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Predicting Mechanical Strength and Optimized Parameters in FDM-Printed Polylactic Acid Parts Via Artificial Neural Networks and Desirability Analysis Cover

Predicting Mechanical Strength and Optimized Parameters in FDM-Printed Polylactic Acid Parts Via Artificial Neural Networks and Desirability Analysis

Open Access
|Sep 2024

Authors

Hind H. Abdulridha

ORCID

Hind.H.Abdulridha@uotechnology.edu.iq

University of Technology

Tahseen F. Abbas

University of Technology

Aqeel S. Bedan

University of Technology
DOI: https://doi.org/10.2478/mspe-2024-0040 | Journal eISSN: 2450-5781 | Journal ISSN: 2299-0461
Language: English
Page range: 428 - 437
Submitted on: Jan 1, 2024
Accepted on: Jul 1, 2024
Published on: Sep 5, 2024
Published by: STE Group sp. z.o.o.
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year

© 2024 Hind H. Abdulridha, Tahseen F. Abbas, Aqeel S. Bedan, published by STE Group sp. z.o.o.
This work is licensed under the Creative Commons Attribution 4.0 License.