DRAFT CONCEPT NOTE

ASSET ACQUISITION AND SUSTAINABLE UTILISATION

Identifying possible principles for acquisition of assets, that would lead to a sustainable railway, issues of financial
sustainability, efficient and effective use and maintenance of assets. Developing a suitable approach to optimize the
acquisition and thereafter maximizing productivity of various movable and immovable assets.

Key words /phrases

Financial Sustainability, optimize asset acquisition, maximizing productivity, moveable & immoveable assets.

Executive Summary

Currently, acquisition of assets is mainly by in-house procurement. Maintenance is undertaken either departmentally or
through outsourcing which is highly dependent on manual interventions at all stages leading to over or under
maintenance. The purpose of this study is to explore financial sustainability by improving the acquisition, utilization, and
maintenance of assets. The topic is broadly classified into

I. Asset acquisition and II. Sustainable utilization and maintenance of assets.

The study attempts to explore policy for future procurement/ Shift from creation and maintenance of assets from
traditional methods. In recent times, a gradual shift towards data- driven maintenance is taken up to reduce the cost of
maintenance and improve the utilisation of assets. Further the study would emphasize on reliability of upcoming
methods of maintenance such as outcome-based maintenance, preventive maintenance, integrated maintenance of
Vande Bharat which combines the procurement and maintenance of the assets in a single concession agreement.

BACKGROUND

1.National Rail plan (NRP) seeks to develop capacity by 2030 that will cater to growing demand up to 2050. NRP
establishes that pushing the capacity envelope will result in accommodating peak level fluctuations, addressing constant
demand growth, increasing efficiency and profitability.

2. An analysis of investments made by the Indian Railways in the past decades and Net Traffic Receipts (Surplus) during
the corresponding periods are depicted in Table 1.

Investments made and surplus Revenue generated by Indian Railway assets Table 1
As on 1950-51 1960- 1970- 1980-81 1990-91 2000-01 2010-11 2020-21
March 31 61 71
Investmen 855.2 1868.6 4099.4 7,448. 22200.5 63341.01 2,31,615.25 6,70,725.78
t (Cr) 40
Surplus 15.05 32.01 -19.84 -197.87 175.67 763.59 1,404.89 2,547.48
(Cr)
Surplus as 1.76% 1.71% -0.48% -2.65% 0.79% 1.21% 0.61% 0.38%
a % over
investment
The above table reveals that the assets created do not generate enough surplus.

3. A relook at the principles employed for acquiring and maintaining assets is imperative to ensure sustainable
incremental Revenue generation. The earnings per coach and per wagon during the past few years is at Table 2.

Table 2

Year 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21
Earnings 4 5
per coach 9,03,566 5,02,470 61,53,913 63,18,470 65,19,779 67,72,433 69,00,666 65,81,330 19,09,939

Earnings 3 36 4 42, 3 3 4 3 38,

per wagon 4,09,832 ,21,792 0,58,773 55,578 6,70,171 9,23,968 2,38,966 8,04,373 24,494

The trend depicts that barring aberrations during covid period, Earnings per coach has increased slowly. But there has
been a decrease in the per wagon earning over the previous year in many instances.
Pictorial of Trend of earnings per coach and per wagon(Crs) Chart 1

Trend of earnings per coach and wagon

8,000,000
6,772,433 6,900,666
Earnings per Rolling stock in Crs

7,000,000 6,519,779 6,581,330

6,153,913 6,318,470
6,000,000 5,502,470
4,903,566
5,000,000
4,058,773 4,255,578 4,238,966
3,923,968 3,804,373 3,824,494
4,000,000 3,621,792 3,670,171
3,409,832
3,000,000
1,909,939
2,000,000
1,000,000
-
2012-13 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21

Year

Earnings per Coach Earnings per wagon

The fluctuations in per wagon earnings clearly indicate the need for a relook at the policies governing procurement and
utilization of wagons. Table 3 below shows that freight Revenues contribute the lion’s share of our Revenues and that
performance of Wagons is a crucial parameter deciding financial viability of Railways.

