Author:
Jančíková Zora Koštialová,Koštial Pavel,Heger Milan,Frischer Robert,David Jiří,Špička Ivo,Garzinová Romana,Ružiak Ivan,Špačková Hana
Abstract
The paper presents the review of works devoted to the material engineering – diagnostic and technological application of artificial neural networks (ANN). This review has been realized by activities created in narrow connection with the industrial sphere, mainly as a constructive step to development of Industry 4.0 philosophy. The review covers different materials measurement and evaluation. There have been investigated such materials as rubber blends, laminates, optical glasses; and also survey covers degradation processes appeared in industrial applications as well as the material defect evaluation and wearing diagnostics. The last part of the review offers output concerning infrared technique application of ANN. This review can serve as an inspiration for new challenges.
Reference32 articles.
1. A novel vibration based non-destructive testing for predicting glass fibre/matrix volume fraction in composites using a neural network model
2. Back-propagation neural network-based approximate analysis of true stress-strain behaviors of high-strength metallic material
3. Computational homogenization of nonlinear elastic materials using neural networks
4. Seidl D.,
Kostial P.,
Jancikova Z.,
Ruziak I.,
Rusnakova S.,
Farkasova M.,
Digital Information Processing and Communications, 170 (2011)
5. Jancikova Z.,
Bosak O.,
Zimny O.,
Legouera M.,
Minarik S.,
Kostial P.,
Poulain M.,
Soltani M. T.,
International Carpathian Control Conference, 196 (2014)