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  4. Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors
 
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Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors

Type
Journal article
Language
English
Date issued
2022
Author
Durczak, Karol 
Rybacki, Piotr 
Sujak, Agnieszka 
Faculty
Wydział Inżynierii Środowiska i Inżynierii Mechanicznej
Wydział Rolnictwa, Ogrodnictwa i Bioinżynierii
Journal
Applied Sciences (Switzerland)
ISSN
2076-3417
DOI
10.3390/app122312452
Web address
https://www.mdpi.com/2076-3417/12/23/12452
Volume
12
Number
23
Pages from-to
art. 12452
Abstract (EN)
Knowledge of the use-to-failure periods of process equipment, including agricultural vehicles, is essential for the determination of their durability and reliability. Obtaining any empirical data on this issue is difficult and sometimes impossible. Experimental studies are costly and time-consuming. Manufacturers are usually reluctant to share such data, claiming that the information is classified for the sake of their companies. The purpose of this study was to compare empirical data with data generated using adequate statistical tools. The newly generated and very similar in value pseudorandom numbers were obtained by simulations using the Monte Carlo, Latin hypercube sampling and Iman-Conover methods. Reliability function graphs obtained from the generated time-series (use-to-failure periods) with matching Weibull distribution had very similar shape and scale parameters. They were are also comparable to parameters from experimental data extracted from a Polish Zetor agricultural tractor service station. The validation of the applied methods was limited as it was carried out only on the basis of the available data. Analysis of line graphs of cumulative deviations of the values of use-to-failure periods (times-to-fail) generated against empirical times-to-fail indicated that the best method in the studied case was the Monte Carlo method.
Keywords (EN)
  • simulation methods

  • pseudorandom number generator

  • reliability

  • farm tractor

  • Monte Carlo method

  • Latin hypercube sampling

License
cc-bycc-by CC-BY - Attribution
Open access date
December 5, 2022
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