Revenues from passenger and freight traffic (Crs) Table 3

Year 2012- 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21
13
Passenger 31323 36532 42190 44283 46280 48643 51067 50669 15248
earnings

Freight earnings 83479 91571 1,03,100 1,06,941 1,02,028 1,13,524 1,22,580 1,11,472 1,15,738
excl wharfage &
demurrage

Freight earnings 72.72 71.48 70.96 70.72 68.79 70.00 70.59 68.75 88.36
as % of Total
Earning

4. Comprehensive Logistics Action Plan (CLAP) for the implementation of the National Logistics Policy (NLP) prescribes
specific key action areas which inter-alia includes standardization of physical assets. The proposed inter-operability
across modes/asset classes calls for a relook at the way we manage assets. NLP targets to reduce cost of logistics in
India to be comparable to global benchmarks by 2030 which means cheaper ways of asset acquisition need to be
explored for Railways to stay viable. The NLP also envisages a GHG Calculator to calculate carbon emission data per
shipment basis on the mode of transport and also use of a Comparative Freight Index for comparing freights between
road and rail. This means that Railways should put in place greener and cheaper options urgently.

5. Indian Railways should grab the opportunity to be flag bearers of ethical investing. Commerce and industry is slowly
migrating to Environmental, social, and governance (ESG) principles. Indian Railways should also start adopting socially
responsible investment (SRI) or sustainable investment principles, keeping in mind the futuristic green compliances that
will likely be expected out of our assets in near future.

METHODOLOGY

● Identifying under-utilisation and inefficiencies of various assets through specific case studies
 ● Studying the trends and patterns of parameters for the past few decades/ recent years.
Deliverables

● Identifying principles of acquisition of assets

● Exploring sustainable alternate models for asset acquisition and maintenance

1. PRINCIPLES IDENTIFIED FOR ASSET ACQUISITION

1.Restricting procurement of assets to the extent leasing is possible.

1.a.i Wet-leasing of Rolling Stock TO ENCOURAGE PRIVATE PARTICIPATION IN TRAIN OPERATIONS

A SNAPSHOT OF RAILWAYS ROLLING STOCK ON INDIAN RAILWAYS: 2020-21 2021-2022

SOURCE:INDIAN RAILWAYS YEAR BOOK 2021-22

PRESENT MODEL OF ACQUISITION OF ROLLING STOCK

Indian Railways does not own ninety percent of the rolling stock operating over IR. Locomotives and coaches
running on railways’ track are owned by IR’s financial arm, Indian Railway Finance Corporation (IRFC). To procure the
stock, IRFC borrows money from domestic and global markets, purchases the rolling stock and then leases it to IR. This is
a ‘financial lease’ where Railways decides which rolling stock to buy and directs IRFC to buy it from Railways’ Production
Units (PU) and lease it back to Indian Railways. Thus, leasing in the form of ‘lease-back model’ is already an embedded
idea in the Indian rolling stock landscape.

This model, however, is limited to the Ministry of Railways (MoR) as all three parties, the PU manufacturing the rolling
stock, the procurer, and the financier, all belong to the same promoter, namely, the MoR. The idea of Wet Leasing of
trains is an improvisation over the existing model and is aimed at increasing private participation in different segments
of the railway sector. Wet Leasing means that the ‘New Leasing Entity’ would not only lease the rolling stock to IR but
also be responsible for repair, maintenance and overhauling of the rolling stock, and for the crew operating the trains.
Thus, it is a structural shift from the ‘financial lease model’ to ‘operating lease model’ and can have tangible benefits in
the railway sector some of which are Encouraging Private Players in Train operations,Up-gradation of Rolling stock by
scouting for the latest rolling stock,Reduce Cost of Rolling Stock by having bargaining power,Attracting Global Investors
and Development,Corporate capital structure,Capturing South Asian and African Markets.

In the light of the above, it is time to look at Wet Leasing as a suitable financial inter-mediation option. The
beauty of this model is that it is achievable in a short span of time and has the potential to create an entity with
professional and independent expertise. Its global governance structure will bring huge benefits to the railway sector in
India which, for far too long, has been influenced by a monolithic entity known as Indian Railways. If the current
government’s policy goal of Atmanirbhar Bharat is to be realised, it is time to give private players (Rolling stock
producers and train operators) a fair opportunity to enter into the rail market. Wet Leasing is a major component of this
policy goal.

