Slide No.1

● The Diesel Locomotive Shed at XXX, homes 181 locomotives. These

locomotives visit the shed periodically for maintenance and repair.

● The shed operates on a 24x7, 365 days a year basis. Locomotives enter

and leave the shed round the clock.

● The shed provides about 20 locomotives for working passenger carrying

trains, which are scheduled as per a published timetable. Thus these

locomotives leave and arrive from/to the shed at predetermined times of

the day.

● The remaining locomotives are provided for freight operations which are

more or less random in terms of arrivals/departures to/from the shed.

● The primary objectives of the shed are to ensure adequate Availability and

Reliability of the Locomotives for working Trains.

● The facilities available for this purpose include maintenance bays,

machinery, plant and equipment to carry out the maintenance, materials

(spare parts) required for maintenance and trained manpower to carry out

the maintenance.

Railroad Industry-Reducing locomotive

maintenance time

Slide No.2

My Focus Dimension -Time I have chosen Time as the key dimension that I want to focus on. The time taken for a

locomotive to be serviced by the shed should be minimized. These could be broken into

● Flow Time i.e. the time taken to carry out the maintenance/repair work.

● Wait Timed being the time spent by the locomotive while it waits for maintenance

attention

and

● Locomotives Turned Away: The instances when a locomotive requiring maintenance is

not admitted into the shed owing to lack of capacity (customers turned away).

The trade offs could be across multiple pairs of the four dimensions of the efficiency frontier, for

example Time v/s Cost, Time v/s Quality, Quality v/s Cost Time v/s Variety etc.

From the perspective of the Shed management, the key tradeoff is between Quality and Time.

I will be focussing on this pair of dimensions and attempt to strike an optimum balance between

Quality and Time.

Key Trade Offs- Quality V/s Time

The purpose of this project is to help the shed improve upon the availability

metric by minimizing the time taken to carry out the maintenance and repair

activities.

Slide No.3

Sensing the problem

The key performance measures in this context as related to the four dimensions of performance

are:

1. Time: The time taken to carry out the maintenance/repair work determines the availability of

the Locomotive (flow time). Lesser the time taken, greater the availability for working trains.

Other parameters would be the time spent by the locomotive while it waits for maintenance

attention (wait time), and the instances when a locomotive requiring maintenance is not

admitted into the shed owing to lack of capacity (customers turned away).

2. Quality: The quality of maintenance determines the reliability of the Locomotive. It also affects

the availability since a failed locomotive is not available to work a train. Number of locomotive

failures per million kilometers run measures this parameter (defect rate).

3. Cost: The cost of staff and materials used to carry out the maintenance and repair activities is

an important performance metric for the shed. The relevant parameters would be Maintenance

cost per Locomotive, Staff required per Locomotive, Idle time of staff etc.

4. Variety: The shed turns out single locomotives, Multiple Units (MUs) i.e. two or more

locomotives coupled together. The customer’s requirements are dynamic and the shed is

required to match the customer’s requirement with respect to singles and MUs

Slide No.4

Objective- What would Success

Look Like?

Based on my interaction with the users (customers) and the shed

management, the vision of success would be as follows:

1. The shed will improve the Availability of its Locomotives by 1%

(Quantity/Throughput).

2. The shed will be able to utilize its resources optimally to attend to the

maintenance and repair requirements of the Locomotives (Efficiency)

a. Reduce material cost by 10%

b. Reduce Labour Content by 10%

Slide No.5

Problem Formulation How can we reduce the time taken for maintenance?

Alternative#1:How can we reduce the maintenance time for various

activities? (Narrow scope)

A: By reducing time taken for each maintenance activity and reducing

waiting times.

Alternative#2: Why should we reduce the time taken for

maintenance? (Broaden scope)

A: The locomotives can earn more on line

Alternative#3: Q: How can the locomotives earn more on line?

(Narrow scope)

A: By visiting the shed less frequently and by taking minimum time in

each visit.

Alternative#4: Q: Why would locomotives visit the shed less

frequently and why would they require minimum time each visit?

(Broaden scope)

A: If the locomotives are more reliable

Slide No.6

•I have defined the KPI here as the Avg. No. Of locomotives inside the shed per day. The lower this number, the

better the performance.

•This is a function of the Avg. Time spent by a locomotive and the Avg. No. Of locomotives for each type of

maintenance/repair activities.

•The sliders on the right side are used to know the impact of improvement in each parameter

KPI Tree: Number of Locomotives in Shed

% Improved

Locomotives

Saved

Slide No.7

Explanatory Notes and Inferences

• The Locomotives visit the shed for Monthly (30 days),

90/180/270 Day schedules, Yearly Schedules, Three Yearly

Schedules, Six Yearly Schedules and Out of Course

(Unscheduled) repairs.

