International Journal of Industrial Engineering and Management

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Vol. 8 No. 4 (2017)
Original Research Article

Prediction of Polymer Composite Material Products Using Neural Networks

Alexander V. Gaganov
Voronezh State Technical University
Bio
Olya A. Karaeva
Voronezh State Technical University
Bio
Mitar Lutovac
University Union Nikola Tesla, Faculty for Management
Bio
Alexey M. Kudrin
Voronezh State Technical University
Bio
Alexander V. Kretinin
Voronezh State Technical University
Bio
Andrey A. Gurtovoy
Voronezh State Technical University
Bio

Published 2017-12-30

abstract views: 33 // FULL TEXT ARTICLE (PDF): 0


Keywords

  • technological process,
  • analysis,
  • modelling,
  • control,
  • neural network

How to Cite

Gaganov, A. V., Karaeva, O. A., Lutovac, M., Kudrin, A. M., Kretinin, A. V., & Gurtovoy, A. A. (2017). Prediction of Polymer Composite Material Products Using Neural Networks. International Journal of Industrial Engineering and Management, 8(4), 209–217. https://doi.org/10.24867/IJIEM-2017-4-121

Abstract

This article contains results of mathematical modeling of technological processes for manufacture of pre-production polymer composite prototypes having certain performance characteristics conducted with application of engineering analysis software using artificial neural networks. Based on mechanical testing results, the following material strength characteristics mathematical models were defined:ultimate strength (at room temperature);modulus of elasticity (at room temperature);compressive strength (at room temperature);compressive strength (at Т=150°С);ultimate strength (shear in the sheet’s plane);modulus of elasticity (shear in the sheet’s plane);ultimate strength (interlayer shear).The first step was to evaluate the statistic importance of outside parameters whichinfluence on materials' properties. The main task was to obtain the function of dependence of the mechanical properties from the outside factors.

 

Article history: Received (29.09.2017); Revised (11.10.2017); Accepted (06.11.2017)  

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