1.a.ii LEASING OF TRACK MACHINES VIA PLANT AND EQUIPMENT LESSORS

Like trains, track machines can also be taken on lease model which will result in following benefits:
1. Reduce upfront cost for acquiring these machines.
2. Reduce the maintenance cost of maintaining these machines which is 2 to 3 percent of their initial capital cost
3. Reduce idling of track machines as zones will be directly billed for usage and idling will become directly
accountable.
4. Will allow Big private players to construct new lines independently without requesting Indian railways for track
machines.
5. Will reduce the capital invested on track machine depots
6. Will optimize acquisition of track machines.

Sample data of Track machines in SCR is at ANNEXURE 2 . Further the data of no. of track machines, total capital outlay
on track machines, total maintenance expenditure of track machine maintenance, track machine idling time for Indian
Railways are being collected.Global experience on leasing and its applicability to Indian context are attached as
ANNEXURE 3 which proves Track machines Leasing can be path breaking in reducing upfront capital investment,
improving asset utilization and creation of big private track maintenance companies in India.

1.b. Concessioning reduces front end capital costs to the concessionaire who uses public assets in return for a profit
share and a commitment to reinvest in the railway. Concessions also provide an instrument that the government can
use to contract out the operation of inherently unprofitable services, by asking concessionaires to bid on a minimum
subsidy rather than a minimum profit-share basis.

2. Applying futuristic concepts of Asset acquisition and Sustainable financing:

Indian railways need a paradigm change in investment decisions on asset creation and we need it right now.
This means shifting from traditional ROR based decisions (which gives only macro-economic sustainability perspective)
to assessment of sustainable value creation (which gives a triple bottom line (TBL) perspective. Investment decisions
that take into account the environmental, social, and governance (ESG) factors of a project/asset is required.

India aims for 500 GW of renewable energy installed capacity by 2030. India also aims to achieve net zero Carbon
emissions by 2070.Decarbonisation of the transport sector necessary to achieve Paris Agreement targets. Indian
Railways have to be the driving engine for these targets for which we need to explore Green Financing options. IRFC has
launched bonds offering to be utilized for green end uses as iterated in IRFC’s Green Framework for Green Debt
Financing which has been duly certified by Climate Bonds Initiatives. Green bonds provide a sustainable alternative
means of financing for Indian Railways, reducing dependence on central and state grants and will also bring in new
foreign investors who specialise in sustainable financing for investment in projects with environmental, social and
governance considerations.

Triple Bottom Line approach

Triple Bottom Line (TBL) reporting is becoming an accepted approach for organisations world over to demonstrate they
have strategies for sustainable growth. TBL accounting expands the traditional reporting framework to take into
account social and environmental performance in addition to financial performance. The phrase, "people, planet, and
profit" describes the triple bottom line :

1.People, the social equity bottom line : A reciprocal social structure in which the well-being of organisation, labour and
other stakeholder interests are interdependent. Quantifying this bottom line is relatively new, problematic and often
subjective. The Global Reporting Initiative (GRI) has developed guidelines to comparably report on the social impact of a
business.
2.Planet, the environmental bottom line : This refers to sustainable environmental practices to benefit the natural order
as much as possible or at the least do no harm and minimize environmental impact. A TBL endeavour reduces
its ecological footprint by, among other things, carefully managing its consumption of energy and non-renewables.
"Cradle to grave" is uppermost in the thoughts of TBL organisations, which typically conduct a life cycle assessment of
products to determine what the true environmental cost is till eventual disposal by the end user.
3.Profit, the economic bottom line: It deals with the economic value created by the organization after deducting the
cost of all inputs, including the cost of the capital tied up. It therefore differs from traditional accounting definitions of
profit. In the original concept, within a sustainability framework, the "profit" aspect needs to be seen as the real
economic benefit enjoyed by the host society. It is the real economic impact the organization has on its economic
environment.

Case study on TBL in transportation sector :US Department of transportation -Federal highway administration

Case study will highlight how FHWA has incorporated sustainability into a wide variety of programs, projects, policies,
processes including Infrastructure Voluntary Evaluation Sustainability Tool, forming Sustainability Working Group and 8
action areas identified.

