Development of Predictive Model for Surface Roughness Using Artificial Neural Networks
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-9523-0_16
Reference22 articles.
1. Khoshaim AB et al (2021) Prediction of residual stresses in turning of pure iron using artificial intelligence-based methods. J Mater Res Technol (2021)
2. Rifai AP, Aoyama H, Tho NH, Dawal SZM, Masruroh NA (2020) Evaluation of turned and milled surfaces roughness using convolutional neural network. Measurement 161:107860
3. Gupta P, Singh B (2020) Local mean decomposition and artificial neural network approach to mitigate tool chatter and improve material removal rate in turning operation. Appl Soft Comput 96(2020):106714
4. Mikołajczyk T, Nowicki K, Bustillo A, Pimenov DY (2018) Predicting tool life in turning operations using neural networks and image processing. Mech Syst Signal Process 104:503–513
5. Sharma SK, Kumar ES (2014) Optimization of surface roughness in CNC turning of mild steel (1018) using Taguchi method. Carbon 100(2014):0–26
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