Annie Vanrenterghem Raven, PhD, Principal, infraplan, LLC, New York, NY. Kurt Vause, Engineering Director, AWWU, Anchorage, Alaska

Transcription

1

2 Annie Vanrenterghem Raven, PhD, Principal, infraplan, LLC, New York, NY Kurt Vause, Engineering Director, AWWU, Anchorage, Alaska

3 infraplan Introduction Analytical? Analytical Program What does it take? Case Study - AWWU

4 Solutions to manage buried (non inspected or inspected) linear assets Main questions: How much money is needed for the next 20 years? What projects should be addressed in priority? Consulting; tools development; training; infraplan Service Answers using utility data and advanced approaches Based in NYC United Water 2/4/

5 Anchorage Apple Valley Rancho Aquarion Water of Ct Boston Columbus Dallas Denver Los Vegas Los Angeles (Park Water) Montreal New York Philadelphia San Diego United Water 2/4/

6 What do we mean with Analytical? What questions are we trying to answer? How will we do this? Why does it matter?

7 Analytical Asset Management study or program aims at making R&R decisions based on the analysis of utility-specific data.

8 How much money is needed for the next CIP? What projects should be selected in priority and when? Given that we: want to maintain a certain level of service can tolerate a certain level of risk

9

10 Utility Data Softwarealgorithm Output - Input Cost Break R&R Cons. of Failure Hydraulic Criticality GIS Pipes Inventory GIS Breaks Long Term Criticality Short -Term Asset Management Asset Management Software and Prioritization Software Plan Risk Score Plan CMMS Clean up Statistics Aging Function EULs Asset Management Plan Answer Q1 Q2 What Where are is the How output How info What Where much is future about projects results is money is from info needed behavior should pipes about a failure be until addressed predicted? attributes? forecasting breaks? 2050? first? model? Failure Forecasting Likelihood of Failure

11 Utility Data Softwarealgorithm Output - Input Cost Break R&R Cons. of Failure Hydraulic Criticality GIS Pipes Inventory GIS Breaks Long Term Criticality Short -Term Asset Management Asset Management Software and Prioritization Software Plan Risk Score Plan CMMS Clean up Statistics Aging Function EULs Why does it Asset Management Plan Answer Q1 Q2 What Where are is the How output How info What Where much is future about projects results is money is from info needed behavior should pipes about a failure be until addressed predicted? attributes? forecasting breaks? 2050? first? model? matter? Failure Forecasting Likelihood of Failure

12 Utility Data Softwarealgorithm Output - Input Cost Break R&R Cons. of Failure Hydraulic Criticality GIS Pipes Inventory Breaks Long Term Plan Short-Term Criticality Prioritization and Risk Plan Score CMMS Clean up Statistics EULs Asset Management Plan Answer Q2 Q1 What Where are is the How output How info What Where much is future about projects results is money is from info needed behavior should pipes about a failure be until addressed predicted? attributes? forecasting breaks? 2050? first? model? Failure Forecasting Likelihood of Failure

13 Assumed Scoring - $0 Lab $$$ Field Inspection $$ Analytics $

14 Break Rate by Age Break Rate (brk/mi/yr) Aging Function Do- Nothing 0,400 0,380 0,360 0,340 0,320 0,300 0,280 0,260 0,240 0,220 0,200 0,180 0, ,140 0,120 0,100 0,080 0,060 0,040 0,020 0, Age

15 To gauge the effect of a certain level of R&R It is the do-nothing reference

16 Blue Curve = Aging Function Do- Nothing

17 Credibility $$$ Total cumulative cost up to based on sources of EUL Industry Assumed EULs Utility and Risk Specific EULs Cost $M % Reduction ($2B) 65% Reduction ($1.2B) Year

18

19 Experts consider that % of the effort going to the first analytics-driven CIP-STP project is to be dedicated to data.

20 Structure Type of Personnel, Skills Tools - Analytical Algorithms Logistics Data Understanding of Risk and Service Levels Business Process development Leadership

21 Structure 1: All in house (AWWU) Structure 2: Nothing in house (Aquarion) Structure 3: Part in house (Denver Water)

22 Data Clean up Reorganizing Models Calibration Training Calibration updates Subsequent Runs Deliverables Structure 1 Structure 2 Structure 3 Utility Outside Expertise

23 Structure 1 Data review Clean up Re organizing Structure 2 Data review Clean up Data review Clean up Stats Model calibration First run Training Statistics Model re calibration Subsequent runs Stats Model calibration Runs Data clean up and re organizing overall direction CIP STP Reports CIP STP Algorithms Reports Structure 3 Data review Clean up Re organizing Data review Clean up Stats Model calibration First run Training Statistics Model re calibration Subsequent runs Simulation of scenarios of R&R CIP Standard Reports STP Standard Reports Utility Outside Expertise

24 Data Clean up Reorganizing Models Calibration Training Calibration updates Subsequent Runs Deliverables Structure 1 Director of Water GIS - IT GIS - Engineer Analyst Economist Structure 2 Mgr. Inf. Planning GIS - Consultant Structure 3 Planning Dept. GIS Planning Dept. - GIS Utility Outside Expertise

25 First run Data review and clean up: 1-3 months Data reorganizing: on-going Statistics calibration:1-3+ months (depends on type of study, size of system, deliverable) Point person Close and dynamic collaboration with all stakeholders Webcast Subsequent run Data review and clean up: 1+ month Statistics re-calibration: 1+ month

26 Tools Cost Break R&R Cons. of Failure Hydraulic Criticality GIS Pipes Long Term Short-Term Inventory Asset Management Criticality and Plan SoftwarePrioritization From Breaks free models and GIS applications to very Risk Plan expensive Score CMMS Clean up Statistics EULs Asset Management Plan infraplan Data Module Failure Forecasting Likelihood of Failure

27 Nature: Pipes and Breaks Source: GIS-CMMS-Hydraulic Model- Failure risk factors- Criticality Quality: Breaks assigned to pipes Pipes ACT and ABN Quantity: Understand and adjust for what is missing 5 yrs of breaks Format: Shape or excel

28

29 Risk Policy Service Standards Business Processes Team Collaboration Leadership Buy-in Refinement/continuous improvement

30 Impossible d afficher l image.

31

32

33

34 Requires 3 C s (clarity, consensus, commitment); Clarity of vision (specific, inclusive, honest in scope) Consensus to move forward (willingness to accept the vision) Commitment to achieve vision (resources, priority to attain vision, perseverance to overcome resistance

35

36 Concept that AWWU is building and maintaining a structure (work in progress) Need a policy foundation On foundation establish QA/QC product quality (back to example of EUL want an EUL that is fool proof) Choose quality material /incorporate them Do it with business processes (needed to collect data, to move data, analyze data, etc.) Need work force with different trades to execute the arrows in framework/program Owner approval (leadership group provides the resources) Maintain and continually improve to refine model

37 llc.com And Thank You!