Examples of possibilities in Indian Railways

Investment on Standardized designs for green buildings, Umbrella work for Ground water recharging arrangements
wherever feasible, Projects for tapping non renewable energy sources, make choices of assets that give maximum
carbon credits.

2. UTILISATION AND MAINTENANCE OF ASSETS

The expenditure incurred for maintenance of Coaches and wagons is shown in Table 4.

Expenditure incurred for maintenance of Coaches and wagons Table 4

Year 2013-14 2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21
Earnings per 55, 61 63 65
coach 02,470 ,53,913 ,18,470 ,19,779 67,72,433 69,00,666 65,81,330 19,09,939

Repairs & 10,82,332 11,47,799 11,77,397 13,72,361 14,21,454 14,63,466 14,63,466 13,42,630
Maintenance
Expenditure per
coach

Percentage of 19.67 18.65 18.63 21.05 20.99 21.21 22.44 70.30

expenditure per
coach wrt
earnings per
coach
Earnings per 36,2 40, 42,5 36, 39, 42, 38, 38,
wagon 1,792 58,773 5,578 70,171 23,968 38,966 04,373 24,494

Expenditure on 87362.41 91744.68 100076 102380.3 109470.2 112711.7 126708.9 120291.5

repairs and
maintenance per
wagon

Percentage of 2.41 2.26 2.35 2.79 2.79 2.66 3.33 3.15

expenditure per
wagon w.r.t
earnings per
wagon

Total 9394.63 10199.56 10766.65 12587.66 13376.65 14089.43 15082.1 14359.2

Expenditure on
repairs &
maintenance(Cr)

R&M 251.17 133.07 102.48 256.21 803.11 373.34 948.79 563.66

expenditure as a
% of surplus
generated

R&M 7.33 7.02 7.12 8.49 8.25 8.11 9.30 10.96

expenditure as a
% of total
earnings from
coaching and
freight

Optimal use and maintenance of assets is required for profitable operations, for which suggestions as below
are being made.

2. a. AI/ML in efficient and sustainable utilization of assets in Railways

Artificial intelligence (AI) and machine learning (ML) are two closely related fields of computer science that are
revolutionizing many industries, including asset management.

AI can play a crucial role in sustainable asset acquisition and management for Indian Railways by improving
efficiency, reducing costs, and minimizing environmental impact. Here are several ways AI can contribute to these
efforts:

2. a. 1. Predictive Maintenance:

Predictive maintenance of railway assets is a process of using data and analytics to predict when an asset is likely to fail
so that maintenance can be scheduled before the failure occurs. This can help to reduce downtime, improve safety, and
extend the lifespan of assets.There are various data sources that can be used for predictive maintenance of railway
assets, including:

● Sensor data: A study indicates that nearly 30 percent of the total delay time caused in the Airline Industry is
due to unplanned maintenance. Hence, Carriers have started to deploy predictive maintenance solutions to
better manage data from aircraft health monitoring sensors of critical components. The same approach can be
applied in the case of IR as well with suitable modifications.
● Inspection data: Inspection data can be used to track the condition of assets over time. This data can be used
to identify trends that may indicate a potential problem
● Historical failure data: is of importance here as this can be generated from the already available data available
with the organisation and is getting populated in the various IT platforms used by the organisation.

Once the data has been collected, it can be analysed using a variety of different machine-learning techniques to develop
predictive models. A hybrid model of historical and real-time (sensor based) data can very accurately predict the
maintenance requirements. These models can then be used to predict when an asset is likely to fail so that maintenance
can be scheduled before the failure occursSome examples of areas where predictive maintenance can be used for
railway assets:

● Predictive maintenance of locomotives

● Predictive maintenance of tracks
● Predictive maintenance of signalling systems
● Predictive maintenance of Bridges and Tunnels

Overall, predictive maintenance is a powerful tool that can be used to improve the efficiency, safety, and reliability of
railway operations. By using predictive maintenance to predict when assets are likely to fail, railway operators can avoid
costly downtime and improve the overall quality of their service.Other areas of AI/ML optimisation include:

2.a. 2. Energy Optimization in Traction system and energy load prediction : AI can optimize energy consumption by
analysing historical data and current conditions to adjust train schedules, speed, and energy usage. This can lead to
significant energy savings, reducing the carbon footprint of the railways.

