CC BY
54
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
УДК 656.222.3:656.212.5
G. I. NESTERENKO1, M. I. MUZYKIN2*, V. L. HOROBETS3, S. I. MUZYKINA4
'Dep. «Management of Operational Work», Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan, Lazaryan St., 2, Dnipropetrovsk, Ukraine, 49010, tel. +38 (056) 373 15 70, e-mail galinamuzykina@rambler.ru, ORCID 0000-0003-1629-0201
2*Dep. «Safety of Life Activity», Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan, Lazaryan St., 2, Dnipropetrovsk, Ukraine, 49010, tel. +38 (095) 251 53 14, e-mail grafmim@rambler.ru, ORCID 0000-0003-2938-7061
3Dep. «Safety of Life Activity», Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan, Lazaryan St., 2, Dnipropetrovsk, Ukraine, 49010, tel. +38 (056) 793 19 08, e-mail v-gorobets@mail.ru, ORCID 0000-0002-6537-7461
4Dep. «Safety of Life Activity», Dnipropetrovsk National University of Railway Transport named after Academician V. Lazaryan, Lazaryan St., 2, Dnipropetrovsk, Ukraine, 49010, tel. +38 (066) 082 88 27, e-mail fufei@rambler.ru, ORCID 0000-0002-5832-6949
STUDY OF CAR TRAFFIC FLOW STRUCTURE ON ARRIVAL AND DEPARTURE AT THE MARSHALLING YARD X
Purpose. The paper is aimed to analyse the existing car traffic organization at the marshalling yard aimed to reduce downtime of cars. Methodology. The methods of mathematical statistics allowed building the histogram of car traffic flow distribution at the marshalling yard and assessment of their parameters. The key quantitative and qualitative indicators of the station operation were analyzed. In order to analyze the effect of rehandling volume on the rehandled transit car downtime elements at the station we plotted the dependence graph of the car downtime elements on the rehandling volume. The curve variation on the graph clearly shows the effect of rehandling volume on two downtime elements: during formation and in expectation of operations. Findings. The question of reducing the average downtime of all car categories at the station should be solved by reducing unproductive downtime was proved. The correct determination of the average time spent by a rehandled transit car at the station is essential, especially in the conditions of new system of economic incentives. But still there is no separate methodology for determining the car downtime, which would allow to objectively consider the equipment and operation technology and exclude the possibility for subjective decisions. Originality. One of the main kinds of unproductive downtime during the carriage of goods by rail is a downtime on the marshalling yards in expectation of technological operations because of the system congestion. Reduction of this indicator is possible due to rational use of the marshalling yard capacity provided the rational distribution and car - and train flows between the major marshalling yards of Ukrzal-iznytsia. Practical value. The analysis of changes in downtime elements, depending on the rehandling volume allows not only to identify the car downtime reduction methods, but also to make a correct assessment of station staff work, as well as to adjust the rate of idle wagons.
Keywords: car traffic flow; marshalling yard; rehandling volume; downtime of cars; formation parameter
Introduction
The marshalling yard is a complex set of technologically interrelated elements intended for car flow rehandling.
Marshalling yards of Ukrainian railway network are usually located at the junctions. They rehandle the flows coming from different directions. These stations were always the busiest and the capacity of the entire line is dependent on them as 70% of all car traffic flows are rehandled at the junctions. That is why, the question of improvement of marshalling yard operation at the junctions is of high importance.
Behavior of incoming and outgoing flows is one of the most important requirements for the components taken into account when describing the performance of any queuing system.
Train arrival analysis was investigated by the scientists V. M. Akulinichev, T. V. Butko, N. N. Shabalin, I. B. Sotnikov, K. K. Tal, P. S. Hruntovy, A. M. Makarochkin and others [114]. The studies have shown that the distribution of intervals between them with a sufficient degree of accuracy can be approximated by the exponential law or generalized Erlang law and in rare cases -by Erlang law of a higher order.
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
Purpose
Analysis of the existing car traffic organization at the marshalling yard aimed to reduce downtime of cars.
Methodology
Using the methods of mathematical statistics we build the histograms of car traffic flow distribution at X marshalling yard and assess their parameters (mathematical expectation, standard deviation, variation coefficient, irregularity coefficient) [1, 2, 14].
Of the total car traffic flow of the station we should distinguish the car flows in unpaired and paired directions. The general car traffic flow includes the cars of working and non-working fleet. The working cars in their turn depending on the destination station are divided into transit (with and without rehandling) and local ones [3-6].
For transit car traffic flow without rehandling, given the negligible downtime at the station and a small amount of coupled and uncoupled cars, it is possible to assume that the ingoing flow equals the outgoing one for the selected period. To determine the average value, variance and standard deviation the month car flow must be divided into intervals. Calculation of average values of the intervals in ranges, their share of the total interval weight and variances of daily transit car flow without rehan-dling is shown in the text. Daily transit car traffic flow without rehandling is broken into 100 car. intervals.
Average daily transit car traffic flow without rehandling in unpaired direction Nav= 537 car. The variance describes the deviation of the actual number of car traffic flow from the average value and equals 28 809 car2 For ease of comparison of the car traffic flow average value and the deviation of actual car traffic flow from this average value one uses the standard deviation that equals c = 170 wag. Histogram of daily transit car traffic flow volume without rehandling in unpaired direction is shown in Fig. 1.
