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HOW BIG DATA BECOME INFORMATION THEN DECISIONS
FOR ASSET MANAGEMENT
UNLV Railroad Infrastructure Diagnosis and Prognosis Symposium
Nicolas FLIX, October 2018
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 2
Condition monitoring, Prognosis & Health management 2
How Big Data become Information then Decisions for Asset Management
Internet-of-Rail and HealthHub 1
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 3
Condition monitoring, Prognosis & Health management 2
How Big Data become Information then Decisions for Asset Management
Internet-of-Rail and HealthHub 1
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 4
The Internet of rail
combines
Rail expertise and
Digital capabilities
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 5
TrackTracer and preliminary
detection w/ thresholds
It takes time to master predictive maintenance and asset management
2006 2011
2012
2013
2014
2015
2016
2017
2018 2010
2019
TrainTracer
Motes & investment
in point machines
1st Health Indicator for detection
and diagnostics
HealthHub
Platform
HMI
CatenaryTracer TrainScanner
& Test bench simulations
Physics based
Prognostics
Demand
Optimizer
Asset Management
at system level (ISO 55 000)
ASSET MONITORING DIAGNOSTICS PROGNOSTICS DYNAMIC
MAINTENANCE
TrainTracer HealthHub Asset Management
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 6
Factors influencing the type of assets that an organization requires to achieve its objectives:
• Nature and purpose of the organization ;
• Operating context ;
• Financial constraints and regulatory requirements ;
• Needs and expectations of the organization and its stakeholders.
Benefits of asset management:
• Improved financial performance ;
• Informed asset investment decisions ;
• Managed risk ;
• Improved services and outputs ;
• Demonstrated social responsibility ;
• Demonstrated compliance (legal, statutory and regulatory) ;
• Enhanced reputation ;
• Improved organizational sustainability ;
• Improved efficiency and effectiveness.
ASSET MANAGEMENT – ISO 55000 : 2014
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 7
What is HealthHub?
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 8
Condition monitoring, Prognosis & Health management 2
How Big Data become Information then Decisions for Asset Management
Internet-of-Rail and HealthHub 1
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 9
Types of maintenance
PREVENTIVE
CORRECTIVE SYSTEMATIC CONDITION-BASED PREDICTIVE
When it fails Every day Upon low fuel
indication
Upon a measurement (gauge)
and a prognostic
NUMBER OF REFILLS Fewest Many Few Minimal and
planned
CAR AVAILABILITY Lowest Medium High High
BREAKDOWN RISK 100% Low Low Lowest
1 2 0
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 10
Increased
System Availability
Reduced Maintenance Cost
(material & labour)
New tools, new processes ,
New ways of working
Periodic
Time or Mileage
based Maintenance
Periodic
Remote monitored
CBM
(Condition-based
Maintenance)
Remote monitored
Predictive Maintenance
Upon failure
Corrective
Maintenance
RCM (Reliability-
Centered
Maintenance)
HealthHub rationale and strategy
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 11
KP
Is
HealthHub rationale and strategy
SYSTEMATIC (km & time-based)
CONDITION-BASED
Doors, HVAC, Brakes
Intrinsic Limit
Implementation complexity
PREDICTIVE
Traction, Gearbox
Crack inspection,
Couplers, Wipers
EXAMPLE
RELIABILITY
AVAILABILITY
COST
Remote Condition Monitoring mainly to improve reliability and to increase effectiveness & efficiency of maintenance tasks
Prognostics & Health Management to move to health-based, dynamic maintenance maximizing asset availability
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 12
HealthHub Model
Asset Management at System level (ISO 55 000) with risk/cost model integrated
Maintenance strategy alignment
Health prediction / Machine Learning
Health assessment per Component / Sub-system
OPTIMIZATION
PREDICTION
Rule Engine & User Interface
Data Management
Point
Mach
On-
board
Way-
side
TrackTracer &
CatenaryTracer TrainScanner
TrainTracer
& Motes / others
CONDITION
MONITORING
DATA
CAPTURING
TRAINS INFRASTRUCTURE SIGNALLING
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 13
Data Acquisition Tools
Track & CatenaryTracer Measure & diagnose: cracks,
radius, geometry, corrugation on
tracks and wear of wire, height and
stagger of catenary
Motes To monitor vibration
temperature and pressure
of several components
TrainTracer On-board data analysis
