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 11.09.04.011 Asset Management Assets – Jun 2015.2 Billing – Nov 2014.1 Core – Aug 2015.1 Mobile – Jun 2015.1 Web – Mar 2014.1 Web Services – May 2015.1 Works – Sep 2015.1 Mobility Core – Mar 2015.1 Mapping – Mar 2015.1 Offline – Mar 2015.1

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

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

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Questions? Contact Sen Vigneswaran Stephen Knott ACKNOWLEDGE Senior Engineer – Asset Management (Waste & Utilities) Townsville City Council M: 0405 185 753 E: sen.vigneswaran@townsville.qld.gov.au ACKNOWLEDGE Stephen Knott Condition Assessment Engineer Questions?