Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors
| cris.virtual.author-orcid | 0000-0003-4811-005X | |
| cris.virtual.author-orcid | 0000-0001-7223-6491 | |
| cris.virtual.author-orcid | 0000-0001-5616-3827 | |
| cris.virtualsource.author-orcid | ebe065e1-88e3-4328-92a9-62cb28d0570e | |
| cris.virtualsource.author-orcid | 110d6c25-5395-4f20-b8e7-5e160c853b52 | |
| cris.virtualsource.author-orcid | a2f42993-2b76-4d53-acc8-61c1b5b10c4e | |
| dc.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. | |
| dc.affiliation | Wydział Inżynierii Środowiska i Inżynierii Mechanicznej | |
| dc.affiliation | Wydział Rolnictwa, Ogrodnictwa i Bioinżynierii | |
| dc.affiliation.institute | Katedra Inżynierii Biosystemów | |
| dc.affiliation.institute | Katedra Agronomii | |
| dc.contributor.author | Durczak, Karol | |
| dc.contributor.author | Rybacki, Piotr | |
| dc.contributor.author | Sujak, Agnieszka | |
| dc.date.access | 2026-01-27 | |
| dc.date.accessioned | 2026-02-06T13:16:14Z | |
| dc.date.available | 2026-02-06T13:16:14Z | |
| dc.date.copyright | 2022-12-05 | |
| dc.date.issued | 2022 | |
| dc.description.abstract | <jats:p>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.</jats:p> | |
| dc.description.accesstime | at_publication | |
| dc.description.bibliography | il., bibliogr. | |
| dc.description.finance | publication_nocost | |
| dc.description.financecost | 0,00 | |
| dc.description.if | 2,7 | |
| dc.description.number | 23 | |
| dc.description.points | 100 | |
| dc.description.version | final_published | |
| dc.description.volume | 12 | |
| dc.identifier.doi | 10.3390/app122312452 | |
| dc.identifier.issn | 2076-3417 | |
| dc.identifier.uri | https://sciencerep.up.poznan.pl/handle/item/7218 | |
| dc.identifier.weblink | https://www.mdpi.com/2076-3417/12/23/12452 | |
| dc.language | en | |
| dc.relation.ispartof | Applied Sciences (Switzerland) | |
| dc.relation.pages | art. 12452 | |
| dc.rights | CC-BY | |
| dc.sciencecloud | nosend | |
| dc.share.type | OPEN_JOURNAL | |
| dc.subject.en | simulation methods | |
| dc.subject.en | pseudorandom number generator | |
| dc.subject.en | reliability | |
| dc.subject.en | farm tractor | |
| dc.subject.en | Monte Carlo method | |
| dc.subject.en | Latin hypercube sampling | |
| dc.title | Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors | |
| dc.title.volume | Special Issue Innovative Solutions for Intelligent and Sustainable Machinery | |
| dc.type | JournalArticle | |
| dspace.entity.type | Publication | |
| oaire.citation.issue | 23 | |
| oaire.citation.volume | 12 |