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Voxel-based sensor placement for additive manufacturing applications

Author

Listed:
  • Nuwan Munasinghe

    (University of Technology Sydney)

  • Thomas Romeijn

    (University of Technology Sydney)

  • Gavin Paul

    (University of Technology Sydney)

Abstract

The manufacturing sector is experiencing a transformation to Industry 4.0. The authors are researching 3D printable sensors to measure operating conditions like wear, strain and temperature, as part of a project to develop a large-scale multi-material extrusion 3D printer to print a Gravity Separation Spiral—a piece of mining equipment that separates minerals from slurry. This paper proposes a sensor placement methodology for placing embedded sensors in large 3D printed objects. Voxels, the 3D equivalent of 2D pixels, are used to discretise the object and an optimisation routine optimally positions the 3D printable sensors into a 3D printed object. The optimisation objectives that are used during sensor placement include the information gain from the sensor, the ability to print the sensor using a robot, and the ability to discourage sensors being placed in important structural locations by penalising these voxels. Finite element analysis is employed to measure the information gain, while the robot arm’s manipulability measures the capability to print at each voxel location. The objectives are integrated using 3D kernels, which are represented by voxels shaped in the size of the sensor and different weights related to the intricate traces that need to be printed. Using a weighted objective function the best locations are chosen. A simulation environment has been developed to simulate the printing and Matlab is used to do the voxel-based calculations to identify the ideal location for sensor placement.

Suggested Citation

  • Nuwan Munasinghe & Thomas Romeijn & Gavin Paul, 2023. "Voxel-based sensor placement for additive manufacturing applications," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 739-751, February.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:2:d:10.1007_s10845-021-01823-x
    DOI: 10.1007/s10845-021-01823-x
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    References listed on IDEAS

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    1. Behzadian, Majid & Kazemzadeh, R.B. & Albadvi, A. & Aghdasi, M., 2010. "PROMETHEE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 200(1), pages 198-215, January.
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