2a 3. Asset Lifecycle Management : AI can assist in tracking the entire lifecycle of railway assets, from procurement to
decommissioning. It can help in making data-driven decisions regarding asset replacement or refurbishment to ensure
sustainability and cost-effectiveness.

2a 4. Route Optimization : AI can optimize train routing and scheduling to save time, money, energy and emissions.
However this area is not explored as this is falling outside the purview of the mandate of the group.

2a 5. Inventory Management : AI-driven inventory management systems can optimize the procurement of spare parts
and materials, reducing waste and overstocking. This can lead to cost savings and a more sustainable supply chain.
However, this area is not explored as this is falling outside the purview of the mandate of the group.

Al case study of predictive maintenance used by a Private player in Canadian Railways is attached as Annexure 4.

3. The Vande Bharat Digital & Logistics Platform

A Holistic, Integrated, Single-Point, Specialized, State-of-the-art Data Centre cum Control Room cum R&D Lab of the
Vande Bharat Platform Rolling Stock for integrating different verticals : 1. Real time tracking over IR (Asset Registration,
Maintenance) so that each & every trainset & coach being accounted for and monitored during its codal life. 2.
Controlling Quality & Standardization in VBP Production Schedules 3. Effective & efficient maintenance across IR
through optimization of supply and inventory management 4. Collation and Introduction of Design Upgrades in
Production by establishing R&D Lab for failure analysis of components etc.

Conclusion: Indian Railways has been entrusted with a major responsibility to carry the nation forward as per the Gati
Shakti policy envisioned for the country. This responsibility not only includes creation of assets for capacity building but
also needs sustainable investments that can carry forward the vision so that the nation can rely upon a faster,
accessible, and affordable transportation model. In this draft concept note the team has explored ways to carry out the
above mandate. The note has discussed briefly about the various modes of acquisition of assets mainly through
engagement of private players, substantiated by global case studies. Leasing of coaches, wagons and Track machines
are discussed. In addition to this the note has also touched upon evaluating asset acquisition in terms of Triple Bottom
Line (TBL) where the traditional financial returns are augmented by the social and environmental aspects as well. This
new approach is very much in alignment with the climatic and environmental responsibilities and commitments taken
upon by the nations. In the utilisation and maintenance of assets part the note has discussed the need to move towards
predictive maintenance which can bring operational and financial efficiency in the asset maintenance ecosystem.
Application of Machine Learning and Artificial Intelligence have also been discussed. This approach is of particular
interest since IR is moving towards adoption of modern technologies in its rolling stock assets such as Vande Bharat
train sets.
 LIST OF MOVABLE AND IMMOVABLE ASSETS ANNEXURE 1

Sl no Fixed Asset Sl No Current Asset

1 Lands 1 Cash and Cash Equivalents

2 Buildings 2 Advance to Employees

3 Bridges/Flyover/Tunnel/Subways 3 Loans and Advances

4 Roads/Streets 4 Earnest money and Security Deposit

6 Furniture and Fixtures 5 Transfer Certificate (TC) Debit

7 Office Equipments 6 Transfer Certificate (TC) Credit

8 Vehicles 7 Siding charges

9 Plant, Machinery & Equipments 8 Bank Balances

10 Computers and Peripherals 9 Cash and Cash Equivalents

11 Medical Equipments 10 Inventory/Closing Stock

13 Capital Work in Progress 10A Diesel at Railway Diesel Institution

14 Plant, Machinery & Equipments 11 Imprest

(Signalling)

15 Plant, Machinery & Equipments 12 Receivable

(Telecom)

16 Electrical Equipments & Fittings 13 Foreign Service Contribution

17 Intangible Assets 14 Advance Against State Railway Provident

Fund

18A Conductors (Wire) 15 Warranty Charges

18B Transformer

18C Mast/Portal Structure

18D Other Equipments

 ANNEXURE 2

A GLIMPSE OF TRACK MACHINE DATA AS AVAILABLE ON SCR IS GIVEN AS BELOW:

