ASSESSMENT OF PROCESSING CAPACITY OF RAILWAY STATIONS BASED ON STATISTICAL ANALYSIS METHODS

Ihor Taran; Aigul Tilemisova; Dmytro Kozachenko; Anatoliy  Verlan; Serhii Grevtsov

doi:10.5937/jaes0-60902

Ihor Taran Rzeszow University of Technology, Faculty of Civil Engineering, Environmental Engineering and Architecture, Department of Roads and Bridges, Rzeszów, Poland
Aigul Tilemisova Satpayev University, M. Tynyshpayev School of Transport Engineering and Logistics, Department of Logistics, Almaty, Republic of Kazakhstan https://orcid.org/0000-0001-9171-5180
Dmytro Kozachenko Ukrainian State University of Science and Technologies, Faculty of Transportation Process Management, Department of Transport Service and Logistics, Dnipro, Ukraine https://orcid.org/0000-0003-2611-1350
Anatoliy Verlan LLC “Transinvestservice”, Vyzyrka, Odesa region, Ukraine https://orcid.org/0000-0001-7855-8942
Serhii Grevtsov Lviv Polytechnic National University, Institute of Mechanical Engineering and Transport, Department of Transport Technologies, Lviv, Ukraine https://orcid.org/0000-0003-2925-4293

DOI: https://doi.org/10.5937/jaes0-60902

Keywords: railway stations, transport services, processing capacity, management decisions

Abstract

The purpose of the study is to improve the methods of assessing the processing capacity of railway stations based on scientific observation data. The paper considers a large private station that provides transport services to port terminals when performing railway and water transportation. The research is performed based on methods of analysis of time series and theory of operation of railways. The study established the maximum permissible volume of work for the port station and also assessed the impact of the combination of diverse types of goods on the amount of its processing capacity. The scientific novelty of the work is to improve the methods of evaluating the processing capacity of railway stations based on the methods of statistical data analysis. Unlike the existing method, the method allows you to more accurately consider local features of stations. The practical value of the results obtained is that they allow to predict the work of the station in the conditions of accidental flow of port terminals requests for servicing and avoid overload. This enables the station management to develop more efficient strategies for managing its work.

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