Average daily transit car traffic flow without rehandling in paired direction Nav= 620 car. The variance is 65108 car2. Standard deviation is c = 255 car. Histogram of daily transit car traffic flow volume without rehandling in paired direction is shown in Fig. 2.
Average total daily transit car traffic flow without rehandling Nav = 1151 car. The variance is 106881 car2. Standard deviation is c = 327 car. Histogram of total daily transit car traffic flow volume without rehandling is shown in Fig. 3.
Fig. 1. Histogram of daily transit car traffic flow volume without rehandling in unpaired direction
Fig. 2. Histogram of daily transit car traffic flow volume without rehandling in paired direction
Fig. 3. Histogram of total daily transit car traffic flow volume without rehandling
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету з^зничного транспорту, 2016, № 1 (61)
Fig. 4. Histogram of daily rehandled transit and local car traffic flow volume
Transit flow with rehandling can be combined with local one due to the fact that both car categories arrive in trains rehandled at X station. The ingoing flow does not equal to the outgoing one for a certain period because of the considerable time of car stay at the station and the corner flow.
Average rehandled transit and local car traffic flow on arrival from unpaired direction is Nav = 1 154 car. The variance is 31 291 car2. Standard deviation is c = 177 car. Histogram of daily rehandled transit and local car traffic flow volume on arrival is shown in Fig. 4.
Average daily rehandled transit and local car traffic on arrival from paired direction Nav= 808 car. The variance is 17251 car2. Standard deviation is c = 131 car. Histogram of daily rehandled transit and local car traffic flow volume on arrival from paired direction is shown in Fig. 5.
Average total daily rehandled transit and local car traffic flow on arrival Nav= 1970 car. The variance is 42056 car2. Standard deviation is c = 205 car. Histogram of total daily rehandled transit and local car traffic flow volume on arrival is shown in Fig. 6.
Average daily rehandled transit and local car traffic flow on departure to unpaired direction Nav= 1018 car. The variance is 38843 car2. Standard deviation is c = 197 car. Histogram of daily rehandled transit and local car traffic flow on departure to unpaired direction is shown in Fig. 7.
Average daily rehandled transit and local car traffic on departure to paired direction Nav = 931 car. Nsr = 931 wt. The variance is 22 145 car2. Standard deviation is c = 149 car2. Histogram of daily rehandled transit and local car traffic flow on departure to paired direction is shown in Fig. 8.
Fig. 6. Histogram of total daily rehandled transit and local car traffic flow volume on arrival
Fig. 5. Histogram of daily rehandled transit and local car traffic flow volume on arrival from paired direction
Fig. 7. Histogram of daily rehandled transit and local car traffic flow on departure to unpaired direction
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету з^зничного транспорту, 2016, № 1 (61)
Average total daily rehandled transit and local car traffic on arrival Nav = 1971 car. The variance is 85322 car2. Standard deviation is c = 292 car. Histogram of total daily rehandled transit and local
car traffic flow on departure is shown in Fig. 9.
Average daily car traffic flows on arrival and departure in unpaired and paired directions for May 2015 are shown in Fig. 10, 11.
Fig. 8. Histogram of daily rehandled transit and local car traffic flow on departure to paired direction
Fig. 9. Histogram of total daily rehandled transit and local car traffic flow on departure
Fig. 10. Histogram of average daily car traffic flow volume on arrival for May 2015
Transit without rehandling from unpaired direction Transit without rehandling from paired direction
Transit rehandled and local from unpaired direction Transit rehandled and local from paired direction
транзит oes псрероокп в непарному напрямку тратит ö« гтерероЗкив парному напрямьу
Tpnmirrs псрсроокою та Micqeei в непарному нппрямку транзит ч перероокоюта мнцсш в парному напрямку
Fig. 11. Histogram of average daily car traffic flow volume on departure for May 2015
Transit without rehandling to unpaired direction Transit without rehandling to paired direction
Transit rehandled and local to unpaired direction Transit rehandled and local to paired direction
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету залiзничного транспорту, 2016, № 1 (61)
ЕКСПЛУАТАЦ1Я ТА РЕМОНТ ЗАСОБ1В ТРАНСПОРТУ
Table 1
The annual analysis of total daily transit car traffic flow volume without rehandling at X marshaling yard
№ ofrange Range limits Range centre, min Number of observations Bj NB Nj2Bj hj
left right Kj
1 679 862 771 65 0.1781 11.575 752.397 0.000973
2 862 1 045 954 86 0.2356 20.263 1 742.619 0.001288
3 1 045 1 228 1 137 75 0.2055 15.411 1 155.822 0.001123
4 1 228 1 411 1 320 41 0.1123 4.605 188.825 0.000614
5 1 411 1 594 1 503 33 0.0904 2.984 98.458 0.000494
6 1 594 1 777 1 686 28 0.0767 2.148 60.142 0.000419
7 1 777 1 960 1 869 13 0.0356 0.463 6.019 0.000195
8 1 960 2 143 2 052 12 0.0329 0.395 4.734 0.000180
9 2 143 2 326 2 235 7 0.0192 0.134 0.940 0.000105
10 2 326 2 509 2 418 5 0.0137 0.068 0.342 0.000075
Total 365 0.9123 45.866 2 638.677
Fig. 12. Histogram of distribution of the total daily transit car traffic flow without rehandling
