1. Asset Degradation Modelling at Townsville Water
Journey to achieve sustainability in business performance
Sen Vigneswaran, Senior Engineer Asset Management - Waste & Utilities,
Engineering Services, Townsville City Council
IPWEAQ Conference 2016
9 November 2016
Notes:
Core Enterprise Suite - Release
Asset Management
Assets – Jun
Billing – Nov
Core – Aug
Mobile – Jun
Web – Mar
Web Services – May
Works – Sep
Mobility
Core – Mar
Mapping – Mar
Offline – Mar

2. Townsville
Capital of Northern Australia  The City with Opportunity and Great Lifestyle
AREA:
3,736
SQ. KM
POPULATION:
190,000
HOUSEHOLDS:
70,000
BUSINESSES:
5,000

3. Commercialised Business Unit of Townsville City Council
Townsville Water
Commercialised Business Unit of Townsville City Council
BUDGET:
$250 million
ASSETS:
$2.7billion
STAFF:
300
Discussion Points:
Budget includes annual capital spend of around $40m-$60m

4. What we own 17,000 – 20,000 ML Sewage Treated per annum
Asset Class
Quantity
Replacement Cost ($ M)
Water Supply Assets
Raw Water (pipes, dams, head works) 2
500.2
Water Treatment Plants 3
192.9
Water Pump Stations 22
14.4
Water Reservoirs 33
91.7
Water Distribution & Reticulation Mains
2,598 km
717.7
Water Service Connections
75,535
107.4
Hydrants & Valves (>375 mm)
20,981
67.4
Meters
72,031
6.7
Total Water Assets
1,698.4
Wastewater Assets
Wastewater Service Connections
194.5 km
16.2
Wastewater Property Connection Points
47,178
48.7
Sewer Mains (Gravity & Pressure)
1,302 km
490.8
Maintenance Holes
21,500
87.5
Wastewater Pump Stations
181
81.7
Wastewater Treatment Plants 6
262.8
Total Wastewater Assets
987.9
Discussion Points:
17,000 – 20,000 ML Sewage Treated per annum
48,000 ML Potable Water Produced per annum
No of Customer Calls (Asset Related) – 4500
No of Work Orders (Asset Related) – Total 16,000
PM – 1,800
RM – 14,000
CM – 800
No of Failure Data Collections – 8500

5. Drivers for Degradation Modelling
Aging Infrastructure 1
Understand the asset & network condition 2
Pressure to keep rates/ charges low 3
Quality of service 4
Call for better financial forecasting 5
Long term forecasts – moving to 15 yrs. 6
Maximise the asset utilisation 7
Improving data quality 8
Improving Technology 9
Evaluating risk (environmental, economic, social, and political) 10
Discussion points:
Nature of assets whether they are pipe network or mechanical and electrical create significant challenges in predicting the condition or asset renewal time.
Demand for better quality service at the lowest cost, i.e. minimise the breaks
Demand for better smooth financial forecasting for longer periods that even beyond 10 years
Availability of technology – even the difference between excel as compared 2007 to 2013 enables for better analysis

6. Asset Degradation Modelling Continuous Validation
The How
Beginning of a journey to achieve sustainability
Data Excellence
Asset Degradation Modelling
Continuous Validation
Discussion Points:
Better and more data (information) is vital for any decision making. Same applies for models as well.
Challenges of collecting data for water and wastewater assets are that either buried assets or complex mechanical and electrical assets that fail without much warning.
It is important that we continuously validate our models as we collect more data.

7. The How Invest in Data Excellence
Maintenance History
Age
Failure Causes
Asset Attributes – Material, Diameter, etc.
Discussion Points:
Heavily rely on Operations and Maintenance to collect the data through integrated inspection and maintenance activities.
Timely asset capture is critical with accurate commissioned date, material, diameter, etc.
Each failure cause directly or indirectly relates to the asset degradation
Sample asset data is selected here for this presentation.

