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Geometric Fidelity of Interlocking Bodies in Two-Component Robotic Additive Manufacturing (2024-09)

10.1007/978-3-031-70031-6_16

 Daneshvar Dana,  Rabiei Mahsa,  Gupta Shashank,  Najmeddine Aimane,  Prihar Arjun,  Moini Mohamadreza
Contribution - Proceedings of the 4th RILEM International Conference on Concrete and Digital Fabrication, pp. 134-141

Abstract

Interlocking mechanisms enable modular designs of structures and offer additional energy absorption capacities. These types of designs with often complex toolpaths can benefit from the utilization of digital fabrication techniques. Two-component (2-K) concrete robotic additive manufacturing (AM) provides an enhanced ability to achieve geometrically complex designs. However, tailored designs enabled by robotic AM techniques require a customized toolpath, involving both rectilinear and curvilinear trajectories. Thus, development of assessment methods and reliable benchmarks is crucial. Here, two interlocking mechanisms, namely suture and dovetail have been introduced to assess the geometric accuracy (error) of individual and pairwise interlocking bodies. The impacts of non-linearity in toolpath trajectory (i.e., rectilinear vs. curvilinear) on geometric accuracies were examined for a range of geometric features (wide/narrow neck, length, and width), toolpath design (spiral, and zigzag) and printing speeds. A Grasshopper algorithm was developed to generate the toolpath trajectories for the ABB industrial robot (in RAPID commands). A 2-K robotic AM process with accelerated hydration was used to fabricate the proposed interlocking benchmarks. Image analysis results show that toolpath trajectory remarkably alters the geometric accuracy given the higher error observed in the curvilinear cases compared to the rectilinear counterparts in both individual and pairwise bodies. Additionally, decreasing printing speed leads to exacerbating effect on error of the individual and pairwise benchmarks. The findings provide initial insight that a calibration of extrusion flow rate is necessary in curvilinear segments of the toolpath in design of complex components such as modular elements. This approach can be used to improve the efficiency of large-scale additive manufacturing in an accuracy-critical context such as modular 3D-printed structures that otherwise may need downstream subtractive manufacturing process.

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2 Citations

  1. Lopes de Aquino Brasil Alexander, Carmo Pena (2025-09)
    A Systematic Review of Robotic Additive Manufacturing Applications in Architecture, Engineering, and Construction
  2. Rabiei Mahsa, Moini Mohamadreza (2025-09)
    Extrusion Under Material Uncertainty with Pressure-Based Closed-Loop Feedback Control in Robotic Concrete Additive Manufacturing

BibTeX
@inproceedings{dane_rabi_gupt_najm.2024.GFoIBiTCRAM,
  author            = "Dana Daneshvar and Mahsa Rabiei and Shashank Gupta and Aimane Najmeddine and Arjun Prihar and Mohamadreza Moini",
  title             = "Geometric Fidelity of Interlocking Bodies in Two-Component Robotic Additive Manufacturing",
  doi               = "10.1007/978-3-031-70031-6_16",
  year              = "2024",
  volume            = "53",
  pages             = "134--141",
  booktitle         = "Proceedings of the 4th RILEM International Conference on Concrete and Digital Fabrication",
  editor            = "Dirk Lowke and Niklas Freund and David Böhler and Friedrich Herding",
}
Formatted Citation

D. Daneshvar, M. Rabiei, S. Gupta, A. Najmeddine, A. Prihar and M. Moini, “Geometric Fidelity of Interlocking Bodies in Two-Component Robotic Additive Manufacturing”, in Proceedings of the 4th RILEM International Conference on Concrete and Digital Fabrication, 2024, vol. 53, pp. 134–141. doi: 10.1007/978-3-031-70031-6_16.

Daneshvar, Dana, Mahsa Rabiei, Shashank Gupta, Aimane Najmeddine, Arjun Prihar, and Mohamadreza Moini. “Geometric Fidelity of Interlocking Bodies in Two-Component Robotic Additive Manufacturing”. In Proceedings of the 4th RILEM International Conference on Concrete and Digital Fabrication, edited by Dirk Lowke, Niklas Freund, David Böhler, and Friedrich Herding, 53:134–41, 2024. https://doi.org/10.1007/978-3-031-70031-6_16.