• Based on the historical data available and the KPI tree, the “M”

(Monthly) schedule has the biggest impact.

• I have therefore prepared the Process Flow Chart for the “M”

schedule.

• I Have not provided a slide for the customer’s perspective, since

the flow unit here is a locomotive.

• The first four Slides pertain to COP Assignment#1. I have

continued COP Assignment#2 in the same file for continuity.

• Activity#6 in the process flow chart i.e. The Drop Pit appears to

be the bottleneck.

Slide No.8

S.No. Activity (time in minutes/%

Attended)

S.No. Activity (time in minutes/% Attended)

1 Placement in Bay (30/100%) 5 Mechanical Repairs (180/30%)

2 Mechanical Maintenance

(240/100%)

6 Drop Pit (180/40%)

3 Lab Test of Oils and Water

(60/100%)

7 Electrical Repairs (240/10%)

4 Electrical Maintenance

(320/100%)

8 Washing filling of Supplies and despatch

(60/100%)

Locomotive Monthly Schedule

Process Flow Diagram

1

2

3

4

5

6

7

8

Locomotive

released

from

Operations

for Monthly

Schedule

Slide No.9

Peer feedback of COP#2

peer 5 → “The presentation is confusing; the problem formulation is like a cat

running to catch its tail: no consistent answer is given The KPI tree does't

lead to costs, revenues, profits, it's closer to a list of number of locomotives

(why so many decimal digits?) The customer perspective is missing even if

it could be done. EG: what does it mean in terms of waiting times, possible

delays, breakage during the trip, ..... whatever... The process flow diagram

is the only thing closer to the requests, but it's not clear what number

represents and why it was chosen the total process and not only a

significant part. In addition to this, no waiting/triangle is explained ...”

Based on the feedback from COP#2, I understand that I need to clarify

certain to help my evaluators have a better perspective of the issue (In spite

of having included a slide titled explanatory Notes”!). The points raised by

one of the Peer evaluators are reproduced below:

Clarification on my Problem Formulation:

I started with “How can we reduce the time taken for maintenance?”

I have then attempted to alternatively broaden and narrow the scope to help

view the problem from different perspectives.

Slide No.10

Peer feedback of COP#2 About the KPI Tree: I have not shown costs here because, in my

organization, there is no “cost” assigned to the locomotive in terms of, say,

$/hour. However, it is intuitive that the lesser the number of locomotives

inside the Shed the better it is. To that end, I have collected data of each

locomotive entering and leaving shed over a period of nine months from 1st

Jan’13 to 30th Sep 13.

The KPI Tree shows the impact of the Number of Locomotives visiting the

shed for each type of Maintenance/Repair and the Time taken to carry out

the maintenance/repair. Thus, more locomotives would be inside the shed if

either more locomotives visit the shed and/or if more time is taken to service

each locomotive. This is what the KPI Tree shows. I have made this Tree in

Excel and built sliders by the side of each parameter. This slider can be

adjusted from 0 to 100%. So if I assume a 10% improvement in service time

for the Six yearly Schedule, I can see the effect of such an impact on the

KPI by merely moving the relevant slider.

I have edited the KPI tree to limit the numbers to two decimal places.

Slide No.11

The Process Flow Diagram:

I have mentioned in Slide 8 that I have chosen the M schedule since it

appeared to have the maximum impact on the KPI. The process flow was

thus only for the M schedule. The waiting triangles indicate the locomotives

may have to wait to get attended at the subsequent operation in case the

work station is busy attending to another locomotive. The numbers are

explained in the Legend to the diagram, e.g., 180/30% indicates that the

operation requires 180 minutes and 30% of the locomotives go through this

operation.

Peer feedback of COP#2

My submission for

COP#3 Starts from

the next slide

Slide No.12

In COP#2, I had identified the Monthly Schedule as the potential

activity which would “give the biggest bang-for-the-buck” as far as

the KPI is concerned.

I have studied the process of the monthly schedule being carried out

on the locomotive.

I have however analysed the data and found that:

1. There was little scope for improvement in the M schedule. I could

not find any significant presence of any of the seven sources of

waste.

2. On the other hand, I found that the variability is more in Y and 3Y

schedules.

3. There is evidence of over processing in the Y,3Y and 6Y

schedules. This discovery was serendipitous, i.e. My finding was

unexpected.

Collecting Primary Data

Slide No.13

Identifying Sources of Waste

Of the seven sources of waste I found that Over processing is a major

contributor to inefficiency with respect to the Y, 3Y and 6Y

schedules.

As per the OEM of the Locomotive, the 6Y Schedule is to be carried

out after the Locomotive produces 23,000 Megawatt hours of power.

The lower schedules (3Y and Y) are also proportionately spaced.

Analysis of data shows that the freight locomotives generate this

amount of power in about 9 years.