8. The How Asset Degradation Modelling – An abstract concept
Define the relationship between asset degradation (decay) and failure causes
Model the asset degradation (decay) curves based on failure ratings
Predict the decay rating of each asset based on the asset degradation curve
Consolidate the decay rating and failure rating to derive the condition of each asset
Discussion Points:
Degradation is an abstract concept which cannot be observed or measured directly.
Collaboratively field staff, engineers and designers get together and assign the scores and weightings to failure causes to understand the asset degradation
Model the failure ratings against the current assets, based on the assign scores and weighting to draw the decay curve.
Place all available assets on the curve to predict the network condition.

9. Asset Degradation Modelling
An Example – Water Mains
Relationship between Degradation and Failure Causes
Discussion points:
Failure causes of all the pipes that break, being collected and stored against the assets.
Weightings are given for each failure cause considering that how does each failure cause contribute to the degradation of the water main.
Then, the expected failure events on a theoretically good pipe are recorded against the condition rating.

10. Asset Degradation Modelling
An Example – Water Mains
Degradation curves based on failures against the age
Discussion points:
Decay curves are approximated based on the past failure events against the age for each material type.

11. Asset Degradation Modelling
An Example – Water Mains
Degradation Curves link to Decay Ratings
Discussion points:
Finally, degradation curves are modelled based on the decay ratings of assets that failed in the past.
Now, you can predict the decay ratings of all your assets in the network based on the decay curves for each material type.

12. Asset Degradation Modelling
An Example – Water Mains
Predicted Decay Ratings for sample number of assets based on asset degradation curves
Discussion points:
Sample number of assets are presented here with predicted decay ratings based on the age.
Some asset classes where less amount of failure history is available, decay ratings can be considered as asset condition ratings.

13. Asset Degradation Modelling
An Example – Water Mains
Failure Ratings are consolidated with predicted Decay Ratings for sample number of assets to derive the Condition Ratings
Discussion points:
Since, we have number of assets in the network that have failed in the past and we consider failure rating in deriving the final condition rating.

14. Continuous Validation
An Example – Water Mains
Continuous validation is critical to ensure the accuracy of asset degradation models.
Discussion points:
You can see in the table that last year nearly 70% of the asset failures were for assets identified as renewal priority 1 or 2.
Our models seem to be working well, we just need to catch up on our renewal work program
To that end, last year council agreed to a 200% increase in our annual renewal budget for small mains based on these models.

15. The Benefits
An Example – Water Mains < 200mm
Understand the condition of the water reticulation network.
Depreciate the assets based on predicted remaining life.
Prioritise the renewals based on the predicted condition.
Discussion points:
We can understand the condition of our water reticulation network
We can predict the average remaining life
You can see the average maintenance costs are high for condition 5 assets.

16. Long term financial forecasting for renewals – scenario 1
The Benefits
An Example – Water Mains < 200mm
Long term financial forecasting for renewals – scenario 1
Discussion points:
You can see the condition of assets are getting worsen with time over 10 year period with the current funding levels.

17. Long term financial forecasting for renewals – scenario 2
The Benefits
An Example – Water Mains < 200mm
Long term financial forecasting for renewals – scenario 2
Discussion points:
You can see the network condition remain almost same with the proposed funding level.

18. Long term financial forecasting for renewals – scenario 3
The Benefits
An Example – Water Mains < 200mm
Long term financial forecasting for renewals – scenario 3
Discussion points:
You can see the average condition of assets are getting better with the time with the excessive funding level.

19. Journey to achieve sustainability in business performance
Summary
Journey to achieve sustainability in business performance
Engage & Collaborate with relevant stakeholders to get the best results.
Understanding the condition of your assets enables you to balance the risk, cost and performance.
Discussion points:
Asset degradation modelling is a first part of the journey to achieve sustainability in business performance.
Engage and collaborate with relevant stakeholders to get the best results.
By balancing the risk, cost and performance, we are able to deliver our customers better value and improved service.

20. Questions? Contact Sen Vigneswaran Stephen Knott ACKNOWLEDGE
Senior Engineer – Asset Management (Waste & Utilities)
Townsville City Council M: E:
ACKNOWLEDGE
Stephen Knott
Condition Assessment Engineer
Questions?