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Organization of Operation, Repair and Maintenance of Locomotives in the Railroad Operating Domain

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E3S Web of Conferences 135, 02008 (2019) https://doi.org/10.1051/e3sconf/201913502008 ITESE-2019 Organization of operation, repair and maintenance of locomotives in the railroad operating domain Aleksander Pavlyukov1, Alexander Buynosov1,*, Aleksander Mironov1, and Sergey Laptev1 1 Ural State University of Railway Transport, 66 Kolmogorova st., 620034, Ekaterinburg, Russia Abstract. The methods that are widely used today to determine the required locomotive fleet, the corresponding maintenance and repair system consider the locomotive as a whole, without taking into account the technical condition of its individual units, which have a limited life cycle. Furthermore, the methods used today do not take into account the time spent on relocation from an operational locomotive depot to a service depot and back. The purpose of this study is to develop the methods for determining the number of locomotives based on the anticipated workloads for specific operational sections, the necessary accompanying maintenance and repair, the optimized repair cycle structure with due account of the available resources of the limiting units in the railroad operating domain which are capable of taking into account the technical condition of equipment (failures, repair costs, and time spent on relocation from one depot to another). A model for organization of repair of gas turbine locomotives assigned to operational locomotive depots while undergoing repair in service locomotive depots is proposed. Using this model, it is possible to develop a software product for distributing routine locomotive repairs among service providers, thus optimizing the workload of the latter. 1 Introduction Development of the Far North regions is an important economic problem for the Russian Federation. Creation of the Northern Latitudinal Railway railroad operating domain will solve the following important problems: 1) provide access to Dudinka and Igarka ports to gain access to the Northern Sea Route connecting the Urals with European Russia and the Far East; 2) develop Russkoye and Zapolyarnoye oil and gas fields and the corresponding infrastructure; 3) create a stable transport connection with the city of Norilsk; 4) create an alternative railroad connection from the Yamalo-Nenets Autonomous District to the North- Western Region, as well as provide transportation support, infrastructure development, and operation of oil and gas fields of the Yamalo-Nenets Autonomous District and the Lower Angara Region; 5) link the Northern and Sverdlovsk railroads; 6) reduce the load on the Trans-Siberian Railway; 7) connect the Yamal peninsula with the country’s transportation infrastructure. * Corresponding author: [email protected] © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/). E3S Web of Conferences 135, 02008 (2019) https://doi.org/10.1051/e3sconf/201913502008 ITESE-2019 Within the framework of the “Strategy for Developing Rail Transport in the Russian Federation up to 2030” approved by the Government of the Russian Federation, the Northern Latitudinal Railway, railroad lines in the sections Obskaya–Salekhard (54 km long), Salekhard—Nadym (355 km), Nadym—Pangody (111 km) will be built. Provisions are made for reconstruction of the sections Pangody—Noviy Urengoy (113 km long), Noviy Urengoy—Korotchaevo (74 km), with a further planned extension of Korotchaevo— Russkoye (Yuzhno-Russkoye oil and gas field, 122 km long), Russkoye—Igarka (482 km), Igarka—Norilsk (285 km). Since the railroad lines of the Northern Latitudinal Railway will not be electrified, a promising rolling stock includes locomotives with a gas turbine engine (LGTE) running on liquefied natural gas (LNG), i.e. mainline gas turbine locomotives GT1h, which showed good performance results during experimental operation on the Sverdlovsk railway. The Russian railroad network has many converter stations for electric and diesel traction. Since a diesel locomotive is much less powerful than an electric locomotive, the trains at such stations need to be broken up and hauled in parts. To move away from this, starting 2005, RZD OJSC launched a complex of research and development works to create a locomotive with a gas turbine engine (LGTE) operating on liquefied natural gas (LNG). The LGTE is more powerful compared to both the electric or diesel locomotives, it is more cost-effective and environmentally friendly, and the LGTE can haul a train weighing more than 6,000 tons and deliver it to the destination without reconfiguration. In 2007, GT1h- 001, a novel mainline gas turbine locomotive based on VL15 electric locomotive, was built, and in 2013, a second gas turbine locomotive (GT1h-002) based on TEM7A diesel locomotive was manufactured [1, 2]. In February 2017, GT1h-002 was consigned to RZD OJSC to the Sverdlovsk railway for operation. Currently, the gas turbine locomotive (GTL) is serviced by STM-Service LLC in Artyomovsky service locomotive depot (SLD); the GTL is operated by crews of Egorshino operational locomotive depot. Because of its more complex structure (compared to a diesel locomotive), the problem of organizing operation, maintenance and repair for a modern GTL in the railroad operating domain Korotchaevo—Voynovka of the Sverdlovsk railway has arisen. This section is not electrified, it is included in the centralized traffic control. Section length is 1,331 km, there are way stations and junctions along the train line. However, there are no methods that take into account the required number of locomotives based on the anticipated workloads for specific operational sections, the necessary accompanying maintenance and repair, the optimized repair cycle structure with due account of the available resources of the limiting units in the railroad operating domain which are capable of taking into account the technical condition of equipment (failures, repair costs, and time spent on relocation from one depot to another), or such methods are not perfect [1–5]. 2 Research Methods To organize the repair and maintenance of gas turbine locomotives in a railroad operating domain, it is necessary to calculate their required number, and the corresponding repair and maintenance rates. Service speed is determined by the given service speed coefficient: Vs 8.0 VТ (1) where 0.8 is the service speed coefficient. Full turnover of locomotive: 2 E3S Web of Conferences 135, 02008 (2019) https://doi.org/10.1051/e3sconf/201913502008 ITESE-2019 2L (2) Т l tm tto Vs where L is the length of the operational section, km; tm is downtime for technical inspection for one turnover cycle, hr; tto is locomotive downtime in turnover point, hr. Locomotive requirement ratio: T K l (3) r 24 where Tl is locomotive turnover in the operational section, locomotive-km. The requirement ratio shows the number of locomotives required to serve one pair of trains per day. Then the operated park of locomotives in the section will be: No Kr n (4) where n is the number of train pairs. Based to the calculated number of locomotives in the section park, let us determine the repair program and the required operational resources. Daily mileage is determined using the following equation: Sd 2 L n (5) where L is section length, km; n is the number of train pairs per day. Annual and monthly locomotive mileage: Syear Sd 365 (6) (7) Average daily mileage for one locomotive is determined using the following equation: n (8) S av.d 2 L N o where No is the operated park of GTL; L is section length, km; n is the number of train pairs. The number of repair bays is determined by the annual program for locomotive repair in a service depot, their downtime in repair or maintenance, and the bay’s production time. For repairs that take days (RR-2 (routine repair), RR-3, BR (basic repair), MR (major repair)), we use the following equation [6]: N t C riri (9) ri D where Nri is the annual program for this type or repair; tri is repair downtime, days; D is the number of working days per year, D = 247 days. For repairs and inspections that take hours (M-2 (maintenance), M-3, RR-1), the number of repair sites is determined using the following equation: Nri trdi (10) Cri D ТС sh 3 E3S Web of Conferences 135, 02008 (2019) https://doi.org/10.1051/e3sconf/201913502008 ITESE-2019 where Tsh is the average duration of a shift; trdi is repair duration, hr; С is the number of shifts per day; µ is the coefficient accounting for nonuniformity of gas turbine locomotives arrival and docking for repairs M-2, M-3, RR-1, µ = 1.1. Generally, the number of bay sites (bays) for inspection and repair of equipment during routine repair of locomotives depends on many factors (repair downtime, shift duration, the bay’s production time, uniformity of docking for repair), and is determined using the following equation [7]: N t rr (11) Cr , K F tsh nsh where Nr is the number of routine repairs; tr is the standard downtime for locomotive repair, hr; K is the converting factor for the number of locomotive sections; F is the bay’s production time, days; tsh is the duration of a shift, hr; nsh is the number of shifts; is the coefficient accounting for nonuniform docking, = 1.1–1.2 [8]. The sequence of equipment failures in the course of locomotive operation can be presented in the form of the following model [9, 10]. Monitoring of the new (repaired) equipment starts at time l = 0 (Fig. 1). Fig. 1. Model of the repair process. After operating for a certain time (running time) 1 a failure occurs, then, equipment is repaired or replaced with new equipment within a time period much shorter than running time to failure li. After running time 2 the equipment fails, it is repaired again or replaced with the similar functioning equipment.
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  • Can Digital Transformation Solve the Problem of Arctic Youth Migration Outflow?

