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Slice Thickness

by Botao Zhang last modified 2015-03-05 15:22

  • A K-D Tree Based Clustered Adaptive Layering Approach to Improve Part Accuracy by Varying Slice Thickness
  • A new approach of determining the variable slices using a 3D k-d tree method has been proposed in this research. The proposed approach is validated for three test parts and by comparing the volumetric, cylindricity, sphericity, and profile errors obtained from this approach with those obtained using a uniform slicing method.
    Since current AM machines are incapable of handling adaptive slicing approach directly, a “pseudo” grouped adaptive layering approach is also proposed here. This “clustered slicing” technique will enable the fabrication of a part in bands of varying slice thicknesses with each band having clusters of uniform slice thicknesses.

    Figure: K-D Tree based Adaptive Slicing and Slice Thickness based Clustering of Slices

  • Adaptive Slicing in Additive Manufacturing Process Using a Modified Boundary Octree Data Structure (MBODS)
  • This method, termed as modified boundary octree data structure (MBODS) algorithm, is used to convert the stereolithography (STL) file of an object to an octree data structure based on the part’s geometry, the machine parameters, and a user defined tolerance value.
    A subsequent algorithm computes the variable slice thicknesses using the MBODS representation of the part and virtually manufactures the part using these calculated slice thicknesses. Points sampled from the virtually manufactured part are inspected to evaluate the volumetric, profile, and cylindricity part errors

    Figure: Part Representation by MBODS

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