Factors for Comparing Life Cycle Management Approaches
Failing to achieve a service level target requires an intervention, or reassessment of the reasonableness of the target. If improvement is required, selecting a management strategy is a function of where performance is insufficient. Safety improvements can reduce crash rates, additional lane capacity can improve travel time reliability, operational enhancements can improve emergency response rates and road availability during inclement weather. Where condition is below target, at a network or corridor level, interventions may be required in multiple areas.
Selecting interventions to achieve condition targets for an asset class or subclass is a data-driven, risk-based process. It evaluates what circumstances lead to asset failure, the subsequent consequences of failure, the options available to avoid failure and their costs. Costs should include the cost to monitor/analyze/ manage an asset in addition to the cost to repair. Based on an understanding of these factors, an agency can determine what strategy will be the most appropriate. The three management strategies introduced in the previous section are incorporated into Table 4.2 along with summaries of the various factors used to compare the approaches.
Table 4.2 - Comparison of Management Strategy Approaches.
Adapted from SAE International 2009
|Decision Making (intervention) Approach||Selects intervention based on a forecasted condition exceedance interval.||Asset is treated based on a time or usage basis whether it needs it or not.||Treatment is performed to fix a problem after it has occurred.|
|Data Needs||Inventory information (Asset / Component)|
Historical condition and expert data – deterioration curves
Current condition and defect data
Historical Intervention and cost data – intervention strategies.
Asset / component type and material data
Intervention thresholds for condition
|Inventory information (Asset / Component)|
Asset / component age
Remaining useful life of asset / component
Timing and type of last action
Interrelationships of different interventions, and how they affect the selection and timing of downstream actions
|Inventory information (Asset / Component)
Current Condition data
Intervention thresholds for condition
Historical cost data
|Life Cycle Planning Expectations||Require the ability to understand the effects of different funding strategies.|
Wish to forecast the future condition state of the network or specific asset classes.
Wish to minimize the life cycle cost.
|Wish to gain an understanding of the typical average cost to manage the network or specific asset classes||General costs estimates based on experience.
Limited need to actively manage the asset.
|Considerations||Cost of collecting and analyzing condition information and developing forecasting models.||Diminished cost effectiveness / efficiency compared to condition modeling.|
Does not support knowledge development of asset behavior (inhibiting the move to more cost-effective regimes).
|Often considered immature but is appropriate for assets if only minor consequences occur from a service disruption.|
|Typical Usage Cases||High risk / criticality assets or risk must be more actively managed.|
Large portfolios or high value assets of similar construction forms
Scenario planning is required
Long-lived assets that can have numerous management approaches applied to them.
More advanced asset management planning is required
Cost uncertainty over time must be assessed (stochastic modeling)
|Moderate or low risk assets.|
Mandated manufactures management regimes or Short-lived assets
Buried assets where condition data is hard to obtain.
Assets where the cost to collect condition data is expensive relative to the maintenance activity that is required
|Low risk or criticality assets.
Assets where the effects of accumulated defects are not critical to their functionality.
Assets that are likely to be subject to unforeseen events or impairment e.g. barriers or light poles.