    Can Digital Transformation Solve the Problem of Arctic Youth Migration Outflow?

    sustainability Article Can Digital Transformation Solve the Problem of Arctic Youth Migration Outflow? Vadim E. Ljovkin 1, Gennadij F. Detter 2, Josif L. Tukkel 3, Elena Gladun 4 and Anastasia O. Ljovkina 5,* 1 Department of General and Social Psychology, Institute of Psychology and Pedagogy, Tyumen State University, 625007 Tyumen, Russia; [email protected] 2 Socio-Economic Research Sector, Arctic Scientific Research Center, 629007 Salekhard, Russia; [email protected] 3 Graduate School of Cyber-Physical Systems and Control, Peter the Great St. Petersburg Polytechnic University, 195251 Saint Petersburg, Russia; [email protected] 4 Institute of State and Law, University of Tyumen, 625007 Tyumen, Russia; [email protected] 5 Department of Economic Security, System Analysis and Control, Financial-Economic Institute, Tyumen State University, 625007 Tyumen, Russia * Correspondence: [email protected]; Tel.: +7-982-903-8395 Received: 24 November 2020; Accepted: 17 December 2020; Published: 21 December 2020 Abstract: Youth educational migration is an urgent problem for most Arctic cities. In particular, this problem is extremely important for Russia in the context of changing the paradigm of the planned development of the Arctic oil and gas economy into indefinite long-term prospects and scenarios of Arctic development. This situation led to reducing social-economic northern benefits and compensations and strengthens the trends of Arctic youth educational migration. However, the experience of digital transformation and forced distance learning due to the pandemic of 2020 could bring young people a new understanding of the opportunities of digitalization, influencing their migration decisions. To clarify the potential of digital technologies in solving the problem of youth migration outflow in the Russian Arctic, we surveyed the students at technical schools and colleges of the Yamal-Nenets autonomous area, Russia; sample size 1532 students in total.