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3D printing and additive manufacturing. 2024 Oct 22;11(5):e1909-e1920. doi: 10.1089/3dp.2023.0189 Q32.12025

Energy Consumption Prediction of Additive Manufactured Tensile Strength Parts Using Artificial Intelligence

基于人工智能的增材制造拉伸试件能耗预测模型研究 翻译改进

Osman Ulkir  1, Mehmet Said Bayraklılar  2, Melih Kuncan  3

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作者单位

  • 1 Department of Electric and Energy, Mus Alparslan University, Mus, Turkey.
  • 2 Department of Civil Engineering, Siirt University, Siirt, Turkey.
  • 3 Department of Electrical and Electronics Engineering, Siirt University, Siirt, Turkey.

    • DOI: 10.1089/3dp.2023.0189 PMID: 39741545

    摘要 Ai翻译

    The manufacturing sector's interest in additive manufacturing (AM) methods is increasing daily. The increase in energy consumption requires optimization of energy consumption in rapid prototyping technology. This study aims to minimize energy consumption with determined production parameters. Four machine learning algorithms are preferred to model the energy consumption of the fused deposition modeling-based 3D printer. The real-time measured test sample d... ...点击完成人机验证后继续浏览
    Copyright © 3D printing and additive manufacturing. 中文内容为AI机器翻译，仅供参考！

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    期刊名：3d printing and additive manufacturing

    缩写：3D PRINT ADDIT MANUF

    ISSN：2329-7662

    e-ISSN：2329-7670

    IF/分区：2.1/Q3

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    Energy Consumption Prediction of Additive Manufactured Tensile Strength Parts Using Artificial Intelligence