Uncertainty in Municipal Maintenance Models
The project uses abstract assets to test which assumptions change a maintenance priority list most. Completed in the scenario; outputs are illustrative.
Problem
A single model curve can conceal highly uncertain maintenance assumptions. The priority list then appears more certain than the underlying assumptions justify.
Research question
Which assumptions change a priority list most? The answer is meant to show which assumptions the ranking is particularly sensitive to.
Method
Discrete state transitions are modelled for abstract assets. On this basis, parameter ranges are defined and sensitivity runs are carried out.
Evaluation criteria
The criteria are rank stability, the range of maintenance demand and the share of unexplained model assumptions. No measured values are reported here.
Expected outcome
Completed in the scenario. The illustrative output is a transparent small model example with varying assumptions. It is not a recommendation for real assets and contains no measured results.
Limits
The model is not empirically calibrated and is not intended for municipal deployment planning.
Publications
- U02
- U07