B-Logistics wagon maintenance

Study on how to do wagon maintenance optimization, done by Data Minded together with our client, B-Logistics

1. Project: Maintenance optimization for wagons
23 July 2015

2. Agenda
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 2


1.About me & my company
2.Project introduction
3.Process raw data
4.Iterative improvement
5.Final results

3. •Bart Maes
•Background in Computer Science (A.I.)
•Data coordinator at SNCB Logistics
•New to data science/big data
•Traveler (on a shoestring)
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 3
A bit about myself

4. •200 locs
•7000 wagons
•1900 employees
•30 million transported tons
•5 billion ton-kilometers
•2000 trains per week
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 4
A little more about SNCB Logistics

5. •..  2011: Ruination
•State owned, part of NMBS
•2009: +100 million loss/year (EBITDA)
•2011: private company, NMBS 100% shareholder
•2011 2015: Transformation
•2014: 11 million profit (EBITDA)
•2015: private investor acquires 66,6% of shares
•2015  ∞: Innovation
•eLearning
•MIA/RITA
•Big Data
•…
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 5
A brief history of SNCB Logistics

6. •Maintenance optimization for (own) wagons
•4800 wagons
•Wagon breakdown
•Each wagon checked before each train departure
•Will probably result in lost train
•Hence, expensive
•Current maintenance process
•Time based: every 6 years, simplified or major overhaul
•Cost: €4-16k, independent of wagon condition
•Hypotheses
•Wagon usage varies widely
•Can tolerate less frequent maintenance of less used wagons
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 6
Project summary

7. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 7
Project steps
1.Reconstruct each wagon’s exact history to
deduce:
•Travelled distance
•#Loads/unloads (‘cycle’)
•Weight transported
•Damage reports
2.Reconstruct estimated wear from maintenance
reports
3.Correlate wear to wagon history
4.Given usage, estimate time until maintenance
is necessary






Wear

km travelled
Need
Overhaul

8. •Initial rough estimate
•Uneven distribution
•Large number of low-usage
wagons
•Smaller number of high-usage
wagons
•Indicate potential for
maintenance policy improvement
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 8
Analysis: distance travelled

9. •Source: CargoWeb
•Collected events for wagons
•Potentially 100s events / week
•Generated by operational systems
•Manually inserted
•~200 types of events: departure, arrival, ready for X, take
over, hand over, passed through, …
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 9
Raw Data: wagon events

10. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 10
Raw Data: dirty & complicated Begin retention - Consignor
RCN accepted
1
Final destination changed
15
First departure
73
Wagon checked (RCN) : ok
74
At disposal
1
Departure
1 41
Wagon assigned to order
39
Physical restitution - Empty wagon
24
Wagon withdrawn from order
3
Assignment of consignee - loaded wagon
10
Assignment of consignee - empty wagon
6
Train composition ok
294
Physical restitution - Loaded wagon
51
Arrival
412
Wagon transport manual undone
1Wagon checked (RCN) : rejected
1
Wagon transport manual done
2
42
2
198
1
1
381
End retention - Consignor
1
58
Administrative restitution - Empty wagon
7
10
340
125
32
196 Administrative restitution - Loaded wagon
7
33
10
17
1259
10
5451
Arrival at destination station
505
205
13
4
1
6
1
16
84
2
4
17
4
626
414
1
1
38
259
34
1
469
31
25
273
74
59
14
Ready to pull
5
22
1
37
Status manually changed
1
Physical restitution - Wagon status is unknown
23
Administrative restitution - Wagon status is unknown
1
12
1159
1
5
1110
1
1
24
1
151032431
434 Last departure
21
38
620
136
1
34
3
5
342
120
14
96
6
1
1
34
7
186
17
1
2
11
69
Begin retention - Consignee
2
2
5
6
5
22
1
7
1
1
10
1
5
3
3
23
23
336
149
1
309
11
23
181
7
17
108
47
94
71
11
3
3
End retention - Consignee
1
114
1125
8
2
166119
7
67
9
5
3
1
89
12
4
533
37
1
24
2
312
3
5
2
13
3
5
1
13
1
1
2
1
1 7
4
3
1
187
382 102 1
7
6
165
1
1163
3 202
276 13
Wagon position changed (from ...)
1
1
1
1
7
6
1125
12
13
3
2
1821
Begin retention - Own RU
1
10
4
Begin retention - Other RU
1
7
6
1
4
1
3
2
2
8
4
10
1
2
1
End retention - Own RU
1
1
1
11
1
11
8
1
1
1071
181
End retention - Other RU
1
2
1
1
1
1
Wagon position changed (to ...)
1
1
1

11. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 11
Summarize raw events
Time Place Event
… … …
30-Apr-2012 10:06 Antwerpen Berendrecht Cirkeldijk Physical restitution — empty wagon
30-Apr-2012 10:35 Antwerpen D.S. Berendrecht Train composition OK
30-Apr-2012 12:29 Antwerpen D.S. Berendrecht Train composition OK
30-Apr-2012 13:08 Antwerpen D.S. Berendrecht First Departure
30-Apr-2012 17:00 Antwerpen Waasl-Zuid van Moer Arrival at Destination
30-Apr-2012 17:20 Antwerpen Waasl-Zuid van Moer At Disposal
… … …
From To Action
… 10:06 At rest at ABC
10:06 10:35 Travel ABC – ADSB
10:35 13:08 At rest at ADSB
13:08 17:00 Travel ADSB – AWZvM
17:00 … At rest at AWZvM

12. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 12
Summarized data: still challenging arrival
travelling: 231
at rest: 176
other (after arrival)
travelling: 571
at rest: 991
departure
travelling: 33
at rest: 658
travelling: 2
at rest: 29
travelling: 1126
at rest: 8048
travelling: 113
at rest: 1417
travelling: 2126
at rest: 10
travelling: 229
at rest: 217
other (after departure)
travelling: 66
at rest: 30
travelling: 58
at rest: 28
travelling: 2
at rest: 8
travelling: 7
at rest: 19
Even after abstracting and simplifying,
interpreting the data is challenging

13. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 13
Distance travelled: a first reconstruction

•Room for improvement:
•Noise
•Gap in Business Understanding
•Goal:
•Improve until ‘good enough’

14. •Ignore manually inserted events
•Unreliable
•Often provide little extra information
•Cluster stations into groups
•Maps with business activities
•Eliminates false positive mismatch between arrival & departure
station
•Improve interpretation of event sequences
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 14
Distance travelled: interative improvement

15. •‘Travel’ action defines movement between 2 points A & B
•No central source for all distances between every 2
points
•Distance matrix constructed using different sources:
•Actual RAILDATA measurements
•Extrapolation (cluster nearby stations)
•Google maps
•Haversine distance
•Manual input
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 15
Distance travelled: another hurdle

16. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 16
Most wagons travel less than 30k km/year
Distance travelled: results

17. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 17
Some wagons have very distinct usage patterns
Cycles & average load: results

18. B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 18
Some wagons have very distinct usage patterns
Cycles & average load: results
Genk-Chatelet
Gent-La Louviere
Gent-Clabecq

19. •Business satisfied by presented results
•New maintenance plan uses ‘wagon groups’
•Focus on distance travelled
•Other elements may be added in the future
•#Cycles
•Average load
•Main achievements:
•Cost reduction for maintenance
•Risk/cost reduction for breakdown
B-LOGISTICS WAGON MAINTENANCE - 23 JULY 2015 19
Final results & business actions

20. SNCB Logistics I Koning Albert II-laan 37 1030 Schaarbeek I Boulevard du Roi Albert II 37 1030 Schaerbeek
T [phone] I F [phone] I [email protected] I www.sncblogistics.com
Thank you