Track Machine Initial Cost

Machine Year of
S. No Div Machine No Initial Cost in Rs. Codal life PB Cost in Crs
Type commissioning

A B C D E F G H

1 SC 3X 3957 07.08.2000 87535491

20 Yrs 10.26
2 BZA 3X 3968 01.05.2015 177443640

3X AVG 132489565

3 GTL CSM 904 01.09.1989 82900000

4 SC CSM 930 11.09.1991 82900000

5 BZA CSM 933 12.12.1992 82900000

6 BZA CSM 934 23.04.1993 82900000

20 Yrs
7 GTL CSM 937 23.04.1993 82900000

8 HYB CSM 940 20.08.1993 82900000

9 NED CSM 948 22.08.1985 82900000

10 GNT CSM 968 29.02.2016 18321077

CSM AVG 74827635

11 SC DUO 3320 25.01.2003 37226520

12 GTL DUO 8057 21.06.2003 53362546

13 NED DUO 8062 15.07.2003 64424067

14 BZA DUO 8067 10.08.2006 62435299

15 HYB DUO 8093 02.12.2010 59676716

16 GTL DUO 8115 05.12.2010 16527720

20 Yrs
17 SC DUO 8126 15.02.2009 38928601

18 BZA DUO VPR-M52 26.03.2013 33179641

19 SC DUO VPR-M58 05.07.2013 33179641

20 BZA DUO VPR-M61 30.10.2013 33179641

21 GTL DUO 8147 12.02.2019 60000000

22 HYB DUO 56600 06.11.2019 57000000

DUO AVG 45760033

23 HYB BCM 289 16.02.1990 105920569 20 Yrs 14.56
24 HYB BCM 290 04.05.1990 105920569

25 BZA BCM 339 10.07.2003 105920569

26 SC BCM 346 08.09.2004 151748685

27 SC BCM 363 20.09.2006 148338183

28 BZA BCM 367 20.06.2007 156326630

29 GTL BCM 379 27.11.2009 44277205

30 GTL BCM 394 05.06.2013 54551953

31 BZA BCM 403 26.12.2015 87582013

32 SC BCM 705 19.09.2016 144006826

33 GTL BCM 717 03.02.2018 201842897

BCM AVG 118766918

34 SC FRM 1874 20.07.1999 84481612

35 BZA FRM 1880 01.11.2002 83655340

20 Yrs 17.00
36 GTL FRM 1888 08.11.2004 102723799

37 HYB FRM 56413 15.11.2019 230000000

FRM AVG 125215188

38 BZA BRM 105 01.10.1990 10000000

39 HYB BRM 111 05.02.1995 10000000

40 NED BRM 121 02.03.1990 10000000

41 SC BRM R 16 21.11.2009 38928601 20 Yrs 5.00

42 SC BRM R 11 17.12.2011 160549087

43 GNT BRM R 23 20.09.2012 13300000

44 GTL BRM R 39 22.04.2015 33179641

BRM AVG 39422476

45 HYB DGS 336 13.05.1995 58000000 20 Yrs 7.46

46 NED DGS 341 14.01.1996 58000000

47 GTL DGS 359 18.04.2003 59390642

48 SC DGS 375 04.02.2005 63588251

49 BZA DGS 387 09.07.2006 64021342

50 SC DGS 395 15.07.2009 37226520

51 SC DGS 418 16.02.2012 56919840

52 GTL DGS 425 22.08.2012 34372895

53 BZA DGS 429 01.06.2012 44277205

54 GNT DGS 434 17.07.2012 44277205
55 HYB DGS 437 30.10.2013 54551953

56 BZA DGS 442 06.05.2014 54551953

DGS AVG 52431484

255 1991 3500000

57 SC PQRS 251 1991 3500000

256 1991 3500000

114

115
58 BZA PQRS 10500000
251 1991

256 1991

5/225 1991 3500000

59 SC PQRS 6/226 1991 3500000 20 Yrs 2.5

242 1988 3500000

1/203 1981 3500000

60 NED PQRS 4/219 1981 3500000

4/220 1981 3500000

49 & 50 2018 17700000

61 BZA PQRS
257 1991 3500000

62 BZA PQRS 77 & 78 2019 17700000

63 BZA PQRS 87 & 88 2020 17700000

PQRS AVG 14080000

64 HYB UNIMAT 8249 30.01.1990 64800000

65 GTL UNIMAT 8253 09.07.1992 64800000

66 NED UNIMAT 8256 11.03.1991 64800000

67 BZA UNIMAT 8265 05.01.1993 64800000

68 GTL UNIMAT 8278 28.06.1997 64800000

69 GNT UNIMAT 8282 29.06.1998 76590952 20 Yrs 16.5

70 SC UNIMAT 8288 10.01.1999 76590952

71 SC UNIMAT 8308 25.11.2007 95834249

72 BZA UNIMAT 8417 17.02.2015 168408537

74 SC MPT 56569 Jul 2020 190000000

75 BZA MPT 56584 Jul 2020 190000000

UNIMAT AVG 101947699

