Asset Management and Condition Assessment Best Practices. Jeffrey Sanford 2/28/2013 Joseph Zalla Jeffrey Sanford February 1, 2013

Transcription

1 Asset Management and Condition Assessment Best Practices Jeffrey Sanford 2/28/2013 Joseph Zalla Jeffrey Sanford February 1, 2013

2 Asset Management Definition Effective Asset Management is: An integrated set of processes to minimize the life-cycle costs of owning, operating and maintaining assets, at an acceptable level of risk, while continuously delivering established levels of service Implementing Asset Management A Practical Guide AMWA, NACWA, WEF 2007 Managing Public Infrastructure Assets to Minimize Costs and Maximize Performance AMSA, AMWA, AWWA, WEF 2002

3 Balancing Act. Minimize the life-cycle costs of assets Continuously deliver established levels of service At an acceptable level of risk Service Levels Low Costs RISK

4 Risk is quantified by the classic equation. Risk = (consequence x likelihood) How severe are the consequences of asset failure? How likely is it for the asset to fail?

5 Understanding the risk of asset failure provides The basis prioritizing capital investments for R&R The basis for optimizing O&M The basis for investing in condition assessments A uniform and rigorous manner that results in defensible decisions

6 Risk Based Approach Quantified by using the classic risk equation Risk = (consequence x likelihood) Levels of Service How severe are the consequences of asset failure? H, S implications Financial impact Regulatory compliance Public confidence Service delivery How likely is it for the asset to fail? Condition Reliability O&M Protocols Performance

7 Rio Rancho Consequence of Failure Matrix Consequence by Level of Service Category Rio Rancho LOS Category Wt. Negligible = 1 Low = 4 Moderate = 7 Severe = 10 Safety of public and employees 30% No injuries or adverse health effects No lost-time injuries or medical attention required Lost-time injury or medical attention required Loss of life or widespread outbreak of illness Financial impact 15% Can be repaired within Utility budget (<$2,500) Can be repaired between $2500 and $9,999 Can be repaired between $10,000 to $29,000. Greater than $30,000. Sealed bids and City Council approval required Public confidence 10% No social or economic impact on the community. No reactive media coverage. Any media coverage is a result of proactive announcements by Utility. No complaints. Minor disruption (e.g., traffic, dust, noise,water pressure). No adverse media coverage. Some complaints. Substantial but short-term disruption. Adverse media coverage due to public impact. Localized media coverage. Long-term impact. Areawide disruption. Regional media coverage. Regulatory compliance 25% No State or local permit violations. No SSO's Possible technical violation Probable enforcement action, but fines or surcharge unlikely Enforcement action with fines or surcharge Service Delivery 20% No impact Minor impact to process or out of service less than 24 hours. No SSO's or loss of service Major impact to process, out of service <24 hours. Potential SSO or loss of service Major impact to process, out of service >24 hours, outside services required, SSO' or loss of service

8 Rio Rancho Likelihood Matrix Likelihood Category Likelihood by Category Rio Rancho Wt Negligible = 1 Unlikely = 3 Possible = 5 Likely = 7 Very Likely = 10 Physical Condition 80% Very good. Condition Grade 1. New or nearly new. Only normal maintenance required. Good. Condition Grade 2. Minor wear. Fair. Condition Grade 3. Poor. Condition Grade 4. Major wear impacting level Unable to meet level of of service. service life. Failure imminent. Very poor. Grade 5. Requires complete rehabilitation or replacement. Failed. O&M Protocols (i.e., PMs, SOPs, JSAs)l 5% Complete, up-to-date, written, easily accessible and is being used. Complete, written, up-todate, being used but not easily accessible. Parially developed Written, but out-date and not used. No written protocols. Reliability 15% No corrective work order events within 12 months <2 corrective work order events within 12 months 2-5 corrective work order events within 12 months 6-8 corrective work order events within 12 months >8 corrective work order events within 12 months