and train to ground
connectivity
TrainScanner For automatic train
inspection of wheelsets,
brake pads, pantograph
and train integrity
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 14
HealthHub overview
• Integrate Data
• Develop Algorithms
• Create Rules
• Create Reports
• Analyse Statistics
• Provide Support
Central Experts Data Hub
PROJECT
Operation
data
Rule
Engine
EVENT STATUS POSITION
MMIS Service
Orders
Trains
Infrastructure
Signalling
GSM / LTE
Rule
Engine
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 15
Sesto, One of our Fleet Support and Data Centres
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 16
Sesto Data Centre handles over 480 trains from multiple fleets
218
3
150
3/4
14
5
121
4/5/6
19
7
19
7
17
7
25
11
53
1
SC
HE
DU
LE
D
500 min 240 min
30% 10%
100% 50%
2016 2017
Minutes of
Delay per month
% No Fault Found
% of Trouble
Shooting time *
* estimated
FLEET
COACHES
-50%
-65%
Base FPMK Target FPMK FPMK Obtained
FP
MK
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 17
Under deployment
Deployed
HealthHub™ Worldwide Deployment
TrainTracer HealthHub Asset Management
2006 2011 2013 2015 2017 2019
2014 2016 2018 2012 2010
Infrastructure
Trains
Signalling
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 18
HealthHub Data Factory: Alstom Smart data work bench
Asset
data
REPORT
published
in HealthHub
Process
Schedule
Purpose
Crunch data
Publish reports
Fine tune rules
Performance
80 reports per day
10 Tera Bytes analyzed each day
Process 1 Billion values per minute
HealthHub
Data
Factory
WEATHER HISTORY DAILY ALERTS CONDITION REPORTS DAILY ALERTS CONDITION REPORTS
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 19
HealthHub achieved benefits
Reduced safety hazards Reducing risky intervention underframe and on the roof
Railway safety improved (automated integrity check)
Increased availability of the rail system Up to 30% decrease in train immobilisation time
Service Affecting Failure reduction on Trains / Infra
and Signalling.
Deployed on our maintenance contracts In place on Reims / WCML / NTV Maintenance.
Proposed for every new project
Useful life of the assets extended
+15% and more in the future
Cost reduced 15% reduction in material consumption
Increased staff productivity +25% in maintenance intervals (more in the future)
and better anticipation
Extended interval between maintenance
tasks Planned major maintenance moved from 20kMiles
to 50kMiles on going
TrainTracer HealthHub Asset Management
2006 2011 2013 2015 2017 2019
2014 2016 2018 2012 2010
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 20
HealthHub data analysis and visualisation principle
REAL TIME DATA
MM
IS
Fleet Management
KPI & telematics
AS
SE
T M
AN
AG
EM
EN
T
& P
RE
DIC
TIV
E M
AIN
TE
NA
NC
E
Fleet usage optimization
Diagnostic/Prognostic
TrainTracer
TrackTracer
CatenaryTracer
Motes
TrainScanner
Point Machine DYNAMIC
MAINTENANCE
PLANNING
Rule engine
Alstom data scientists
HealthHub database
HealthHub Platform
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 21
HealthHub Model
Asset Management at System level (ISO 55 000) with risk/cost model integrated
Maintenance strategy alignment
Health prediction / Machine Learning
Health assessment per Component / Sub-system
OPTIMIZATION
PREDICTION
Rule Engine & User Interface
Data Management
Point
Mach
On-
board
Way-
side
TrackTracer &
CatenaryTracer TrainScanner
TrainTracer
& Motes / others
CONDITION
MONITORING
DATA
CAPTURING
ROLLING STOCK INFRA SIGNALING
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 22
PHM development Process
PHM user
requirem.
Technical
design
Virtual
prototyping
Bench
prototyping
Demonstrator
design
Field
Demonstrator
Identification
of key physical
parameters
and
target failure
mechanisms
Healthy condition
in context
Degraded condition
in context
HEALTH
INDICATORS
Test bench
Virtual
prototype
PHYSICS OF FAILURES & MACHINE LEARNING
Field data
from
Demonstrator
Technical docs
Experience
FMMEA
LCCA
Expert knowledge
Preliminary
architecture
(hardware & software)
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 23
Physics of Failures and Machine Learning
Machine Learning
Extracting information from
data
Feature extraction and
selection:
Detection
Diagnostics (pattern
recognition)
Predicting future values
(prognostics)
Virtual Prototyping
Software-based model to simulate
the dynamics of an asset
Benefits:
High flexibility
Reduced experiment cost
Safe evaluation of extreme
states
Uncertainty
Accurate incorporation of
sources of uncertainty
Monte Carlo simulation
PHM user
requirem.