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету залiзничного транспорту, 2016, № 1 (61)
Table 2
The annual analysis of total daily rehandled transit and local car traffic flow volume on arrival at X marshaling yard
№ ofranges Range limits Range centre, min Number of observations Bj NjBj Nj2Bj hj
left right K
1 1 280 1 423 1 352 5 0.1613 0.806 4.032 0.001128
2 1 423 1 566 1 495 17 0.5484 9.323 158.484 0.003835
3 1 566 1 709 1 638 27 0.8710 23.516 634.935 0.006091
4 1 709 1 852 1 781 36 1.1613 41.806 1 505.032 0.008121
5 1 852 1 995 1 924 91 2.9355 267.129 24 308.742 0.020528
6 1 995 2 138 2 067 71 2.2903 162.613 11 545.516 0.016016
7 2 138 2 281 2 210 63 2.0323 128.032 8 066.032 0.014212
8 2 281 2 424 2 353 24 0.7742 18.581 445.935 0.005414
9 2 424 2 567 2 496 19 0.6129 11.645 221.258 0.004286
10 2 567 2 710 2 639 12 0.3871 4.645 55.742 0.002707
Total 365 9.0323 592.645 44 643.226
Fig. 13. Histogram of distribution of total daily transit rehandled and local car traffic flow on arrival
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету залiзничного транспорту, 2016, № 1 (61)
Table 3
The annual analysis of total daily rehandled transit and local car traffic flow volume on departure at O marshaling yard
№№ of ranges Range limits Range centre, min Number of observations Bj NB Nj2Bj hj
left rights Kj
1 1 247 1 419 1 333 12 0.0329 0.395 4.734 0.000191
2 1 419 1 591 1 505 33 0.0904 2.984 98.458 0.000526
3 1 591 1 763 1 677 35 0.0959 3.356 117.466 0.000558
4 1 763 1 935 1 849 39 0.1068 4.167 162.518 0.000621
5 1 935 2 107 2 021 79 0.2164 17.099 1 350.792 0.001258
6 2 107 2 279 2 193 56 0.1534 8.592 481.140 0.000892
7 2 279 2 451 2 365 51 0.1397 7.126 363.427 0.000812
8 2 451 2 623 2 537 28 0.0767 2.148 60.142 0.000446
9 2 623 2 795 2 709 20 0.0548 1.096 21.918 0.000319
10 2 795 2 967 2 881 12 0.0329 0.395 4.734 0.000191
Total 365 0.9123 45.866 2 638.677
Fig. 14. Histogram of distribution of total daily transit rehandled and local car traffic flow on departure
The law of train arrival distribution is Poisson, and the intervals between them have exponential distribution (see Table 1-3, Fig. 12-14). Irre-gularity of train arrivals affects the station operation and must be taken into account both when developing the procedure and when solving the problems of the station technical equipment. [7-8].
The main indicator of the marshalling yard operation is the average downtime of rehandled transit cars. Station-time of cars consists of the time taken to perform successive operations on
individual elements of the rehandling process and downtime in expectation of operations. The correct determination of the average time spent by a rehandled transit car at the station is essential, especially in the conditions of new system of economic incentives. But still there is no separate methodology for determining the wagon downtime, which would allow to objectively consider the equipment and operation technology and exclude the possibility for subjective decisions.
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету залiзничного транспорту, 2016, № 1 (61)
Total station-time of rehandled transit car consists of the following elements [9-12]:
treh =tha +tbu +th +tacc +tqu +tcc +thd +tqu ,
where tha - time for train handling on arrival, t
ha
= 0.35 h; - average breaking-up queue time, hours; th - hump train breaking-up interval, th = 0.37 h; tacc - average downtime of cars during formation, hours; tqu - average composition queue time, hours; tcc - time for composition completion and train launching to departure yard excluding locomotive return time, tcc= 0.44 h; thd - time for train pre-departure handling, thd = 0.5 h; tdqu - departure queue time, hours.
Some downtime elements are the values, determined by the operation procedure and not dependent on the volume of work, which can be expressed as time to complete the operations.
Increase in workload leads to reduced downtime during formation but extends the queue downtime on the subsequent service element. Depending on the operation volume effect on the downtime elements, the latest can be divided into three groups
t = (t б +1 + ^ +1 б ) +1 + (tp + гф +to )
пер Vlo6 lr 1ф 1обр/ пак "оч оч оч /
Given Pollaczek-Khinchin formula [12], the last three downtime elements can be written as
tb =Ntg(UlC;5+Dg). qu 48-2Nth :
f =Nt2(1+u2), qu 48М-2№„ ;
td =NId(1+od),
qu 48-2NL :
d
Average downtime during formation is determined by the formula
t =
acc
ck N ''
where N - number of trains rehandled at the station per day; к - number of appointments of the trains composed at the station; c - formation parameter.
In order to analyze the effect of rehandling volume on the rehandled transit car downtime elements at the station we plot the dependence graph of the car downtime elements on the rehandling volume. The dependence graph is shown in Fig. 15.
Fig. 15. Dependence of car downtime on rehandling volume
The curve variation on the graph clearly shows the effect of rehandling volume on two downtime elements: during formation and in expectation of operations.
In case of small rehandling volumes the car downtime decrease should be achieved mainly by reducing the car formation costs organizing the approach of locking groups, replacement of one-group minor purpoe trains with the group ones, etc. In case of large rehandling volumes the focus should be given to reducing the time of breaking-up, composition and departure processes, in order to shorten the queue downtime.
