Mathematical modeling of failure of port control systems

Abstract The need to increase the capacity of ports is due to the development of the Northern Sea Route as a national transport route of Russia in the Arctic, the National Program for the Development of the Far East, in the context of an increase in trade with other regions of Russia, as well as the...

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Published in:IOP Conference Series: Materials Science and Engineering
Main Author: Khripko, Tatyana
Format: Article in Journal/Newspaper
Language:unknown
Published: IOP Publishing 2021
Subjects:
Online Access:http://dx.doi.org/10.1088/1757-899x/1030/1/012101
https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101/pdf
https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101
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spelling crioppubl:10.1088/1757-899x/1030/1/012101 2024-06-02T08:02:25+00:00 Mathematical modeling of failure of port control systems Khripko, Tatyana 2021 http://dx.doi.org/10.1088/1757-899x/1030/1/012101 https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101/pdf https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101 unknown IOP Publishing http://creativecommons.org/licenses/by/3.0/ https://iopscience.iop.org/info/page/text-and-data-mining IOP Conference Series: Materials Science and Engineering volume 1030, issue 1, page 012101 ISSN 1757-8981 1757-899X journal-article 2021 crioppubl https://doi.org/10.1088/1757-899x/1030/1/012101 2024-05-07T14:02:28Z Abstract The need to increase the capacity of ports is due to the development of the Northern Sea Route as a national transport route of Russia in the Arctic, the National Program for the Development of the Far East, in the context of an increase in trade with other regions of Russia, as well as the reorientation of cargo flows from the Baltic ports to Russian ones in Primorsk, Ust-Luga and Vysotske. Increasing cargo turnover and ensuring the strategic economic interests of Russia requires the reconstruction of existing and construction of new modern port-industrial complexes, provided with advanced technologies, including the automation of logistics management processes, production and engineering systems. This article describes a method for mathematical modeling of the failure of control systems for automation of cargo terminals of ports. Since failures in the operation of automation systems lead to an increase in the load of cargo berths (terminals) of both sea and river port complexes, to a violation of logistics schemes, and as a consequence to an increase in costs. Modeling is carried out using methods of probability theory, in particular, the Poisson distribution law. A comparison of the empirical and theoretical failure rates of automation is performed using the Pearson criterion. The performed modeling will allow determining the technical and economic indicators of new construction, reconstruction or overhaul, in terms of the engineering systems of the facility, and optimize the automation processes. Article in Journal/Newspaper Arctic Northern Sea Route IOP Publishing Arctic IOP Conference Series: Materials Science and Engineering 1030 1 012101
institution Open Polar
collection IOP Publishing
op_collection_id crioppubl
language unknown
description Abstract The need to increase the capacity of ports is due to the development of the Northern Sea Route as a national transport route of Russia in the Arctic, the National Program for the Development of the Far East, in the context of an increase in trade with other regions of Russia, as well as the reorientation of cargo flows from the Baltic ports to Russian ones in Primorsk, Ust-Luga and Vysotske. Increasing cargo turnover and ensuring the strategic economic interests of Russia requires the reconstruction of existing and construction of new modern port-industrial complexes, provided with advanced technologies, including the automation of logistics management processes, production and engineering systems. This article describes a method for mathematical modeling of the failure of control systems for automation of cargo terminals of ports. Since failures in the operation of automation systems lead to an increase in the load of cargo berths (terminals) of both sea and river port complexes, to a violation of logistics schemes, and as a consequence to an increase in costs. Modeling is carried out using methods of probability theory, in particular, the Poisson distribution law. A comparison of the empirical and theoretical failure rates of automation is performed using the Pearson criterion. The performed modeling will allow determining the technical and economic indicators of new construction, reconstruction or overhaul, in terms of the engineering systems of the facility, and optimize the automation processes.
format Article in Journal/Newspaper
author Khripko, Tatyana
spellingShingle Khripko, Tatyana
Mathematical modeling of failure of port control systems
author_facet Khripko, Tatyana
author_sort Khripko, Tatyana
title Mathematical modeling of failure of port control systems
title_short Mathematical modeling of failure of port control systems
title_full Mathematical modeling of failure of port control systems
title_fullStr Mathematical modeling of failure of port control systems
title_full_unstemmed Mathematical modeling of failure of port control systems
title_sort mathematical modeling of failure of port control systems
publisher IOP Publishing
publishDate 2021
url http://dx.doi.org/10.1088/1757-899x/1030/1/012101
https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101/pdf
https://iopscience.iop.org/article/10.1088/1757-899X/1030/1/012101
geographic Arctic
geographic_facet Arctic
genre Arctic
Northern Sea Route
genre_facet Arctic
Northern Sea Route
op_source IOP Conference Series: Materials Science and Engineering
volume 1030, issue 1, page 012101
ISSN 1757-8981 1757-899X
op_rights http://creativecommons.org/licenses/by/3.0/
https://iopscience.iop.org/info/page/text-and-data-mining
op_doi https://doi.org/10.1088/1757-899x/1030/1/012101
container_title IOP Conference Series: Materials Science and Engineering
container_volume 1030
container_issue 1
container_start_page 012101
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