Schematic of the ANN model.

<div><p>Despite the advantages of additive manufacturing, its widespread adoption is still hindered by the poor quality of the fabricated parts. Advanced machine learning techniques to predict part quality can improve repeatability and open additive manufacturing to various industries. T...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Fatma Alamri (20855088) (author)
مؤلفون آخرون:	Imad Barsoum (17178454) (author), Shrinivas Bojanampati (20855091) (author), Maher Maalouf (6318215) (author)
منشور في:	2025
الموضوعات:	Sociology Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified xlink "> despite mean squared error lt ;&# 8201 gt ;&# 8201 feature importance analysis alsi10mg samples produced 10 &# 181 support vector regression kernel ridge regression additive manufactured samples g ., porosity data including porosity open additive manufacturing scan speed region predicting relative density optimal laser power predict part quality additive manufacturing scan speed relative density laser power lasso regression accurately predict widespread adoption various industries study identified study aims still hindered results presented random forest process parameters poor quality layer thickness improve repeatability hatch distance evaluated based current work computational results additional measurements 120 hv
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Schematic of the ANN model.

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