The analysis of changes in downtime elements, depending on the rehandling volume allows not only to identify the car downtime reduction methods, but also to make a correct assessment of station staff work, as well as to adjust the rate of idle cars. The station car downtime rate is set for a specified amount of work. But the actual rehandling is different from the scheduled one. In this regard for objective evaluation of station staff work it is necessary to adjust the rate on the amount of work performed.
One of the important elements of the time spent by the cars at technical stations that affects the car traffic management system is car downtime during formation. This downtime may be determined both by total car flow, that is from the moment of arrival at the station of these specific cars and to
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
the moment of their departure from the station, and only by the flow at the marshalling track. To plan the composition for a specified period the car downtime during formation is determined with sufficient accuracy by analytical calculations. Analysis of the formation process in different conditions of car approach to the station and its operation makes it possible to determine more precisely the formation parameter c, and hence the formation car-hours for individual destinations or total value for the station.
The uncoordinated car approach to the station results in continuous formation process, with some cars queueing for the next train composition. In practice, there is uneven arrival of car groups and in different amounts, thus the formation parameter c may differ for certain destinations, and for certain categories of trains with the same destination that depart during the day. The formation parameter c is always averaged during the analytical calculations, that is its fluctuations are ignired.
Table 4
Analysis of execution of major quantitative and qualitative indicators
Description of indicator Plan for 1 half year of 2015 Execution
1 half year of2014 1 half year of 2015 Till 2014, % To plan, %
Total daily departure, incl., car 3 099 5 036 3 002 60 97
- transit with rehandling, car 1 987 2 401 1 940 81 98
- transit without rehandling, car 1 092 2 540 1 002 39 92
- local, car 20 46 17 37 85
Average arrival per day, train 62 95 63 66 102
Average departure per day, incl., train 60 91 57 63 95
- own composition, train - 47 39 83 -
Operating fleet, car 1 218 1 144 1 165 102 96
Average loading per day, car - 6 3 50 -
Average unloading per day, car - 36 7 19 -
Downtime of relandled transit cars, h 10.50 10.28 13.05 79 80
Downtime of transit cars without relandling, h 1.40 1.37 1.50 91 93
Downtime during 1 load operation, h 95.0 154.73 133.02 116 71
Static loading, ton/car 48.09 50.19 59.02 118 123
Wagon turnover, car 6 199 10 071 5 996 60 97
One can conclude that the formation parameter is dependent on uneven approach of car groups to the station, but besdides it is dependent on a significant number of factors that affect the train formation process. The average number of car groups e, forming the trains mom, depend on the number of car groups of a specific destination arriving during a certain period (day or TH ).
But we need to pay attention to the fact that continuous and uniform flow to the station of car groups with the same volume does not affect the formation parameter. Thus, the formation parameter is dependent on the interval between the car group arrivals, frequency and duration of interruptions in the train formation, the value of completing group, the number of cars in the first and other groups.
Analysis of execution of the main indicators at X station was conducted for the 1st half of 2015 and is presented in Table 13.
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету зашзничного транспорту, 2016, № 1 (61)
Downtime of transit car without rehandling for the I half of 2015 is not executed and makes 1.50 hours, that is overvalued compared to the planned target by 0.10 hours. Total losses in car -hours due to non-execution of downtime for transit car without rehandling make 18,127 car -h and occured for the following reasons:
- The target «Locomotive supply queue time» exceeds by 0.08 h (losses of 15,436 car -h) due to lack of train locomotives and foot-plate staff;
- «Departure queue time» by 0.02 h (losses of 2,691 car -h) due to occurence of non-productive element:
- Making way for passenger and suburban trains (losses of 217 car -h);
- Regulation by train dispatcher (losses of 2,474 car -h).
Compared to last year fact, the downtime of transit cars without rehandling exceeded by 0.13 h. Total losses in car-hours due to non-execution of downtime for transit car without rehandling make 23,565 car -h and occured for the following reasons:
- The target «Locomotive supply queue time» exceeds by 0.11 h (losses of 20,874 wag-h) due to lack of train locomotives and foot-plate staff;
- By 0.02 h (losses of 2,691 car -h) due to occurence non-productive element «Departure queue time» through waiting for departure after delivery trains.
Downtime of rehandled transit car for the I half of 2015 is not executed and makes 13. 05 h, that is overvalued compared to the planned target by 2.55 h. Total losses in car -hours due to non-execution of downtime for rehandled transit car make 887,586 car -h.
The element «For breaking-up» is overvalued by 0.12 h (losses of 41,769 car -h), for the following reasons:
- The target of unproductive element «Breaking-up queue time» is overvalued because of:
- The lack of free tracks at yards «B», «D» for formation of a new train on the free track (losses weights 4,993 car-h);
- Inability to transfer corner wagon traffic flow (losses of 27,744 car-h);
- Work with long trains (losses of 8,220 car-
h);
- Work with nomenclature cargo (losses of 812 car-h).
The element «Formation» is overvalued by 2.35 h (total losses of 817,972 car-h) for the following reasons:
- Long-term formation of certain destinations (losses of 709,205 car -h);
- Expectation for formation completion and supply of formed trains to the departure yard due to lack of shunting locomotives (losses of 14 045 car -h);
- Downtime of wagons with guard, with destination to Volnovakha station due to lack of suitable covered cars for guard travel (losses of 10,378 car -h);
- Downtime of formed trains with destination of Donetsk railways station (total losses of 84,344 car -h)
The element «Departure» is overvalued by 0.08 h (total losses of 27 845 car-h) for the following reasons:
- the target of unproductive element «Locomotive supply queue time» is exceeded by 0.06 h (losses of 21 784 car-h) due to lack of train locomotives and foot-plate staff;
- The target of unproductive element «Departure queue time is overvalued by 0.02 h (total losses of 6,061 wag-h) because of:
- Regulation by train dispatcher (losses of 2,656 car-h);
- Closure of the station О at the section from the point No. 344 to 203 km pk.3, closure at the line Н - I (losses of 2,395 car-h);
- Making way for passenger and suburban trains (losses of 714 car-h);
- Car accounting of 20.05.2015 (losses of 296 car-h).
