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Chapter Fourteen - Rapid alloying in additive manufacturing using integrated computational materials engineering

Fast facts

  • Further publishers

    • Farzad Foadian
    • Robert Kremer
    • Somayeh Khani
  • Publishment

    • 2023
  • Anthology

    Quality Analysis of Additively Manufactured Metals

  • Organizational unit

  • Subjects

    • Mechanical engineering in general
    • Materials engineering
  • Publication format

    Anthology contribution (Other document type)

Quote

Foadian, Farzad, Kremer, Robert & Khani, Somayeh 2023. Chapter Fourteen - Rapid alloying in additive manufacturing using integrated computational materials engineering. In Quality Analysis of Additively Manufactured Metals. Amsterdam [et al]: Elsevier, 583-624.

Content

Thanks to metals Additive Manufacturing (AM) in recent decades, a shift has been created in how metal components are manufactured. Using AM processes, materials and parts could be fabricated simultaneously using only a single machine. Almost no-limit design is possible and local properties of materials such as microstructure property relationships may be realized through regional process variations. Although many scientists and engineers who worked and are working on AM and their efforts have resulted in the commercialization of metals AM technologies, the consistency and quality of parts and materials are still open challenges for many applications. Integrated Computational Materials Engineering (ICME) could help us understand the materials' behavior during the AM and accelerate the development and adoption of materials technologies for AM of metals. This chapter briefly reviews the alloy design using ICME in AM. It shows how ICME and AM combination could support us to organize and increase the efficiency of alloy development and adaption with a specific focus on the appropriate AM technique. Establishing a quantitative ICME linkage is essential to unfold the full potential of metal AM. It will help understand the underlying physics and provide a powerful and effective tool for optimal computational design. The review concludes with a case study on ICME to optimize a manufacturing process.

Keywords

ICME

PBF

SLM

Notes and references

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