Prediction of Surface Roughness in Additive Manufacturing Using Artificial Neural Networks

المؤلفون

  • Fatma Wafa Department of Material Science, College of Engineering, Misurata University, Libya
  • A.M. Abdulshahed Department of Electrical and Electronic Engineering, College of Engineering, Misurata University, Libya

DOI:

https://doi.org/10.36602/ijeit.v10i1.60

الكلمات المفتاحية:

3D printing، Surface roughness، Artificial neural network، The Back propagation network، the Multi-regression model

الملخص

In this work, we applied an Artificial Neural Networks (ANN) approach for prediction of the part surface roughness for 3D printing technology. A small number of neurons was used for building ANN model with the help of MATLAB environment. The predicted values are found to be in excellent agreement with the experimental data with average error value of 8%.In addition, we compared the proposed ANN model to another regression-based approach. Results show that the proposed model has high accuracy in comparison to statistical approach. Therefore, we can use ANN model to predict the part surface roughness for 3D printing technology.

التنزيلات

تنزيل البيانات ليس متاحًا بعد.

التنزيلات

منشور

2024-01-23

إصدار

مجلد 10 عدد 1 (2022): December 2022

القسم

Article

الرخصة

الحقوق الفكرية (c) 2022 The International Journal of Engineering & Information Technology (IJEIT)

Creative Commons License

هذا العمل مرخص بموجب Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

كيفية الاقتباس

Prediction of Surface Roughness in Additive Manufacturing Using Artificial Neural Networks. (2024). The International Journal of Engineering & Information Technology (IJEIT), 10(1), 99-104. https://doi.org/10.36602/ijeit.v10i1.60

المؤلفات المشابهة

1-10 من 131

يمكنك أيضاً إبدأ بحثاً متقدماً عن المشابهات لهذا المؤلَّف.