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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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: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


Agenda

  • Intro to the UKWIR project

    • Objectives

    • Deliverables

  • Key findings of the project

  • Application

    • Demo of the tool


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


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.


Summary of the Risk Modelling Process


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


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


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


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


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


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


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


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


  • 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.


    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


    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


    Examples and Demo of the Tool


    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


    What does the data need to look like?

    • Excerpt of the failure data for actuator…..

    • Need to model qualitative data as a dummy


    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 !


    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


    Looking at the Tool…..


    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


    :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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