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Khan FINAL 12 11 23 with cert.pdf (4.27 MB)

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Manufacturability Analysis of Laser Powder Bed Fusion using Machine Learning

Khan, Daniyal
http://orcid.org/0009-0003-4832-7870
http://rave.ohiolink.edu/etdc/view?acc_num=ysu1702296851253353

Abstract Details

2023, Master of Computing and Information Systems, Youngstown State University, Department of Computer Science and Information Systems.
Additive Manufacturing (AM), particularly LASER Powder Bed Fusion (LPBF), has gained prominence for its flexibility and precision in handling complex metal structures. However, optimizing L-PBF for intricate designs involves analyzing over 130 process parameters, leading to prolonged duration and increased costs. This thesis proposes a novel approach by harnessing statistical and machine learning algorithms to predict manufacturability issues before the printing process. By performing a comparative analysis of the intended design with the machine produced result, the study introduces two machine learning and one artificial neural network (ANN) algorithm to forecast the printability of new designs accurately. This innovative method aims to reduce or eliminate the need for iterative printing, reducing productivity costs and optimizing the LPBF additive manufacturing process.
Alina Lazar, PhD (Advisor)
John R. Sullins, PhD (Committee Member)
Hunter Taylor, PhD (Committee Member)
37 p.
Computer Engineering; Computer Science; Engineering; Information Science; Information Systems; Information Technology; Materials Science; Mechanical Engineering
laser powder bed fusion; machine learning; additive manufacturing; optimization; quality test artifact 3D printing; deep learning; Artificial neural network; Decision Tree; AdaBoost; XGBoost; computer science; LPBF; AM; AI; ML; QTA

Recommended Citations

Citations

  • Khan, D. (2023). Manufacturability Analysis of Laser Powder Bed Fusion using Machine Learning [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1702296851253353

    APA Style (7th edition)

  • Khan, Daniyal. Manufacturability Analysis of Laser Powder Bed Fusion using Machine Learning. 2023. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1702296851253353.

    MLA Style (8th edition)

  • Khan, Daniyal. "Manufacturability Analysis of Laser Powder Bed Fusion using Machine Learning." Master's thesis, Youngstown State University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1702296851253353

    Chicago Manual of Style (17th edition)

ysu1702296851253353
129
© 2023, all rights reserved.
This open access ETD is published by Youngstown State University and OhioLINK.