So all activities which are presently being carried out in Y6 can be

postponed to Y9.

This would cascade to Y3 and Y schedules also.

I have checked the implication from the technical aspect also and am

satisfied that such an extension is justified.

Time taken for Maintenance/Repair

Schedule Type

Number of Locos

attended over the

period

Average time

spent in shed

per loco (days)

Average

Locomotives

in Shed

MONTHLY 1512 1.22 6.74

90/180/270 Days 372 1.84 2.50

Y 61 7.30 1.62

Y3 22 21.68 1.74

Y6 24 37.96 3.32

OUT OF

COURSE 138 3.23 1.63

Grand Total 2129 2.26 17.56

Primary Data

The data pertains to the period from 1st Jan 2013 to 30th Sep 2013.

This was compiled from the available database maintained in the

shed. Side No.14

Slide No.15

Process Variability

X Axis: Month (1=Jan) Y Axis: Time taken in Days

0.5

0.75

1

1.25

1.5

1.75

2

1 2 3 4 5 6 7 8 9

Avg Mly Time

LCL

UCL

0

2

4

6

8

10

12

14

1 2 3 4 5 6 7 8 9

Avg Yly Time

LCL

UCL

-1

9

19

29

39

49

59

69

79

1 2 3 4 5 6 7 8

Avg 3 Yly Time

LCL

UCL

20

25

30

35

40

45

50

1 2 3 4 5 6 7 8

Avg 6 Yly Time

LCL

UCL

Slide No.16

Demand forecast after review of periodicity of the

Y,3Y and 6Y schedules

Schedule Existing

Periodicity

Proposed

Periodicity

Existing

Demand

per Year

Demand

per Year

based on

proposed

periodicity

Y 1 year 1.5 years 80

locomotives

71

locomotives

3Y 3 years 4.5 years 54

locomotives

36

locomotives

6Y 6 years 9 years 27

locomotives

18

locomotives

Note: There are 161 freight locomotives. Demand is

calculated as follows:

6Y Existing: 161/6= 27 locomotives

6Y Proposed: 161/9= 18 locomotives

Etc.

Slide No.17

Inflexibilities Noticed

I have found evidence of Volume inflexibility: The capacity

which is fixed, is not able to adjust to the demand which

varies over time

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

No

. o

f L

oco

mo

tiv

es e

nte

rin

g t

he s

hed

Time of Day

Average demand over a 24 hour period

Slide No.18

“...Regarding your comments on the Monthly Schedule and Seven Wastes : ...

A. Transportation of locomotives back and forth to the repair center is present

here. Is this absolutely necessary for all types of repairs? If there are

category of repairs that are performed by a travelling repair vehicle staffed

appropriately, will that save or improve the capacity of the facility? ...As an

example, electrical maintenance takes 320 minutes and it the longest

operation, can this be done onsite instead? I recognize that the repair vehicle

idea itself promotes transportation. However, if there is evidence that this

movement may free up space at the repair center, then it may be worth

considering.

B. A source of waste seems to be the amount of time a locomotive waits to be

serviced as well as the possibility of it overstaying because of the pre-

determined schedule to be taken out. This seems to be a possibility for the

passenger locomotives. Is overstay considered as a waste in evaluating a

monthly schedule?

C. Inflexibilities You have identified the inability to respond to volume demand.

Again the bottleneck seems to be the one center or facility that carries out all

forms of repairs. Is there any reason some of these repairs cannot be carried

out on site or where the locomotive is stationed by a visiting repair vehicle? Is

this kind of a strategy that can alleviate the volume demand considered?”

Peer feedback of COP#3

Slide No.19

My comments on the feedback

First, thanks to my peers for the constructive feedback. I am to

blame for not adequately clarifying things. So, here is some more

explanation.

Item A of the feedback

• Once the locomotive is berthed (operation 1 in slide#8),

operations 2,3 and 4 take place simultaneously.

• Operations 5 and 7 take place if required (with probabilities

indicated in the table on slide#8). Locomotive is not moved in

these cases.

• Locomotive is required to be moved for Operation 6 (the Drop

Pit) , because this requires the use of a heavy machine which is

installed at a fixed location. This probability that this activity is

required is also shown in the table on slide#8

• Operations 8 is the final operation (required for all locomotives).

The locomotive is moved for this purpose, since the wash house

is located separately.

Slide No.20

My submission for COP#4 Starts from

the next slide

My comments on the feedback contd... Item B of the feedback

Yes, I have considered “over stay” of the locomotive beyond the

prescribed schedule time as a waste. The Monthly schedule is

supposed to take 6 hours. The average time taken is 1.25 days.

However, the elements of waste are thinly spread out and

therefore the steps required to tackle these require several inputs

which I feel are beyond the scope of this project.