76 SC PRC-T.28 3&4 25.08.1994 15000000 20 Yrs 10.34

77 BZA PRC-T.28 9&11 01.11.1993 15000000

78 GTL PRC-T.28 10&12 01.07.2009 15000000

PRC-T.28 AVG 15000000

79 BZA UTV 002 15.03.2008 8200085

80 BZA UTV 013 26.05.2009 10071165

81 SC UTV '018 01.09.2009 10196813

82 SC UTV 030 16.02.2012 9174149

83 HYB UTV 5005 24.06.2005 8200085

25 Yrs 1.5
84 SC UTV 222 10.04.2007 8012373

85 GTL UTV 2015 24.04.2012 9000000

86 GTL UTV 3038 16.06.2003 10071165

87 NED UTV 9050 01.12.2013 10196813

88 GNT UTV 9051 15.11.2013 10221611

UTV AVG 9334426

ANNEXURE 3
Case studies on leasing in global rail sector
USA:
In the United States, there are several major track equipment leasing companies that specialize in providing track
maintenance and construction equipment to railway operators, contractors, and other organizations in the railroad
industry. These leasing companies offer a wide range of track machines and equipment for lease. Here are some of the
major track equipment leasing companies in the USA:

1. Progress Rail: Progress Rail, a Caterpillar company, offers equipment leasing services for a variety of
rail-related equipment, including track maintenance machines and locomotives.
2. Holland Company: Holland provides not only track maintenance and inspection services but also
leases track maintenance equipment to railroads and contractors for their maintenance and
construction needs.
3. Loram Maintenance of Way, Inc.: Loram, known for its rail grinding and maintenance services, also
provides equipment leasing solutions for rail grinding machines, ballast regulators, and other track
maintenance equipment.
4. Herzog Railroad Services, Inc.: Herzog offers a wide range of railroad services, including track
maintenance equipment leasing, making equipment available for specific projects or long-term needs.
5. Rail Construction Equipment Co. (RCE): RCE specializes in track equipment leasing and provides a
variety of equipment for track construction and maintenance, including regulators, tie inserters, and
tie exchangers.
6. R. J. Corman Railroad Group: R.J. Corman offers track construction, maintenance, and emergency
response services and provides equipment leasing options to support these operations.
7. Danella Rental Systems: Danella Rental Systems provides track maintenance equipment leasing and
services, including equipment such as regulators, tie handlers, and tampers.
8. NMC Railway Systems: NMC Railway Systems offers leasing solutions for track maintenance
equipment and machines, including regulators, undercutters, and tie inserters.
9. MERMec Inc.: MERMec specializes in track inspection and measurement equipment and offers leasing
options for inspection cars and related machinery.
10. Geismar North America: Geismar provides railway maintenance equipment, including tamping
machines and welding equipment, which may be available for lease.

These companies offer a range of track machines and equipment, including regulators, tampers, ballast regulators, and
other specialized machines used for track maintenance, construction, and inspection. The specific leasing terms and
equipment availability can vary among these companies, so railway operators and contractors often work with them
based on their specific project needs and requirements.

