征稿通知：人工智能與增材制造專刊IF 2.861

經(jīng)過三十多年的發(fā)展,，增材制造（3D打�,。┮呀�(jīng)成為主流的制造工藝,。增材制造通過直接基于3D模型逐層添加材料來制造產(chǎn)品,。與傳統(tǒng)制造技術(shù)相比，它能夠制造復(fù)雜的零件,，并允許更多的設(shè)計優(yōu)化自由度,。機器學(xué)習(xí)現(xiàn)在是一種熱門技術(shù)，已被用于醫(yī)學(xué)診斷,、圖像處理,、預(yù)測,、分類、學(xué)習(xí)關(guān)聯(lián),、回歸等領(lǐng)域,。目前，機器學(xué)習(xí)在制造業(yè)中的應(yīng)用越來越受到關(guān)注,，包括增材制造,。近期，由奧克蘭大學(xué)的Jingchao Jiang博士,，山東大學(xué)的Bin Zou,，Jikai Liu教授以及佐治亞理工的David Rosen教授在International Journal of Computer Integrated Manufacturing（影響因子2.861）上發(fā)起了Machine learning in Additive Manufacturing專刊,。目前正在征稿中,。

征稿包含以下主題但不限于以下主題：
●Artificial intelligence in AM
●Machine learning aided design for AM
●Machine learning for AM optimization
●Machine learning for AM decision making
●Machine learning for AM process planning
●Machine learning for 3D bioprinting
●Machine learning in hybrid additive-subtractive manufacturing
●State-of-the-art and new perspectives on machine learning in AM
●Artificial intelligence integrated AM systems
●Machine learning applications in AM

截稿日期為9月30日，期間如有疑問可隨時聯(lián)系特刊主編,。
Jingchao Jiang, Email: [email protected]
Bin Zou, Email: [email protected]
Jikai Liu, Email: [email protected]
期刊鏈接：https://www.tandfonline.com/toc/tcim20/current
特刊Call for papers鏈接：https://www.callforpapers.co.uk/machine-learning-manufacturing


全球科學(xué)家發(fā)布的涉及到3D打印的科研成果論文、專利,，盡在南極熊“3D打印科研”專欄http://93item.com/forum-231-1.html