Simulation model of situational control of transshipment machinery fleet
The seaport is a place for cargo transshipment and storage. The speed of vehicle processing is one of the indicators of port’s performance. The time of vehicles being under processing depends on the performance of a fleet of transshipment machinery. The stochastic nature of vehicles’ arriving leads...
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2019-01-01
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doaj-f2f5f8a9698342b98c93706ab796bd342021-02-02T01:45:51ZengEDP SciencesE3S Web of Conferences2267-12422019-01-011350202810.1051/e3sconf/201913502028e3sconf_itese18_02028Simulation model of situational control of transshipment machinery fleetZub Igor0Ezhov Yuriy1Shchemelev Viktor2Admiral Makarov State University of Maritime and Inland ShippingAdmiral Makarov State University of Maritime and Inland ShippingAdmiral Makarov State University of Maritime and Inland ShippingThe seaport is a place for cargo transshipment and storage. The speed of vehicle processing is one of the indicators of port’s performance. The time of vehicles being under processing depends on the performance of a fleet of transshipment machinery. The stochastic nature of vehicles’ arriving leads to the intense operation of handling facilities and formation of wait lists for vehicles to be loaded or unloaded, or to the downtime of transshipment machinery when vehicles are absent. Depending on the operational situation, transshipment machinery is brought out for maintenance operations that can be performed by unit, which provides the increase in the technical use coefficient. For maintenance of individual units, the decomposition of handling facility is performed; statistical data on the time of maintenance conduction for all units is collected. Statistical data are entered into the database. When transshipment machinery is brought out of operation for a short period, the unit is selected, the service time of which coincides with the downtime of a brought out facility. To visualize the process of situational management of maintenance and define conflict situations, a simulation model was developed with the use of the apparatus of Petri nets. The analysis of the model helped to reveal conflict situations that can be solved both during situational management of transshipment machinery fleet and by means of models nested into conflict places.https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/61/e3sconf_itese18_02028.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zub Igor Ezhov Yuriy Shchemelev Viktor |
spellingShingle |
Zub Igor Ezhov Yuriy Shchemelev Viktor Simulation model of situational control of transshipment machinery fleet E3S Web of Conferences |
author_facet |
Zub Igor Ezhov Yuriy Shchemelev Viktor |
author_sort |
Zub Igor |
title |
Simulation model of situational control of transshipment machinery fleet |
title_short |
Simulation model of situational control of transshipment machinery fleet |
title_full |
Simulation model of situational control of transshipment machinery fleet |
title_fullStr |
Simulation model of situational control of transshipment machinery fleet |
title_full_unstemmed |
Simulation model of situational control of transshipment machinery fleet |
title_sort |
simulation model of situational control of transshipment machinery fleet |
publisher |
EDP Sciences |
series |
E3S Web of Conferences |
issn |
2267-1242 |
publishDate |
2019-01-01 |
description |
The seaport is a place for cargo transshipment and storage. The speed of vehicle processing is one of the indicators of port’s performance. The time of vehicles being under processing depends on the performance of a fleet of transshipment machinery. The stochastic nature of vehicles’ arriving leads to the intense operation of handling facilities and formation of wait lists for vehicles to be loaded or unloaded, or to the downtime of transshipment machinery when vehicles are absent. Depending on the operational situation, transshipment machinery is brought out for maintenance operations that can be performed by unit, which provides the increase in the technical use coefficient. For maintenance of individual units, the decomposition of handling facility is performed; statistical data on the time of maintenance conduction for all units is collected. Statistical data are entered into the database. When transshipment machinery is brought out of operation for a short period, the unit is selected, the service time of which coincides with the downtime of a brought out facility. To visualize the process of situational management of maintenance and define conflict situations, a simulation model was developed with the use of the apparatus of Petri nets. The analysis of the model helped to reveal conflict situations that can be solved both during situational management of transshipment machinery fleet and by means of models nested into conflict places. |
url |
https://www.e3s-conferences.org/articles/e3sconf/pdf/2019/61/e3sconf_itese18_02028.pdf |
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