Compared to last year fact, the downtime of transit rehandled cars exceeded by 2.77 h. Total losses in car-hours due to non-execution of downtime for transit rehandled car make 964,162 car-h.
The element «Formation» is overvalued by 2.88 h through expectation of sending the finished trains to the destination yard.
Process operation queue downtime amounted to elements:
- «from arrival to supply» - 50.36 h;
- «from cleaning to departure» - 30.41 h.
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
ЕКСПЛУАТАЦ1Я ТА РЕМОНТ ЗАСОБ1В ТРАНСПОРТУ
Table 5
Analysis of the local car during 1 loading operation
Description of indicator Plan for 1 half year of 2015 Execution 1 half of2015 Execution / plan
Downtime during 1 load operation, incl., h 95.00 133.02 +38.02
- from arrival to supply, h 29.34 60.97 +31.63
- during loading operations, h 38.02 28.71 -9.31
- from cleaning to departure, h 27.64 43.34 +15.70
Table 6
Analysis of hump operation
Description of indicator Plan for 1 half year of 2015 Execution
1 half year of2014 1 half year of 2015 Till 2014, % To plan, %
Relandling of cars per day, incl., car 2 776 3 211 2 845 88.60 102.48
- unpaired system, car 1 442 1 582 1 521 96.14 105.48
paired system, car 1 334 1 629 1 324 81.28 99.25
Repeated rehandling - 766 942 122.98 -
Corner flow per day, incl., car - 345 415 120.29 -
- unpaired system, car - 176 182 103.41 -
- paired system, car - 169 233 137.87 -
Local wagons per day, incl., car - 421 527 125,18 -
- unpaired system, car - 208 258 124.04 -
- paired system, car - 213 269 126.29 -
Repeated rehandling is required for 942 car, incl.:
- Corner flow wagons - 415 car;
- Cars from ap/tracks - 10 car;
- Cars of productive rehandling - 294 car, incl.:
- Buffer cars for dangerous goods - 48 car;
- Cars of separating track after repair, cars without documents - 56 car;
- Rebuilding of trains because of the cars traveling by the 1st freight document - 51 car;
- Composition of pickup trains - 48 car;
- Rebuilding of trains of extra-length and weight - 48 car;
- For composition of cars with metal products, setting of covered wagon for MSS escorting - 43 car;
- Cars to be placed into train main part - 223 car, incl.:
- Cars, requiring MSS escorting - 92 car;
- Cars loaded with metal and metal products -131 car.
Total car downtime at the station consists of productive and unproductive downtime. Productive downtime includes time for process operations, time for car formation, while unproductive downtime includes the process operation queue time.
The question of reducing the average downtime of all car categories (transit without rehandling, rehandled, local) at the station should be solved by reducing unproductive downtime.
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету з^зничного транспорту, 2016, № 1 (61)
Findings
The methods of mathematical statistics allowed building the histogram of car traffic flow distribution at the marshalling yard and assessment of their parameters. The key quantitative and qualitative indicators of the station operation were analyzed. In order to analyze the effect of rehandling volume on the rehandled transit car downtime elements at the station we plotted the dependence graph of the car downtime elements on the rehandling volume. The curve variation on the graph clearly shows the effect of rehandling volume on two downtime elements: during formation and in expectation of operations.
In case of small rehandling volumes the car downtime decrease should be achieved mainly by reducing the car formation costs organizing the approach of locking groups, replacement of one-group minor purpoe trains with the group ones, etc. In case of large rehandling volumes the focus should be given to reducing the time of breaking-up, composition and departure processes, in order to shorten the queue downtime.
Originality and practical value
One of the main kinds of unproductive downtime during the carriage of goods by rail is a downtime on the marshalling yards in expectation of technological operations because of the system congestion. Reduction of this indicator is possible due to rational use of the marshalling yard capacity provided the rational distribution and car- and train flows between the major marshalling yards of Ukrzaliznytsia. The analysis of changes in downtime elements, depending on the rehandling volume allows not only to identify the car downtime reduction methods, but also to make a correct assessment of station staff work, as well as to adjust the rate of idle cars. The rate of car downtime at the station is set for a specified amount of work. But the actual rehandling is different from the target one. In this regard the objective evaluation of station staff work requires adjustment of the rate on the amount of work performed.
Conclusions
The question of reducing the average downtime of all car categories at the station should be solved by reducing unproductive downtime. The correct
determination of the average time spent by a rehandled transit car at the station is essential, especially in the conditions of new system of economic incentives. But still there is no separate methodology for determining the car downtime, which would allow to objectively consider the equipment and operation technology and exclude the possibility for subjective decisions.
LIST OF REFERENCE LINKS
1. Богданов, В. М. Резервы пропускной и провозной способности / В. М. Богданов // Ж.-д. трансп. - 2008. - № 8. - C. 54-56.
