METHOD OF THE STATISTICAL DIAGNOSTIC OF RELIABILITY OF SHIPS’ EQUIPMENT
DOI:
https://doi.org/10.18372/2306-1472.74.12291Keywords:
parameter value, ships’ electronic equipment, statistical diagnostic, technical serviceAbstract
Purpose: The purpose of this article is to present the method of the statistical diagnostic of ship onboard electronic equipment reliability. with using of probabilistic model of stream of refuses on the Neyman-Pirson’s plausibility criteria. Method: The article describes the method of account these criteria which allow to increase a control level on the state of reliability of ship onboard electronic equipment with using of the statistical diagnostic. Results: On the basis of the analysis conducting received in relation to the level of reliability of ship equipment made decision concerning to possible declining of equipment reliability level and terms and volume of his technical service. Discussion: The proposed method is the methodological basis for search of extremums of Neyman-Pirson’s criteria of the supervisions terms and permit to provide the diagnostic of ship onboard equipment reliability.
References
Anderson T. W. (1994) Statistical Analysis of Time Series. New York, Wiley-Interscience Publ., 704 p.
Arab-Ogly E.A., Bestuzhev-Lada I.V., Gavrilov N.F. (1982) Rabochaya kniga po prognozirovaniyu [Working book on prognostication]. Moscow, “Mysl” Publ., 430 p.
Borovikov V. (2003) Iskusstvo analiza dannykh na kompyuteri: dlya professionalov [Art of analysis of data on a computer: for professionals]. Saint-Petersburg, “Statistica” Publ., 688 p.
Gaskarov D.V., Golinkevich T.A., Mozga¬levskiy A.V. (1974) Prognozirovaniye tekhnicheskogo sostoyaniya i nadyozhnosti radioelektronnoy apparatury [Prognostication of the technical state and reliability of radio electronic equipment]. Moscow, Sovetskoye Radio Publ., 224 p.
Danik O.V. (2017) Sposib kontrolyu rivnya nadiynosti sudnovykh kompleksiv pri nestabil’nykh umovakh sposterejennya [A method for controlling the level of reliability marine complex in unstable conditions of observations]. Kiev, “Naukovy zapysky UNDIZ”, Issue No. 1 (45), pp. 104-108.
Ivanovich V.V., Il’in O. Yu., Kucheruk S.M. (2013) Prognozuvannya bezvidmovnosti obladnannya zasobiv vodnogo transportu metodamy statystychnogo analyzu chasovykh ryadiv [Prognostication of faultlessness of equipment of facilities of water transport objects by the methods of statistical analysis of time series]. Kiev, KSAWT, “Vodnyy Transport”, Issue No. 2., p. 218-223.
Lavrinenko V.F., Stadnik A.I., Torokhtey V.P. (2014) Vybor metoda mnogokriterial’noy optimizacii dlya upravleniya vodnym transportnym sredstvom [Choice of method of multicriterion optimization for a management by a water transport object]. Kiev, KSAWT, “Vodnyy Trtansport”. Issue No. 3 (21). pp. 11-14.
Tyurin Yu.P., Makarov A.A. (2003) Analiz dannykh na kompyutere [Analysis of data on a computer]. Moscow, “Infra-M” Publ., 544 p.
Shumway R. H., Stoffer D. S. (2010) Time Series Analysis and its Applications. With R Examples. Third edition. NY, Springer New York Dordrecht Heidelberg London Publ., 576 p. ISBN 978-1-4419-7864-6. DOI 10.1007/978-1-4419-7865-3.
Allianz Global Corporate & Specialty «Safety and Shipping Review 2015» Available at: https://www.cesam.org/documents/Shipping-Review-2015.pdf .
Official site of the International Maritime Organization. Casualties Statistic Analysis Available at: http://www.imo.org/en/KnowledgeCentre/ShipsAndShippingFactsAndFigures/Statisticalresources/ /Documents/FSI%2020%20INF-17%20%20Casualty%20statistics%20-%20loss%20of%20life%20from%202006%20to%20date.pdf .
Global Integrated Shipping Information System (GISIS) portal on the official site of site of the International Maritime Organization. Casualties Statistic Available at: https://gisis.imo.org/Public/ MCI/Default.aspx.