DOI: https://doi.org/10.15802/stp2018/154686

EVALUATING THE QUALITY OF CARGO DELIVERY USING THE COEFFICIENT OF DEVIATION IN THE ARRIVAL TIME OF TRAINS

B. A. Tseyko

Abstract


Purpose. The research is aimed at considering the features of calculating the coefficient of deviation in the arrival time of trains to the station from the planned one relative to the expected deviation. Currently, for the management of cargo transportation, one uses the approaches in which such an indicator as the coefficient of deviation is not calculated and not taken into account. In practical implementation, this leads to the fact that the railway transporting cargo does not receive information on the ratio of nominal time deviations to real ones. This situation requires solving the problems of improving the current technologies of the transportation process related to the formation, organization and shipment of cargoes. Therefore, the requirements for the calculation of such factors are relevant. Methodology. To achieve the purpose, it is necessary to rank the collected statistics, group them and analyze them. A mathematical model is proposed for calculating the deviation of the train arrival time from the planned one and the dependence of this deviation from the delivery stage (station) and the number of trains (as a percentage of their total number). Findings. The concept of «deviation coefficient» has been introduced, which characterizes the deviation of the time of train arrival to a station from the planned relative to the expected deviation. Based on the results of the analysis of the deviation of the train arrival time at the station depending on the run, it can be noted that there is a direct relationship between the lateness of trains in hours and the station number (that is, distance). The result remains valid for an arbitrary number of trains (0, 25, 50, 75 and 100% were considered). Originality. The author first introduced the concept of “deviation coefficient”, which characterizes the deviation of the time of train arrival to a station from the planned relative to the expected deviation. Practical value. Based on the presented mathematical model, it is possible to foresee an approximate value of the lateness of trains for a railway line with a large number of stations, if the main characteristics of cargo transportation remain without significant changes, for example, a significant improvement or deterioration of the technical characteristics of the railway infrastructure.


Keywords


deviation; deviation coefficient; mean deviation; total coefficient of deviation; train

References


Gmurman, V. Y. (2004). Teoriya veroyatnostey i matematicheskaya statistika: uchebnoe posobie dlya vuzov. Moscow: Vyisshaya shkola. (in Russian)

Mochernyi, S. V. (Ed.). (2000). Ekonomichna entsyklopediia (Vol. 1-3). Kyiv: Akademiia. (in Ukrainian)

Yeliseeva, I. I. (Ed.), & Yuzbashev, M. M. (2001). Obshchaya teoriya statistiki. Moscow: Finansy i Statistika. (in Russian)

Kyrychenko, H. I. (2012). Problematyka zastosuvannia informatsiinykh tekhnolohii v upravlinni protsesamy dostavky vantazhu. Transport Problems, 9, 17-27. (in Ukrainian)

Kyrychenko, H. I. (2015). Intelligence system of a cargo delivery process management. Information and Management Systems of Railway Transport, 5(114), 3-6. (in Ukrainian)

Kyrychenko, H. I. (2013). Kontseptsiia intelektualnoi transportnoi systemy upravlinnia protsesamy dostavky vantazhu. Zaliznychnyi transport Ukrainy, 1, 37-40. (in Ukrainian)

Marmoza, A. T. (2013). Teoriia statystyky: Pidruchnyk. Kyiv: Tsentr uchbovoi literatury. (in Ukrainian)

Danko, M. I., Butko, T. V., Lomotko, D. V., & Kozak, V. V. (2010). Metodolohichnyi aspekt formuvannia kryteriiv efektyvnoho upravlinnia zaliznychnoiu transportnoiu systemoiu. Collected Scientific Works of Ukrainian State University of Railway Transport, 113, 5-9. (in Ukrainian)

Shmoylova, R. A. (Ed.). (2002). Obshchaya teoriya statistiki. Moscow: Finansy i Statistika. (in Russian)

Titov, B. A. (2012). Transportnaya logistika. docplayer.ru. Retrirved from https://docplayer.ru/25930451-B-a-titov-transportnaya-logistika.html (in Russian)

Udoskonalennia tekhnichnoho normuvannia pokaznykiv ekspluatatsiinoi roboty v umovakh pererozpodilu povnovazhen strukturnykh vertykalei PAT «Ukrzaliznytsia»: materialy seminaru-narady (05–06 chervnia 2018 r.). Lviv. (in Ukrainian)

Uskov, A. A., & Kuzmin, A. V. (2004). Intellektualnye tekhnologii upravleniya. Iskusstvennye neyronnye seti i nechetkiaya logika. Moscow: Goryachaya liniya-Telekom. (in Russian)

Grigorov, O., Druzhynin, E., Anishchenko, G., Strizhak, M., & Strizhak, V. (2018). Analysis of Various Approaches to Modeling of Dynamics of Lifting-Transport Vehicles. International Journal of Engineering & Technology, 7(4.3), 64-70. doi: 10.14419/ijet.v7i4.3.19553 (in English)

Kyrychenko, H., Statyvka, Y., Strelko, O., Berdnychenko, Y., & Nesterenko, Н. (2018). Assessment of Cargo Delivery Quality Using Fuzzy Set Apparatus. International Journal of Engineering & Technology, 7(4.3), 262-265. doi: 10.14419/ijet.v7i4.3.19800 (in English)

Marinov, М., Zunder, Т., Arnoldus, R., & Moolen, С. (2012). A standardised language code for rail freight operations. Transport Problems, 7(2), 141-148. (in English)

Kirit Mehta, A., & Swarnalatha, R. (2018). Adopting pade approximation for first order plus dead time models for blending process. International Journal of Engineering & Technology, 7(4), 2800-2805. doi: 10.14419/ijet.v7i4.18089 (in English)