2. Бутько, Т. В. До питання визначення оптимально! шлькосп сортувальних станцш / Т. В. Бутько, М. I. Данько, Г. М. Оконенко // Коммунальное хоз-во городов. - Харьков, 2003. -Вып. 45. - С. 237-242.
3. Бутько, Т. В. Удосконалення управлшня про-цесом просування пойдопотошв на основi стабшзацп об^ вантажного вагону / Т. В. Бутько, О. В. Лаврухт, Ю. В. Доценко // Зб. наук. пр. Дон1ЗТ. - Донецьк, 2010. - Вип. 22. -С. 18-26.
4. Годяев, А. И. Оценка потенциально реализуемой пропускной способности железнодорожного участка / А. И. Годяев // Вестн. ВНИИЖТа. - 2004. - № 6. - C. 29-32.
5. Луханин, Н. И. К вопросу сокращения оборота вагонов / Н. И. Луханин, Г. И. Музыкина, П. В. Бех // Залiзн. трансп. Укра!ни. - 2007. -№ 4. - С. 69-71.
6. Макарочкин, А. М. Оптимизация развития пропускной способности железнодорожных линий / А. М. Макарочкин. - Москва : Транспорт, 1969. - 200 с.
7. Музишн, М. I. Вплив «вшон» на пропускну спроможтсть залiзничного напрямку / М. I. Музишн, Г. I. Нестеренко // Наука та прогрес транспорту. - 2014. - № 3 (51). - С. 24-33. doi: 10.15802/stp2014/25797.
8. Музишна, Г. I. Вплив параметрiв накопичення вагошв на !х простш на сортувальнт станци / Г. I. Музишна, Т. В. Болвановська, £. М. Жо-рова // Вюн. Дншропетр. нац. ун-ту залiзн. трансп. iм. акад. В. Лазаряна. - Дншро-петровськ, 2008. - Вип. 20. - С. 198-201.
9. Сотников, Е. А. Неравномерность грузовых перевозок в современных условиях и ее влияние на потребную пропускную способность участков / Е. А. Сотников, К. П. Шенфельд // Вестн. ВНИИЖТа. - 2011. - № 5. - С. 3-9.
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
10. Сотников, И. Б. Взаимодействие станций [Електронний ресурс] / S. Gestrelius // Licentiate и участков железных дорог / И. Б. Сотников. - thesis. Malardalen University Press Licentiate Москва : Транспорт, 1976. - 268 с. Theses, Sweden. - 2015. - 42 p. - Режим досту-
11. Шабалин, Н. Н. Оптимизация процесса пере- пу: mdh.diva-por-tal.org/smash/get/diva2:798-работки вагонов на станциях / Н. Н. Шабалин. 558/FULLTEXT01.pdf. - Назва з екрана. -- Москва : Транспорт, 1973. - 184 с. Перевiрено : 20.01.2016.
12. Яновський, П. О. Дослвдження впливу факто- 14. Railway operations, time-tabling and control / рiв на час перебування по1здв на дтницях / M. Marinov, I. Sahin, S. Ricci, G. Vasic-Franklin П. О. Яновський // Залiзн. трансп. Украши. - // Research in Transportation Economics. - 2015. 2008. - № 3. - С. 25-29. - Vol. 41, № 1. - P. 59-75. doi: 10.1016/j.ret-
13. Gestrelius, S. Mathematical models for optimising rec.2012.10.003. decision support systems in the railway industry
Г. И. НЕСТЕРЕНКО1, М. И. МУЗЫКИН2*, В. Л. ГОРОБЕЦ3, С. И. МУЗЫКИНА4
1 Каф. «Управление эксплуатационной работой», Днепропетровский национальный университет железнодорожного транспорта имени академика В. Лазаряна, ул. Лазаряна, 2, Днепропетровск, Украина, 49010, тел. +38 (056) 373 15 70, эл. почта galinamuzykina@rambler.ru, ORCID 0000-0003-1629-0201
2* Каф. «Безопасность жизнедеятельности», Днепропетровский национальный университет железнодорожного транспорта имени академика В. Лазаряна, ул. Лазаряна, 2, Днепропетровск, Украина, 49010, тел. +38 (095) 251 53 14, эл. почта grafmim@rambler.ru, ORCID 0000-0003-2938-7061
3 Каф. «Безопасность жизнедеятельности», Днепропетровский национальный университет железнодорожного транспорта имени академика В. Лазаряна, ул. Лазаряна, 2, Днепропетровск, Украина, 49010, тел. +38 (056) 793 19 08, эл. почта v-gorobets@mail.ru, ORCID 0000-0002-6537-7461
4 Каф. «Безопасность жизнедеятельности», Днепропетровский национальный университет железнодорожного транспорта имени академика В. Лазаряна, ул. Лазаряна, 2, Днепропетровск, Украина, 49010, тел. +38 (066) 082 88 27, эл. почта fufei@rambler.ru, ORCID 0000-0002-5832-6949
ИССЛЕДОВАНИЕ СТРУКТУРЫ ВАГОНОПОТОКОВ ПО ПРИБЫТИЮ И ОТПРАВЛЕНИЮ СОРТИРОВОЧНОЙ СТАНЦИИ X
Цель. Научная работа своей целью имет анализ имеющейся организации вагонопотоков по сортировочной станции с целью уменьшения простоя вагонов. Методика. Используя методы математической статистики, были построены гистограммы распределения вагонопотоков сортировочной станции и проведена оценка их параметров. Проанализировано выполнение основных количественных и качественных показателей работы станции. Для анализа влияния объема переработки на элементы простоя на станции транзитного вагона с переработкой построен график зависимости элементов простоя вагонов от объема переработки. Характер изменения кривых на графике наглядно отображает влияние объема переработки на два элемента простоя: под накоплением и в ожидании выполнения операций. Результаты. Подтверждено, что вопрос сокращения среднего времени простоя вагонов всех категорий на станции нужно решать за счет уменьшения времени непроизводительного простоя. Верное определение среднего времени нахождения на станции транзитных вагонов с переработкой имеет важное значение, тем более в условиях новой системы экономического стимулирования. Но до сих пор так и не существует отдельной методики определения простоя вагонов, которая позволяла бы объективно учитывать техническую оснащенность и технологию работы и не давала места для субъективных решений. Научная новизна. Одним из основных видов непроизводительного простоя при перевозке грузов железнодорожным транспортом является простой на сортировочных станциях в ожидании выполнения технологических операций из-за загруженности системы. Уменьшение этого показателя возможно при рациональном использовании пропускной способности сортировочных станций при условии рационального распределения вагоно- и поездопотоков между основными сортировочными станциями Укрзализныци. Практическая значимость. Анализ изменения элементов простоя в зависимости от объема переработки позволяет не только целенаправленно определять методы по сокращению простоя вагонов, но и осуществлять точную оценку работы коллектива станции, а также корректировать норму простоя вагонов.