Technical
design
Virtual
prototyping
Bench
prototyping
Demonstrator
design
Field
Demonstrator
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 24
From raw signals to Health Indicator
Raw signals Machine Learning
Model
Healt
h In
dic
ato
r
17 19 21 23 25 27 31 29
1
October 2017
2
0,3
Health Indicator
Too many false alarms or too
few detections
Requires high precision to
capture relevant variations
Alstom Know-how
HealthHub Data Factory
Customer requirements
Maintainer feedback
0 0.5 1 1.5400
600
800
1000
1200
1400
1600
04/11
25/11
30/11
Quantification of distance
between the observed state
and a healthy condition
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 25
The Health Indicator: the heart of detection, diagnosis and prognosis
-100
10
-5
-4
-3
-2
-1
0
1
2
3
4
5
-10-5
0
5
10
Distance:
Health
Indicator
The Health Indicator measures
discrepancy between test (observed)
data and training data
The anomaly is visible with the Health
Indicator while the raw signals won’t
always show the anomalies
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 26
HealthHub on selected components and behaviours
Track Catenary Point Machines
Track Circuits
Brakes Traction Bogie HVAC Toilets Doors Trains
Infrastructure Signalling
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 27
PHM on point machines: case study and health indicator
𝑓1(𝐼) 𝑓2(𝐼) 𝑓3(𝐼) 𝑓4(𝐼) 𝑓5(𝐼) 𝑓𝑛(𝐼) 𝑓 = HI 𝑓…(𝐼)
Data capture
Feature
extraction
Detection
Diagnostics
Creating the Health Index for each machine
Creating the Health Indicator for each machine
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 28
PHM on point machines: case study and health Indicator
BENEFITS Detecting potential failures
before they occur
Increasing interval between
interventions: from 1 month to
3 months
Reducing people
mobilization, therefore less
exposure to accidents
Saving time by geolocalizing
potential failures
Nominal behaviour Progressive deterioration Post-maintenance
behaviour
Healt
h In
dic
ato
r
Dec 28 Dec 29 Dec 30 Dec 31 Jan 1 Jan 2 Jan 4 Jan 3
2018
5500
0
Jan 5 Jan 6
2017
Maintenance
Intervention
Data capture
Feature
extraction
Detection
Diagnostics
𝑓 = HI2A 𝑓1(𝐼) 𝑓2(𝐼) 𝑓3(𝐼) 𝑓4(𝐼) 𝑓5(𝐼) 𝑓𝑛(𝐼) 𝑓…(𝐼)
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 29
PHM on point machines: case study and health Indicator
Loss of tolerance
Rail deformation
Power supply
Feature values Lubrication
Data capture
Feature
extraction
Detection
Diagnostics
Using specific features to diagnose the problem
𝑓1(𝐼) 𝑓2(𝐼) 𝑓3(𝐼) 𝑓4(𝐼) 𝑓5(𝐼) 𝑓𝑛(𝐼) 𝑓 = HI 𝑓…(𝐼)
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 30
PHM on HVAC: Context
-10%
drops
Working hours
Pow
er
(kW
)
0 600.0 300
Cooling Capacity
Coefficient Of Performance
Simulation of
HVAC operation over 591 working hours
Context of HVAC Energy consuming
High maintenance costs
When faulty Reduce fleet availability
Reduce passenger comfort
Clogged filter Cooling capacity -10%
COP degrades
Clean filter vs Clogged filter
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 31
Filter life extended by
+91%
Threshold reached
on 9th August
PHM on HVAC: The Health Indicator and prognostics
Extended life time
Healt
h In
dic
ato
r
2017-03 2017-04 2017-05 2017-06 2017-07 2017-08 2017-09
Threshold
Learning window Prognostics horizon
Systematic maintenance
replacement date Prediction date
Predictive maintenance replacement date
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 32
Future Perspectives
Adaptive PHM:
PHM algorithms adapt to the changing
environment, context & mission profile Machine learning
Dynamic Maintenance:
Adapt maintenance and assign tasks &
resources dynamically according to
operations needs Machine learning, optimization
Risk-based Asset Management:
Balance between cost (maintenance,
renewals) and risk (service affecting failures)
is achieved based on customer preferences Utility theory, decision theory, cost-benefit
analysis
Resilient Systems:
Systems that self-heal when detecting
degradations Artificial intelligence, control theory, reliability
engineering
TrainTracer HealthHub Asset Management
2006 2011 2013 2015 2017 2019
2014 2016 2018 2012 2010
© ALSTOM SA, 2015. All rights reserved. Information contained in this document is indicative only. No representation or warranty is given or should be relied on that it is complete or correct or will apply to any particular project. This will depend on the technical and commercial circumstances. It is provided without liability and is subject to change without notice. Reproduction, use or disclosure to third parties, without express written authorisation, is strictly prohibited.
ALSTOM - 11/10/2018 – P 33
It is not about Big Data, but about Smart Data
Alstom started 12 years ago with data analysis
and connected assets
Alstom combines outstanding railway expertise
with advanced digital technologies
Alstom is a world leader in rail maintenance…
… Alstom is your partner in this journey
Key take-aways
www.alstom.com