@article{3475d4f9-38f0-4648-80ab-badf610e0b9f,
author = {Piotr Bera, Małgorzata Heinrich, Grażyna Jasica, Jan Szybka},
title = {Developing the operational reliabity of motor vehicles},
journal = {Czasopismo Techniczne},
volume = {2014},
number = {Mechanika Zeszyt 1-M (4) 2014},
year = {2014},
issn = {0011-4561},
pages = {3-10},keywords = {developing reliability; operational reliability; artificial neural networks},
abstract = {This article presents a process of developing operational reliability based on damage occurring during operation. A programme operating on the basis of the artificial neural network method was used to determine the probability of damage to selected engine elements. The results calculated in this way may serve as feedback information for the design process, enabling continuous improvement in the quality of the product, i.e. the automobile combustion engine. Factors taken into consideration during artificial neural network construction, the number of inputs and outputs resulting from the number of variables, and the learning algorithm were described.},
doi = {10.4467/2353737XCT.14.043.2493},
url = {https://ejournals.eu/czasopismo/czasopismo-techniczne/artykul/developing-the-operational-reliabity-of-motor-vehicles}
}