Наука та прогрес транспорту. Вкник Дншропетровського нащонального ушверситету залiзничного транспорту, 2016, № 1 (61)
Ключевые слова: вагонопоток; сортировочная станция; объем переработки; простой вагонов; параметр накопления.
Г. I. НЕСТЕРЕНКО1, М. I. МУЗИЮН2*, В. Л. ГОРОБЕЦЬ3, С. I. МУЗИЮНА4
'Каф. «Управлшня експлуатацшною роботою», Днiпропетровський нацiональний ун1верситет залiзничного транспорту iменi академжа В. Лазаряна, вул. Лазаряна, 2, Днгпропетровськ, Укра!на, 49010, тел. +38 (056) 373 15 70, ел. пошта galinamuzykina@rambler.ru, ORCID 0000-0003-1629-0201
2*Каф. «Безпека жип^яльносп», Дшпропетровський нацiональний унiверситет залiзничного транспорту iменi академжа В. Лазаряна, вул. Лазаряна, 2, Дншропетровськ, Украша, 49010, тел. +38 (095) 251 53 14, ел. пошта grafmim@rambler.ru, ORCID 0000-0003-2938-7061
3Каф. «Безпека життедшльностЬ>, Дшпропетровський нацюнальний утверситет залiзничного транспорту iменi академжа В. Лазаряна, вул. Лазаряна, 2, Дншропетровськ, Украша, 49010, тел. +38 (056) 793 19 08, ел. пошта v-gorobets@mail.ru, ORCID 0000-0002-6537-7461
4Каф. «Безпека життедшльноста», Дшпропетровський нацюнальний утверситет залiзничного транспорту iменi академжа В. Лазаряна, вул. Лазаряна, 2, Дншропетровськ, Украша, 49010, тел. +38 (066) 082 88 27, ел. пошта fufei@rambler.ru, ORCID 0000-0002-5832-6949
ДОСЛ1ДЖЕННЯ СТРУКТУРИ ВАГОНОПОТОК1В ПО ПРИБУТТ1 ТА В1ДПРАВЛЕНН1 СОРТУВАЛЬНО1 СТАНЦП X
Мета. Наукова робота мае за мету аналiз наявно! оргашзацп вагонопоток1в по сортувальнш станци iз метою зменшення простою вагошв. Методика. Використовуючи методи математично! статистики, були побудованi гiстограми розподшу вагонопоток1в сортувально! станци та проведено оцшювання !х параметрiв. Проаналiзовано виконання основних кiлькiсних та як1сних показнишв роботи станцп. Для аналiзу впливу об'ему переробки на елементи простою на станци транзитного вагону iз переробкою побуду вано графiк залежностi елеменпв простою вагонiв ввд об'ему переробки. Характер змши кривих на граф^ наглядно вiдображуе вплив об'ему переробки на два елементи простою: тд накопиченням та в очiкуваннi виконання операцт. Результата. Пiдтверджено, що питання скорочення середнього часу простою вагошв уах категорiй на станцп потрiбно вирiшувати за рахунок зменшення часу непродуктивного простою. Вiрне визначення середнього часу знаходження на станци транзитних вагонiв iз переробкою мае важливе значения, тим паче в умовах ново! системи економiчного стимулювання. Але до цього часу так i немае окремо! методики визначення простою вагошв, яка б дозволяла об'ективно враховувати технчну оснащешсть та технолопю роботи i не давала мюця для суб'ективних рiшень. Наукова новизна. Одним iз основних видiв непродуктивного простою при перевезенш вантаж1в залiзничним транспортом е простiй на сортувальних стаицiях в очiкуваннi виконання технолопчних операцiй через завантаженiсть системи. Зменшення цього показника можливе при рацюнальному використаннi пропускно! спроможиостi сортувальних станцш за умови рацiонального розподiлу вагоно- та попдопотошв м1ж основними сортувальними станцiями Укрзалiзницi. Практична значимiсть. Аналiз змiни елементiв простою в залежносп вгд об'ему переробки дозволяе не тшьки цiлеспрямоваио визначати методи по скороченню простою вагонiв, але й здшснювати вiрну оцiнку роботи колективу станци, а також корегувати норму простою вагошв.
