1. Engineering Asset Management Systems
Nalinaksh S. Vyas
Professor
Department of Mechanical Engineering
Indian Institute of Technology Kanpur
&
Chairman
Technology Mission for Indian Railways (TMIR)
Ministry for Railway
Government of India

5. What is Engineering Asset Management
Engineering Asset Management, addressies the general problem of physical asset management, relating engineering capability to economic cost and value in a highly integrated way.

6. Typical Engineering Asset Management Platform for Railways
An Engineering Asset Management (EAM) platform for Railways can be configured with the following levels –
Component Level (e.g. Bearings, Side Frames, Bolsters etc.)
Sub-System Level ( e.g. Bogie, Coach, Locomotive, Track, Signals etc.)
Vehicle Level (i.e. train / rake level)
Operational Parameter Level ( Track, Gradient, Speed, Braking etc.)
Infrastructural Issues
Organisational Goals
The Platform is represented through Concentric Rings which would be interconnected to each other through extensive and complex input-output mappings.

7. EAM Configuration Decision Decision Decision Decision Decision
Organisational Goals
Decision
Infrastructural Issues
Operational Parameters (Track, Gradient, Speed, Braking etc.)
Decision
Decision
Vehicle Level
Sub-System Level (Engine, Wagon, Coach, Signals, tracks, bridges
Component Level (Side Frame, Bearing, Bolster)
Deep Learning Open Platform
Decision
Decision

8. Organisational Goals Organisational Goals
Infrastructural Issues
Infrastructural Issues
Operational Parameters (Track, Gradient, Speed, Braking etc.)
Operational Parameters (Track, Gradient, Speed, Braking etc.)
Vehicle Level
Vehicle Level
Sub-System Level (Engine, Wagon, Coach, Signals, tracks, bridges
Sub-System Level (Engine, Wagon, Coach, Signals, tracks, bridges
Component Level (Side Frame, Bearing, Bolster)
Deep Learning Open Platform
Component Level (Side Frame, Bearing, Bolster)
Deep Learning Open Platform
Deep Learning Open Platform

9. Big Data with Artificial Neural Architecture
Each Concentric Ring, withiin itself would carry an Artificial Neural Network architecture.
A typical Artificial Neural Network is shown in the next Figure.
It would contain Input and Output ports with various intermediate layers carrying neurons, connected through neural synapses.

11. Guru Gobind Singh Super Thermal Power Station, 210 MW, Unit1, Ropar Punjab The Plant

12. FFT for various faults

13. Fault-Symptom Frame – Predominant Frequencies

14. Fault-Symptom Frame – Predominant Direction

15. Fault-Symptom Frame – Predominant Location

16. Fault-Symptom Frame – Predominant Sound

17. Causes

18. Back-Propagation Network Validation : 20 Faults
Fault numbers 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
0.9947
0.0010
0.9993
0.0003
0.0013
0.9998
0.0004
0.0002
0.9999
0.9935
0.3032
0.9990
0.0005
0.0001
0.0071
0.0177
0.9997
0.0075
0.2762
0.9681
0.0025
0.9518
0.0019
0.0060
0.0008
0.0198
0.0006
0.9995
0.2086
0.0054
0.8408
0.0026
Output required is identity matrix of 20x20

20. Self Organising Maps 81

22. IVHM Strategy for Aerospace Applications
Strategies of Integrated Vehicle Health Management (IVHM), (will be adopted at a Systemic Level for modeling the Railway System Platform (Ref: NASA IVHM tech plan)
IVHM Strategy views Aircraft System Management through four levels
Component / Sensor level
Sub-System Level
System Level
Fleet Level
The IVHM Strategy for Aircraft Systems is described in greater detail in the following Figure.

23. IVHM 1.2 Modeling and Simulation IVHM 1.3 Data Analysis and Algorithm
IVHM Levels
LEVEL 4 AIRCRAFT LEVEL
IVHM 4.1
Ground / Flight
IVHM 4.2
Systems Analysis
Demo
LEVEL 3 AIRCRAFT SYSTEM LEVEL HEALTH MANAGEMNET
IVHM 3.1 Detection
IVHM 3.2 Diagnosis
IVHM 3.3 Prognosis
IVHM 3.4 Mitigation
IVHM 3.5
Integrity Assurance
LEVEL 2 SUBSYSTEMS HEALTH MANAGEMNET
IVHM 2.1
General Systems HM
IVHM 2.2 Airframe SHM
IVHM 2.3 Propulsion HM
IVHM 2.4
Avionics & FCS HM
IVHM 3.5
Software HM
LEVEL 1 TECHNOLOGY DEVELOPEMENT
IVHM 1.1
Sensors
IVHM 1.2 Modeling and Simulation
IVHM 1.3 Data Analysis and Algorithm
IVHM 1.4
Test Beds for V & V
Ref: NASA IVHM tech plan

24. Generic STRUCTURE for Asset Management Application
This STRUCTURE can be generically be implemented
for Asset Management Applications in various domains,
Road Transport,
Water Distribution,
Health Services
etc.

25. thank you