An Image-Based Transfer Learning Approach for Using <i>In Situ</i> Processing Data to Predict Laser Powder Bed Fusion Additively Manufactured Ti-6Al-4V Mechanical Properties-Reference-Cited by-同舟云学术

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An Image-Based Transfer Learning Approach for Using In Situ Processing Data to Predict Laser Powder Bed Fusion Additively Manufactured Ti-6Al-4V Mechanical Properties

Published:2024-02-12 Issue: Volume: Page:
ISSN:2329-7662
Container-title:3D Printing and Additive Manufacturing
language:en
Short-container-title:3D Printing and Additive Manufacturing

Author:

Luo Qixiang¹,Shimanek John D.¹,Simpson Timothy W.²³,Beese Allison M.¹³^ORCID

Affiliation:

1. Department of Materials Science and Engineering, Pennsylvania State University, University Park, Pennsylvania, USA.

2. Department of Industrial and Manufacturing Engineering, Pennsylvania State University, University Park, Pennsylvania, USA.

3. Department of Mechanical Engineering, Pennsylvania State University, University Park, Pennsylvania, USA.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/3dp.2023.0186

Reference41 articles.

1. Additive manufacturing of metallic components – Process, structure and properties

2. Additive manufacturing of Ti6Al4V alloy: A review

3. Defect structure process maps for laser powder bed fusion additive manufacturing

4. Analysis of defect generation in Ti–6Al–4V parts made using powder bed fusion additive manufacturing processes

5. Instability of scan tracks of selective laser sintering of high speed steel powder

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