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:diagnostics/ :transformation/ :investment planning/ :portfolio optimisation/ :investment economics/ :regulation and economics/ :training/. Review of the water industry UKWIR project – when to repair, refurb or replace assets ICS Consulting November 2011. Agenda.

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  1. :diagnostics/ :transformation/ :investment planning/ :portfolio optimisation/ :investment economics/ :regulation and economics/ :training/ Review of the water industry UKWIR project – when to repair, refurb or replace assetsICS Consulting November 2011

  2. Agenda • Intro to the UKWIR project • Objectives • Deliverables • Key findings of the project • Application • Demo of the tool

  3. Project Objectives • Project commenced in Spring 2011 • Development of a robust modelling and costing guidance: • Identify potential intervention strategies for different types of assets • Identify and justify asset policy decisions • Identify intervention cost approaches • Map best practice approaches to Common Framework structure • Focus primarily on non-infrastructure assets • Practical examples • Develop Excel Tool • Costing and deterioration examples

  4. What are the challenges to address? • Limited scope of interventions considered – used to answer: • At what point do we stop reactively repairing assets and replace it due to cost considerations? • Should we proactively invest to get a better level of service? • Limited use of asset attributes • Lack of maintenance, environment, location, asset history, etc. • Hard to understand impact of some intervention if only have ‘age’ only • Optimal asset policy may be a mix of interventions • Optimal asset policy may not be optimal across the asset base • COTS - time consuming for a single intervention strategy, and may not be well suited to a range of different interventions strategies • Focus has been on next 25 years, rather than next 5 years.

  5. Summary of the Risk Modelling Process

  6. The guidance centres on the development and build of a risk modelling framework • The framework must start with considering the TOP DOWN priorities • Top down priorities are generally communicated in terms of service performance (though some may be asset performance) • Many of these will be ‘valued’ – using WTP for example • We also need to model up to these service performance metrics Customer and Environmental Values Corporate Priorities and Constraints Service Performance Asset Performance Physical Assets Investment

  7. Developing a modelling approach involves a number of stages 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  8. The modelling approach involves a number of stages Stage 1: • Identify assets to be modelled and the range of interventions • Consideration of the triggers for intervention • Intervention when a trigger is hit can be manually set or determined by optimisation process • Modern equivalence may be relevant to capture 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  9. The modelling approach involves a number of stages Stage 2: • Estimate asset performance profile • Fix on fail baseline • Range of alternative intervention strategies • To model interventions and triggers – not just age only models • Ideally need some measure of condition/performance – helps identify intervention impacts 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  10. The modelling approach involves a number of stages Stage 3: • Estimation probability of service failure given asset failure • Estimate severity of the service failure • For the intervention strategies need to estimate: • Number of asset failures; number of interventions; asset base profile; expected service levels • Validation techniques needed 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  11. The modelling approach involves a number of stages Stage 4: • Cost of interventions • Impact of interventions on operational costs • Inclusion of social costs and benefits and private costs in the costing framework • Discounting and NPV 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  12. The modelling approach involves a number of stages Stage 5: • Selection of the optimal asset policy • Selection of the optimal programme of investment • Use of corporate tools to support decision making is preferable • Understand sensitivity and uncertainty around the modelling inputs and assumptions • Clear explanation of the choices made about investment 1 Asset and Intervention definition 2 Asset deterioration modelling 3 Service Consequence modelling 4 Determining costs 5 Decision making

  13. Designing the framework • Top down needs to align with bottom up • Failure Modes Analyses needed to develop the bottom up approach: • Modes – mechanical asset failure: repairable or not • Causes – maintenance, age, usage, corrosive environment… • Effects – supply interruption, pollution….. • Need to consider the impact of duty standby and duty assist • Data gaps are likely – may need to group failure modes, result asset attributes, etc in light of that • There is only so many gaps in data that can be dealt with elicitation and other techniques

  14. Designing the framework • Consistency in the framework is desirable • Data gaps may mean that the robustness across the whole analysis is not uniform • Deal with this using sensitivity analysis and uncertainty • Actual time and effort in modelling some elements depends on the size of the programme in relative terms – the more the expenditure, the more effort should be put in • It’s a journey • PR09 was a key learning point. • The time and resources to make the change to adapt to the learning could be considerable – and may not always be worth it.

  15. The key messages in risk modelling • Need to estimate pre- and post-investment profiles • Data gaps are inevitable and infill commonplace • Uncertainty around data should be explicitly considered in the analysis. • Survival analysis is most popular in modelling end-of-life failures for assets • Best practice is to use the Weibull distribution • AND many assets are repairable in nature • A mix of interventions should be included in the modelling framework • Proactive and reactive; Repair, refurbish and replace • Different levels of the asset hierarchy • The restoration times for the different types of interventions – rather than assets! • Intervention impacts articulated in terms of asset attributes and history • Performance, energy consumption, condition, nrs failures / refurbishments • Need better intervention benefits tracking

  16. Key messages in risk modelling • NI assets…. need to capture system reliability • BUT some reliability modelling techniques are resource and time consuming – need to be pragmatic given this • All service impacts need to be expressed in monetary figures • Aim for Cost Benefit Analysis (CBA) for all investments • Decisions based on CBA need to be made at the programme level even though the modelling is at asset group level. • Uncertainty and sensitivity analysis are crucial • Understand robustness of decisions and the impact of data gaps and modelling errors

  17. Examples and Demo of the Tool

  18. The Example in the Tool • Asset Selection by the Steering Group • Rapid Gravity Filter • Simplified to the four major assets • Actuator • Blower • Tank • Pipework • Demo of costing and deterioration modelling principles

  19. What does the data need to look like? • Excerpt of the failure data for actuator….. • Need to model qualitative data as a dummy

  20. Weibull modelling…. • Stata and R Weibull model • Stata estimates the shape parameter (b and 1/b); R estimates (1/b) only • Intercept and predictor coefficients in R are scaled by b. Hence for the constant in Stata of -10.28, the equivalent in R is -10.28/3.595 = 2.861 • Key: Know the parameterisation of the software and the modelling tool !

  21. What about repairable rates • Again, know the parameterisation of the software and the tools • Need to use count data regression – note: the offset/exposure • Choice between exponential and power model – need to be sure which you are modelling – depends on the nature of the age variable

  22. Looking at the Tool…..

  23. Summary of inputs and outputs • Service measures and social values • Discount rates • Energy prices & carbon prices • Asset lists – age and attributes • Deterioration models • Weibull end of life survival rates • Repairable failures • Service impacts • Interventions – costs and impacts • Intervention strategies • Age based triggers • (Repairable) failure based triggers • Pre and post simulation strategies • Age profile • Numbers of failures • Numbers of interventions • Intervention costs, energy costs • Service WTP, carbon costs • Cost benefit assessment of each strategy • Change in risk/service benefits (between pre and post) • PV of Benefits • PV of Costs • NPV • Graph of breakdown of NPV by asset • Ranking of strategies – to select ‘best’ one

  24. :diagnostics/ :transformation/ :investment planning/ :portfolio optimisation/ :investment economics/ :regulation and economics/ :training/ Review of the water industry UKWIR project – when to repair, refurb or replace an assetICS Consulting November 2011

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