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

Hind H. Abdulridha

Hind H. Abdulridha

University of Technology
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Abdulridha, Hind H.
, 
Tahseen F. Abbas

Tahseen F. Abbas

University of Technology
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Abbas, Tahseen F.
 and 
Aqeel S. Bedan

Aqeel S. Bedan

University of Technology
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Bedan, Aqeel S.
  
Sep 05, 2024
Predicting Mechanical Strength and Optimized Parameters in FDM-Printed Polylactic Acid Parts Via Artificial Neural Networks and Desirability Analysis's Cover Image
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Published Online: Sep 05, 2024
Page range: 428 - 437
Received: Jan 01, 2024
Accepted: Jul 01, 2024
DOI: https://doi.org/10.2478/mspe-2024-0040
Keywords
© 2024 Hind H. Abdulridha et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Engineering, Mechanical Engineering, Tools and Methods, Production Technology, Process Engineering and Industrial Engineering, Business and Economics, Business Management, Management Accounting, Financial Controlling, Cost Calculation, Investment
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