Chernenko, S., Klimov, E., Chernish, A., Pavlenko, O., & Kukhar, V. (2018). Simulation Technique of Kinematic Processes in the Vehicle Steering Linkage. International Journal of Engineering & Technology, 7(4.3), 120-124. doi: 10.14419/ijet.v7i4.3.19720 (in English)

Strutynskyi, S., Kravchu, V., & Semenchuk, R. (2018). Mathematical Modelling of a Specialized Vehicle Caterpillar Mover Dynamic Processes Under Condition of the Distributing the Parameters of the Caterpillar. International Journal of Engineering & Technology, 7(4.3), 40-46. doi: 10.14419/ijet.v7i4.3.19549 (in English)


GOST Style Citations


  1. Гмурман, В. Е. Теория вероятностей и математическая статистика : учеб. пособие для вузов / В. Е. Гмурман. – 10-е изд., стереот. – Москва : Высш. шк., 2004. – 479 с.
  2. Економічна енциклопедія : у 3 т. / відп. ред. С. В. Мочерний. – Київ : Академія, 2000. – Т. 1. – 864 с.
  3. Елисеева, И. И. Общая теория статистики : учебник / И. И. Елисеева, М. М. Юзбашев ; под ред. И. И. Елисеевой. – 4-е изд., перераб. и доп. – Москва : Финансы и Статистика, 2001. – 480 с.
  4. Кириченко, Г. І. Проблематика застосування інформаційних технологій в управлінні процесами доставки вантажу / А. І. Кириченко // Проблеми транспорту : зб. наук. пр. – Київ, 2012. – Вип. 9. – С. 17–27.
  5. Кириченко, Г. І. Інтелектуальна система управління процесом доставки вантажу / Г. І. Кириченко // Інформ.-керуючі системи на залізн. трансп. – 2015. – № 5 (114). – С. 3–6.
  6. Кириченко, Г. І. Концепція інтелектуальної транспортної системи управління процесами доставки вантажу // Залізничний транспорт України. – 2013. – № 1. – С. 37–40.
  7. Мармоза, А. Т. Теорія статистики : підручник / А. Т. Мармоза. – 2-е вид, перероб. та доп. – Київ : Центр учбової літератури, 2013. – 592 с.
  8. Методологічний аспект формування критеріїв ефективного управління залізничною транспортною системою / М. І. Данько, Т. В. Бутько, Д. В. Ломотько, В. В. Козак // Зб. наук. пр. Укр. держ. акад. залізн. трансп. – Харків, 2010. – Вип. 113. – С. 5–9.
  9. Общая теория статистики : учебник / под ред. Р. А. Шмойловой. – 3-е изд., перераб. – Москва : Финансы и Статистика, 2002. – 560 с.
  10. Титов, Б. А. Транспортная логистика [Електронний ресурс] : электрон. учеб. пособие / Б. А. Титов // docplayer.ru. – Самара, 2012. – Режим доступу: https://docplayer.ru/25930451-B-a-titov-transportnaya-logistika.html – Назва з екрана. – Перевірено : 22.12.2018.
  11. Удосконалення технічного нормування показників експлуатаційної роботи в умовах перерозподілу повноважень структурних вертикалей ПАТ «Укрзалізниця» : матеріали семінару-наради (05–06 черв. 2018 р.). – Львів, 2018. – С. 1–16.
  12. Усков, А. А. Интеллектуальные технологии управления. Искусственные нейронные сети и нечёткиая логика / А. А. Усков, А. В. Кузьмин. – Москва : Горячая линия-Телеком. 2004. – 143 с.
  13. Analysis of Various Approaches to Modeling of Dynamics of Lifting-Transport Vehicles / O. Grigorov, E. Druzhynin, G. Anishchenko, M. Strizhak, V. Strizhak // International Journal of Engineering & Technology. – 2018. – Vol. 7. – Iss. 4.3. – P. 64–70. doi: 10.14419/ijet.v7i4.3.19553
  14. Assessment of cargo delivery quality using fuzzy set apparatus / Н. Kyrychenko, Y. Statyvka, О. Strelko, Y. Berdnychenko, Н. Nesterenko // International Journal of Engineering & Technology. – 2018. – Vol. 7. – Iss. 4.3. – P. 262–265. doi: 10.14419/ijet.v7i4.3.19800
  15. A standardised language code for rail freight operations / M. Marinov, T. Zunder, R. Arnoldus, C. Moolen // Transport Problems. – 2012. – Vol. 7. – Iss. 2. – Р. 141–148.
  16. Kirit Mehta, A. Adopting pade approximation for first order plus dead time models for blending process / A. Kirit Mehta, R. Swarnalatha // International Journal of Engineering & Technology. – 2018. – Vol. 7. – Iss. 4. – P. 2800–2805. doi: 10.14419/ijet.v7i4.18089
  17. Simulation Technique of Kinematic Processes in the Vehicle Steering Linkage / S. Chernenko, E. Klimov, A. Chernish, O. Pavlenko, V. Kukhar // International Journal of Engineering & Technology. – 2018. – Vol. 7. – Iss. 4.3. – P. 120–124. doi: 10.14419/ijet.v7i4.3.19720
  18. Strutynskyi, S. Mathematical Modelling of a Specialized Vehicle Caterpillar Mover Dynamic Processes Under Condition of the Distributing the Parameters of the Caterpillar / S. Strutynskyi, V. Kravchuk, R. Semenchuk // International Journal of Engineering & Technology. – 2018. – Vol. 7. – Iss. 4.3. – P. 40–46. doi: 10.14419/ijet.v7i4.3.19549




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