Ключовi слова: вагонопопк; сортувальна стаицiя; об'ем переробки; простш вагонiв; параметр накопичення.
REFERENCES
1. Bogdanov V.M. Rezervy propusknoy i provoznoy sposobnosti [Reserves of carriage and traffic capacity]. Zheleznodorozhnyy transport - Railway Transport, 2008, no. 8, pp. 54-56.
2. Butko T.V., Danko M.I., Sikonenko H.M. Do pytannia vyznachennia optymalnoi kilkosti sortuvalnykh stantsii [To the question of determining the optimal number of sorting yards]. Kommunalnoye khozyaystvo gorodov -Municipal Infrastructure of Cities, 2003, issue 45, pp. 237-242.
3. Butko T.V., Lavrukhin O.V., Dotsenko Yu.V. Udoskonalennia upravlinnia protsesom prosuvannia po-izdopotokiv na osnovi stabilizatsii obihu vantazhnoho vahonu [Improving governance in the process of moving the train flows on the basis of stabilization of the turnover of the freight car]. Zbirnyk naukovykh prats
Наука та прогрес транспорту. Вкник Дншропетровського нацюнального ушверситету залiзничного транспорту, 2016, № 1 (61)
Donetskoho instytutu zaliznychnoho transportu [Proc. of the Donetsk Institute of Railway Ttransport]. Donetsk, 2010, issue 22, pp. 18-26.
4. Godyaev A.I. Otsenka potentsialno realizuemoy propusknoy sposobnosti zheleznodorozhnogo uchastka [Evaluation of potentially feasible throughput capacity of the railway section]. Vestnik Vserossiyskogo nauchno-issledovatelskogo instituta zheleznodorozhnogo transporta [Bulletin of All-Russian Research Institute of Railway Transport]. Moscow, 2004, no. 6, pp. 29-32.
5. Lukhanin N.I., Muzykina G.I., Bekh P.V. K voprosu sokrashcheniya oborota vagonov [To the reduction of rail car turnover]. Zaliznychnyi transport Ukrainy - Railway Transport of Ukraine, 2007, no. 4, pp. 69-71.
6. Makarochkin A.M. Optimizatsiya razvitiya propusknoy sposobnosti zheleznodorozhnykh liniy [Optimization of the development of the capacity of rail lines]. Moscow, Transport Publ., 1969. 200 p.
7. Muzykin M.I., Nesterenko H.I. Vplyv «vikon» na propusknu spromozhnist zaliznychnoho napriamku [Influence of maintenance windows on the working capacity of railway route]. Nauka taprohres transportu -Science and Transport Progress, 2014, no. 3 (51), pp. 24-33. doi: 10.15802/stp2014/25797.
8. Muzykina H.I., Bolvanovska T.V., Zhorova Ye.M. Vplyv parametriv nakopy-chennia vahoniv na yikh prostii na sortuvalnii stantsii [The influence of cars acquisition parameters on their idle hours on marshalling yard]. Visnyk Dnipropetrovskoho natsionalnoho universytetu zaliznychnoho transportu imeni akademika V. Lazariana [Bulletin of Dnipropetrovsk national University of railway transport named after Academician V. Lazaryan], 2008, issue 20, pp. 198-201.
9. Sotnikov Ye.A., Shenfeld K.P. Neravnomernost gruzovykh perevozok v sovremennykh usloviyakh i yeye vliyaniye na potrebnuyu propusknuyu sposobnost uchastkov [The unevenness of freight transport in modern conditions and its impact on the needs of capacity areas]. Vestnik Vserossiyskogo nauchno-issledovatelskogo instituta zheleznodorozhnogo transporta [Bulletin of All-Russian Research Institute of Railway Transport], 2011, no. 5, pp. 3-9.
10. Sotnikov I.B. Vzaimodeystviye stantsiy i uchastkov zheleznykh dorog [The interaction of stations and railways]. Moscow, Transport Publ., 1976. 268 p.
11. Shabalin N.N. Optimizatsiya protsessa pererabotki vagonov na stantsiyakh [Optimization of recycling process of cars at stations]. Moscow, Transport Publ., 1973. 184 p.
12. Yanovskyi P.O. Doslidzhennia vplyvu faktoriv na chas perebuvannia poizdiv na dilnytsiakh [Research of influence factors on the time of trains at stations]. Zaliznychnyi transport Ukrainy - Railway Transport of Ukraine, 2008, no. 3, pp. 25-29.
13. Gestrelius S. Mathematical models for optimising decision support systems in the railway industry. Licentiate thesis. Malardalen University Press Licentiate Theses, Sweden, 2015. 42 p. Available at: mdh.diva-por-tal.org/smash/get/diva2:798558/FULLTEXT01.pdf (Accessed 20 January 2016).
14. Marinov M., Sahin I., Ricci S., Vasic-Franklin G. Railway operations, time-tabling and control. Research in Transportation Economics, 2015, vol. 41, no. 1, pp. 59-75. doi:10.1016/j.retrec.2012.10.003.
Prof. V. I. Bobrovskyi, Dr. Sc. (Tech.) (Ukraine); Prof. T. V. Butko, Dr. Sc. (Tech.) (Ukraine) recommended this article to be published
Accessed: Nov. 20, 2015
Received: Jan. 21, 2016