Item C of the feedback

This is true. I have identified certain “set up” activities which can

be carried out without occupying the bottleneck resource (the

Drop Pit). There are however some organizational/labour union

issues which prevent me from implementing this at present. I

propose to work in this in the future.

Slide No.21

Three ideas for improvement

1. Extend the periodicity of Y, 3Y and 6Y Schedules to 1.5Y,

4.5Y and 9Y respectively. This will reduce the demand. This

will in-turn release labour to attend to other schedules and

repair activities, in other words, this will increase capacity.

2. Review the shift timings to better address the peak arrivals at

00:00 hours. Is it possible to schedule the shift timings so that

the locomotives which bunch up are tackled with minimum

delay?

3. Meet the spikes in arrivals on Wednesdays, Thursdays and

Fridays by deploying an additional gang on these days. There

is already an additional gang, but this gang is available on

Mondays, Tuesdays, and Wednesdays. (Sorry, I did not

include the week day wise variability in COP#3, but here it is

in the next slide...).

Slide No.22

7.63

7.43

7.20

7.95

8.13 8.25

6.65

1 2 3 4 5 6 7

Nu

mb

er

of

Lo

co

mo

tives A

rriv

ing

Week Day (1=Sunday)

Weekday wise Arrivals of Locomotives

Slide No.23

Expected Benefits of eliminating

Over Processing (per year)

Revising the periodicity of activities hitherto carried out in 1/3/6 year

intervals to 1.5/4.5/9 year intervals is expected to yield in the

following benefits:

Present

schedule

type

Demand per

year as per

existing practice

Demand per year

as per proposed

practice

Savings in

Spare Parts Saving in Staffing

Total Savings

6Y 47 38 $727,562 $45,680 $773,242

3Y 61 43 $219,187 $49,334 $268,522

Y 338 246 $214,960 $28,017 $242,977

Total $1,161,708 $1,23,031 $1,284,741

Apart from the above, the cost of Capital saved (by generating two extra

locos), works out to about $ 8.5 million, with locomotive cost of $ 4.5

million, life of 36 years and interest rate of 6%

The impact of this idea on the KPI Tree is shown in the next Chart. I

have moved the sliders for “Avg. No. of locomotives Visiting Shed per

Day” to 67% to show the impact of this idea in the next slide.

Slide No.24

Expected returns from these ideas-

1.Eliminate Over processing

Slide No.25

Expected benefits of revised shift

timings to meet the spike in demand

•The demand spikes are at 00:00 hrs, 09:00

hrs, 12:00 hrs, 15:00 hrs and 18:00 hrs (see

Slide#17).

•There are three gangs of staff (A,B and C)

which rotate over the three shifts on a weekly

basis (6 days a week).

•One more gang (D), acts as a “Rest giver” for

the three gangs A,B and C.

•This gang is “Spare” on three days in the

week. The details are as follows:

Slide No.26

Present Staffing Plan

Shift

No. Timings Sunday Monday Tuesday Wednesday Thursday Friday Saturday

1 06:00-

14:00 A A A A A A Rest/D

2 14:00-

22:00 B B B B B Rest/D B

3 22:00-

06:00 Rest/D C C C C C C

4. 07:30-

16:30 _ D D D Rest - -

Changes Proposed:

1. Shift the Weekly Rest for Gang B to Tuesday

2. Shift Weekly Rest for Gang D to Monday

3. This will result in Gang D available as “Spare” on Wednesdays, Thursdays and Fridays

with revised timings of 08:00 to 16:00 to tackle the peaks at 09:00, 12:00 and 15:00 hrs.

These changes will address idea Nos. 2 and 3. I have indicated these proposals in the chart

on the next slide.

Slide No.27

0 1

2

3

4

5

6

7

8

9

10

11 12

13

14

15

16

17

18

19

20

21

22

23

Locomotive Arrivals over 24 hours and Shift timings

No. Of Locos

Spare Batch

Shift1

Shift2

Shift3

Slide No.28

Comparison Table

Idea Ease of

Implementation

Likely Magnitude of

impact

Extend the periodicity of Y,

3Y and 6Y Schedules to 1.5Y,

4.5Y and 9Y respectively.

Easy. The OEM’s

manual supports this.

Next Locomotive falling

due Y/3Y/6Y shall be

attended for M/90 day

schedule.

High. The savings in

terms of Material and

Labour is expected to be

around $1.3 million per

year and a one time

saving of $ 8.5 million.

Review the shift timings to

better address the peak

arrivals at 00:00 hours

Medium. Need to

negotiate issue with

Staff Union.

Low. The peaks in

demand can be

addressed.

Meet the spikes in arrivals on

Wednesdays, Thursdays and

Fridays by deploying an

additional gang on these

days.

Medium. Need to

negotiate issue with

Staff Union.

Low. The peaks in

demand can be

addressed.