStudio® as a case study. The results showcase the capabilities of the proposed algorithm to provide manufacturing results out of the process planning process from geometric information available at the design stage. These results include process duration, path planning, resource allocation and utilization. This study provides a framework to include manufacturing information in design decisions to facilitate planning or cost estimations and anticipate issues downstream generated during the design phase.
Original languageEnglish
Article number105191
Number of pages16
JournalAutomation in Construction
Volume158
Early online date14 Nov 2023
DOIs
Publication statusPublished - 1 Feb 2024

Keywords

  • Construction
  • Offsite construction
  • Robot path planning
  • Robotic machining
  • CLT machining
  • Automated machining
  • Robotic milling

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