9 Use consequence and likelihood scoring matrices to quantify risk of asset failure ASSET Safety of public and employees Financial impact on Utility Public confidence CONSEQUENCE Regulatory compliance Service Delivery Consequence Score Consequence Rank Physical Condition Performance (i.e., capacity, utilization and functionality of asset) LIKELIHOOD O&M Protocols (i.e., SOPs) Planned maintenance as a % of total maintenance Weight-> MILLS ELSWORTH HEACOCK CACTUS & NASON NASON & DRACAEA FREDERICK/ SUNNYMEAD MORENO PERRIS & FIR HEMLOCK ELDER MEDLEY PIGEON PASS ROAD VILLAGE ROAD PERRIS / IRONWOOD HIDDEN SPRINGS STEEPLECHASE / IRONWOOD STEEPLECHASE / KALMIA SUNNYMEAD PKWY PERRIS & KALMIA BOOSTER COVEY REDLANDS / COTTONWOOD Likelihood Score Likelihood Rank Risk Score Risk Rank

10 Use risk levels to prioritize detailed assessments Re-score likelihood of failure based on updated field information Recalculate risk

11 Based on risk assessment, identify areas with unacceptable levels of risk Relative Risk Score of Level 3 Assets Acceptable / Unacceptable Risk Level

12 Benefits from detailed condition assessment Identifies specific deficiencies in equipment assessed Identifies specific maintenance steps that may be taken to increase asset life and reduce likelihood of failure Provides data for the prioritization process Repeatable process that can be continued Repeated assessments of an asset will build a decay curve

13 Condition Assessment is a step-by-step process Gather asset data for the high risk assets identified Develop assessment criteria Upload data into the Asset Condition Evaluation System (ACES) tool Field condition assessment by experienced maintenance personnel Utilize data in prioritization process

14 Asset data gathering Assets and their characteristics are captured Typically, data is obtained from CMMS/GIS Once obtained, data is aligned to hierarchy and asset categories previously developed

15 Development of asset condition criteria Ask and answer predefined questions that relate to the asset condition Questions are grouped by asset type Answers for each question (criteria) are scored from 1 to 5

16 Upload data to the SQL database Pre-populated with risk analysis Condition data gathered is entered into ACES

17 On-site condition assessment

18 Condition assessment data will then be used to: Identify specific deficiencies in equipment assessed Develop condition summary Provide data for the prioritization process Produce multiple reporting options

19 Rio Rancho Water Utility Optimized Asset Management Decision Process

20 Summary Data

21 ATF, 809, 36% System Asset Count Booster Station, 164, 7% Lift Station, 199, 9% Well, 231, 10% Reservoir, 16, 1% WWTP, 825, 37%

22 System Asset Value Booster Station, $1,604,223, 3% ATF, $12,883,032, 29% Lift Station, $2,728,647, 6% Reservoir, $8,914,639, 20% WWTP, $13,349,150, 30% Well, $5,529,642, 12%

23 All Asset Trigger Score Range

24 Replacement Schedules and Costs Water Production Wastewater Treatment Total Capital Plan $ 70,000 $ 63,000 $133,000 Repairs and Maintenance $ 11,600 $ 14,200 $ 25,800 TOTAL $ 81,600 $ 77,200 $158,800

25 Production Repair and Replacement Schedule Based on Equipment Lifespan $8,000,000 $7,000,000 $6,000,000 $5,000,000 $4,000,000 $3,000,000 $2,000,000 $1,000,000 $ Production Production CM

26 Wastewater Repair and Replacement Schedule Based on Equipment Lifespan $6,000,000 $5,000,000 $4,000,000 $3,000,000 $2,000,000 $1,000,000 $ Wastewater Wasterwater CM

27 Combined CM and Replacement Schedule Based on Equipment Lifespan $10,000,000 $9,000,000 $8,000,000 $7,000,000 $6,000,000 $5,000,000 $4,000,000 $3,000,000 $2,000,000 $1,000,000 $

28 10,000,000 Statistical 5 year NPV Plot versus Typical Lifespan Model 9,000,000 8,000,000 7,000,000 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 0 Year 1 Year 6 Year 11 Year 16 Year 21 Year 26 Simulated Time (Years)

29 10,000,000 Statistical 5 year Pay Back Plot versus Typical Lifespan Model 9,000,000 8,000,000 7,000,000 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000 0 Year 1 Year 6 Year 11 Year 16 Year 21 Year 26 Simulated Time (Years)

30 Optimized versus 5 year NPV Model 5,000,000 4,500,000 4,000,000 3,500,000 3,000,000 2,500,000 2,000,000 1,500,000 1,000, ,000 With 5-year payback rule Optimized Replacement Policy Simulated Time (Years)

31 Questions???