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Additive Manufacturing of Functionally Graded Ceramic Materials by Stereolithography
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Automated Process Planning for Embossing and Functionally Grading Materials via Site-Specific Control in Large-Format

Michael Borish1, Brian T Gibson1, Cameron Adkins1

  • 1Oak Ridge National Laboratory, Knoxville, TN 37932, USA.

Materials (Basel, Switzerland)
|June 24, 2022
PubMed
Summary
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This study introduces automated process planning software for additive manufacturing (AM), enabling precise control over material properties throughout printed objects. This advancement facilitates site-specific parameter adjustments for enhanced component functionality.

Area of Science:

  • Materials Science and Engineering
  • Manufacturing Technology
  • Computational Engineering

Background:

  • Additive Manufacturing (AM) offers site-specific control, but process planning remains a bottleneck.
  • Interest in functionally graded materials via AM is high, yet development is hindered by manual programming.
  • Current methods for site-specific control in AM often rely on bespoke solutions and manual programming.

Purpose of the Study:

  • To develop automated slicing software for through-thickness, process-parameter control in additive manufacturing.
  • To overcome limitations in process planning for site-specific material property control in AM.
  • To enable advanced material grading and structural modifications in AM components.

Main Methods:

  • Development of slicing software with a fully automated process planning approach.
Keywords:
additive manufacturingembossinglarge-format DEDslicing

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  • Utilizing parent and child geometries for defining locations of site-specific parameters.
  • Implementing a vector-based planning approach, assigning information like melt pool size to toolpath vectors.

    • Main Results:

    • Demonstrated a proof-of-principle experiment generating dynamic bead geometries for a novel surface embossing effect.
    • Successfully enabled through-thickness, process-parameter control for various AM processes.
    • Showcased software support for complex object geometries and macro/micro-structural modifications.

    Conclusions:

    • The developed software provides a fully automated process planning solution for site-specific parameter control in AM.
    • This technique allows for precise control over material properties and structural modifications, advancing functionally graded materials.
    • The vector-based approach with parent/child geometries offers a versatile platform for complex AM applications.