Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors
-
Published:2022-12-05
Issue:23
Volume:12
Page:12452
-
ISSN:2076-3417
-
Container-title:Applied Sciences
-
language:en
-
Short-container-title:Applied Sciences
Author:
Durczak KarolORCID, Rybacki PiotrORCID, Sujak AgnieszkaORCID
Abstract
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.
Funder
Polish Ministry of Science and Higher Education program Regional Initiative Excellence
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference44 articles.
1. Rzeźnik, C., Durczak, K., and Rybacki, P. (2015). Serwis Techniczny Maszyn, Wydawnictwo Uniwersytetu Przyrodniczego w Poznaniu. 2. Mishra, D., and Satapathy, S. (2021). Reliability and maintenance of agricultural machinery by MCDM approach. Int. J. Syst. Assur. Eng. Manag., 1–12. 3. Durczak, K., Selech, J., Ekielski, A., Żelaziński, T., Waleński, M., and Witaszek, K. (2022). Using the Kaplan–Meier Estimator to Assess the Reliability of Agricultural Machinery. Agronomy, 12. 4. Shao, X., Zheng, B., Luo, Z., and Song, Z. (2022). Establishment and Validation of a Structural Dynamics Model with Power Take-Off Driveline for Agricultural Tractors. Agriculture, 12. 5. Zhuravel, D., Samoichuk, K., Petrychenko, S., Bondar, A., Hutsol, T., Kuboń, M., Niemiec, M., Mykhailova, L., Gródek-Szostak, Z., and Sorokin, D. (2022). Modeling of Diesel Engine Fuel Systems Reliability When Operating on Biofuels. Energies, 15.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|