LANI GOOD, PE COURTNEY HALL, PE - · PDF fileINFOMASTER SEWER RISK ASSESSMENT CALIBRATION...
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INFOMASTER SEWER RISK ASSESSMENT CALIBRATION InfoMaster User Group Meeting | December 9, 2016 LANI GOOD, PE COURTNEY HALL, PE
Transcript of LANI GOOD, PE COURTNEY HALL, PE - · PDF fileINFOMASTER SEWER RISK ASSESSMENT CALIBRATION...
INFOMASTER SEWERRISK ASSESSMENT CALIBRATIONInfoMaster User Group Meeting | December 9, 2016
LANI GOOD, PE COURTNEY HALL, PE
Presentation Outline
Introduction Initial Risk Model Setup Risk Calibration Results Validation
Introduction
USD Study
USD system: 787 miles of gravity sewer, 6 pump stations, and 25 miles of force mains
Project Goal: Use a business risk assessment to guide modifications to the CS preventative maintenance program
Initial Risk Model Setup
Risk Assessment Methods
Bi-directional Distribution Custom 3x3 or 5x5
LOFxCOF Matrix Linear Normalization
Classification For a monetary
assessment
Linear Normalization Classification Method
Risk Assessment Methods
Bi-directional Distribution Custom 3x3 or 5x5
LOFxCOF Matrix Calibrated by Value or %
Linear Normalization Classification For a monetary
assessment Multi-Criterion Classification
Optimistic risk vs. pessimistic risk
Asset Grading Classification
Developing Risk Factors/Criteria
Limit the number of criteria used Considerations for valid criteria: Evaluation information must be readily available
Example: Manhole proximity to storm drain outfall to creek
The same evaluation information should not be used for more than one criterion Example: Street classification as a factor for Emergency
Access and for Public Traffic Impacts
Evaluation information must be available for a majority of assets Example: Sewer Likelihood of Structural Failure partial CCTV
data vs. pipe age data used to evaluate
Filling Data Gaps Using Proxy Data
Typical Sewer Failure Modes
Structural Failure Maintenance Failure Hydraulic Capacity Failure
Likelihood of Failure Rating Factors
Structural Defect Score
Pipe Installation Year (Proxy for Structural Defects)
Likelihood of Failure Rating Factors
Typical Maintenance Failure Factors
CCTV Maintenance Defects Strong indicator if Positive Weak indicator if Negative
Pre-CCTV cleaning and root cutting Low-frequency CCTV inspection vs. maintenance defect
reoccurrence
High Frequency Maintenance Schedule Couldn’t use for USD because if high PM frequency = high
risk, then study couldn’t evaluate reducing the PM frequency
Number of Non-routine Work Order Hours Number of Total Work Orders
Maintenance Defect Score
Non-Routine Labor Hours
Rating Scale, Logic, Weighting
Rating Scale 1-10 scale vs. 1-5 scale
1-10: how do you define a difference between a 6 and a 7?
When to use 0 vs. 1
Rating Scale, Logic, Weighting
Rating Logic Weighting Internal weighting in 0-5 scale
Weighting factors
InfoMaster DemoRating Scale, Rating Logic, and Weighting
Typical Sewer Consequences of Failure Regulatory Compliance Impacts Impacts to Environmentally Sensitive Areas Public Health Impacts Emergency Response Cost
Consequence of Failure Rating Factors
Public Exposure
Risk Calibration
Calibration
Risk Assessment Goals Phasing – somewhat equal risk categories by %
Max/Min Scaling – pipes scored in both upper and lower risk areas
Monetary evaluation
Initial Results – Factor by Factor Looking for differentiation between scores – using
GIS figures
Adjust ranges of values in each rating category
Risk Calibration
Setting 5x5 or 3x3 risk matrix score boundaries By % of pipes (quantity or length) in each risk level
By value - using engineering judgement
InfoMaster DemoRisk Calibration
Demo – Risk Calibration
Final Risk Results
Results Validation
USD Map – Figure 20 Results
Risk Assessment Results
Results Validation
Results Validation
USD Map – Figure 20 Results
Risk Assessment Results
Results Validation
Results Validation
