Loading...
Please wait, while we are loading the content...
Similar Documents
Applying a Neural Network-Based Machine Learning to Laser-Welded Spark Plasma Sintered Steel: Predicting Vickers Micro-Hardness
| Content Provider | MDPI |
|---|---|
| Author | Olanipekun, Ayorinde Tayo Mashinini, Peter Madindwa Owojaiye, Oluwakemi Adejoke Maledi, Nthabiseng Beauty |
| Copyright Year | 2022 |
| Description | This paper presents an artificial neural network (ANN) approach to the estimation of the Vickers hardness parameter at the weld zone of laser-welded sintered duplex stainless steel. The sintered welded stainless-steel hardness is primarily determined by the sintering conditions and laser welding processing parameters. In the current investigation, the process parameters for both the sintering and welding processes were trained by ANNs machine learning (ML) model using a TensorFlow framework for the microhardness predictions of laser-welded sintered duplex stainless steel (DSS 2507 grade). A neural network is trained using a thorough dataset. The mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and $R^{2}$ for the train and test data were calculated. The predicted values were in good agreement with the measured hardness values. Based on the results obtained, the ANN method can be effectively used to predict the mechanical properties of materials. |
| Starting Page | 91 |
| e-ISSN | 25044494 |
| DOI | 10.3390/jmmp6050091 |
| Journal | Journal of Manufacturing and Materials Processing |
| Issue Number | 5 |
| Volume Number | 6 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-08-23 |
| Access Restriction | Open |
| Subject Keyword | Journal of Manufacturing and Materials Processing Manufacturing Engineering Duplex Stainless-steel Alloy Spark Plasma Sintering Laser Welding Artificial Neural Network Microhardness |
| Content Type | Text |
| Resource Type | Article |
