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Updated: Jun 8, 2025

Stereolithographic 3D Printing with Renewable Acrylates

Stereolithographic 3D Printing with Renewable Acrylates

Published on: September 12, 2018

通过机器学习优化制药3D打印中的环境可持续性.

Hanxiang Li¹, Manal E Alkahtani², Abdul W Basit¹

¹UCL School of Pharmacy, University College London, 29-39 Brunswick Square, London WC1N 1AX, UK.

International journal of pharmaceutics

|November 4, 2024

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这项研究探讨了环保的制药3D打印 (3DP),通过在化沉积模型中分析能源使用和二氧化碳排放. 优化构造板温度等参数和使用机器学习显著降低了环境影响.

科学领域:

制药制造业制药制造业制药制造业
可持续的工程是可持续的工程.
增材制造增材制造是一种增材制造.

背景情况:

3D打印 (3DP) 提供了个性化医疗,但也面临着有关碳排放的环境问题.
环保制造对于制药行业的未来至关重要.

研究的目的:

调查使用化沉积建模 (FDM) 制药3D打印对环境的影响,特别是能源消耗和二氧化碳排放.
确定影响能源使用的关键参数,并探索机器学习 (ML) 在优化可持续制药生产中的作用.

主要方法:

利用实验设计 (DoE) 和机器学习 (ML) 来分析四种常见药物剂型的136次实验运行中的能耗.
确定了影响能源使用的关键参数:物体数量,构造板温度,喷嘴温度和层高度.

主要成果:

减少研发中的试错和较低的构造板温度被发现可以显著降低二氧化碳排放.
与DoE相比,ML管道在预测二氧化碳排放方面表现出更高的准确性,验证了其在可持续工艺开发方面的潜力.
经过验证的ML模型在各种剂量形式和几何复杂性中保持了高准确性.

结论:

结合可持续性和数字化,特别是通过机器学习,是环保医药3D打印的关键,与工业5.0原则保持一致.

关键词:

通过3D打印打印3D打印.人工智能的人工智能是人工智能.数字制造数字制造能源消耗, 碳足迹, 碳排放医疗保健 5.0 在线制药制造业制药制造业制药制造业可持续发展可持续性可持续性

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Last Updated: Jun 8, 2025

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优化打印参数和减少浪费对于制药添加剂制造的可持续未来至关重要.

ML显示了与DoE相似的学习能力,表明了它在制药制造业更广泛采用的有希望的道路.