EUROPE:
In Europe, there are several track equipment leasing companies that provide track maintenance and construction
equipment to railway operators, contractors, and other organizations in the railroad industry. These companies offer a
wide range of track machines and equipment for lease to support railway maintenance and construction projects. Here
are some of the major track equipment leasing companies in Europe:

1. Belequipment Limited: Belequipment, based in the United Kingdom, offers track equipment leasing services,
including tamper machines, regulators, and other track maintenance equipment.
2. Colas Rail: Colas Rail, a major railway infrastructure company, provides track maintenance and construction
services and offers equipment leasing solutions for various track machines and equipment.
3. Plasser & Theurer: Plasser & Theurer is a leading manufacturer of track maintenance machines, and in addition
to manufacturing, they may offer leasing options for their equipment.
4. SRS Sjölanders AB: SRS Sjölanders, based in Sweden, specializes in the lease and rental of railway maintenance
machines, including regulators and ballast cleaning machines.
5. EM Spoor: EM Spoor, located in the Netherlands, offers a range of railway machinery, including tamping
machines and ballast regulators, for lease to railway operators and contractors.
6. Raillogix: Raillogix, based in the Netherlands, provides rail logistics services and offers equipment leasing for
various railway machines and equipment.
7. JumboTec: JumboTec, based in Germany, offers leasing services for track maintenance and construction
equipment, including tamping machines and ballast regulators.
8. GRAWIMAN: GRAWIMAN, located in Poland, specializes in the lease and rental of track maintenance
machines, including regulators, tampers, and ballast regulators.
9. Sersa Group: Sersa Group, based in Switzerland, offers railway infrastructure services and may provide
equipment leasing options for track machines.
10. Loram Europe: Loram Europe, a subsidiary of Loram Maintenance of Way, Inc., offers track maintenance
equipment leasing services for rail grinding machines, ballast regulators, and other equipment.
11.
CONCESSIONING UNDER CONTRACT: Case study:

1.(C).1 Argentina: The state-owned railway was restructured into 14 concessions. Concessions are a highly
adaptable and flexible instrument which can be used to operate freight, rail transit, subway, or intercity
passenger services. Under these agreements, the government retained ownership of rolling stock, rail
infrastructure, and facilities, all of which were assigned to the concessionaire. The concessionaire had full
responsibility for rail operations and for rail asset renewal, including commercial development of
transportation service, maintenance of rolling stock, and infrastructure. Concessions were granted for 10-year
terms with 10-year extensions as agreed by the parties.

ANNEXURE 4
Case Study: Predictive Maintenance for Siemens Mobility.

Overview: Siemens Mobility is designing, building, and maintaining 32 new bi-directional train sets for the Canadian Rail
Company. OXplus, a Dutch IT consulting firm, is helping Siemens Mobility with predictive maintenance for the new train
fleet.

Highlights of Implementations:

● OXplus is implementing Siemens Mobility CMMS (Computerized Maintenance Management Information

System) offering, CORMAP®, an IBM Maximo based solution, and integrating it with Railigent®, the
Mindsphere® based IoT platform of Siemens Mobility.
● OXplus is also involved in initiating organizational changes in conjunction with CMMS implementation.

Expected Results:

● The predictive maintenance solution will help the Canadian Rail Company to execute maintenance activities in
the most efficient manner.
● The predictive maintenance solution will help to reduce downtime, improve safety, extend the lifespan of
assets, and improve the efficiency of railway operations.

Remarks on Case Study: Since the project is still ongoing the results of the implementation is not publicly available.

Indian Railways is mainly relying on preventive maintenance methodology where the failures are avoided by
doing scheduled maintenance. However this may not be the optimum way of utilization of the assets as unnecessary
downtime and excess expenditure (spare parts and manpower) due to excess maintenance can happen. It is high time
that we move towards a predictive maintenance regime duly considering the lessons learnt from earlier preventive
maintenance experiences and incorporation of modern sensors to validate and monitor the maintenance schedules
adopted and actual failures happening. IR is moving towards introduction of train sets where a lot of automation and
sensor-based data is already available in the design of the train sets, now this infrastructure and data needs to be
effectively utilized to move towards a predictive maintenance regime to realise the actual potential of these modern
assets.