Deterioration modeling

[1][2] Deterioration models are instrumental to infrastructure asset management and are the basis for maintenance and rehabilitation decision-making.

A well-known model to show the probability of failure of an asset throughout its life is called bathtub curve.

In infrastructure asset management the dominant mode of deterioration is because of aging, traffic, and climatic attribute.

[3] If a state or class of the performance measure is of interest, Markov models and classification machine learning algorithms can be utilized.

A limitation of Markov models is that they cannot consider the history of maintenance,[3][10] which are among important attribute for predicting the future conditions.

Deterioration models developed based on Markov chain consider the condition of asset as a series of discrete states.

Crude Markov models have been criticized for disregarding the impact of ageing and maintenance history of the asset.

Despite their high learning capability, neural networks have been criticized for their black-box nature, which does not provide enough room for interpretation of the model.

The bathtub curve hazard function (blue, upper solid line) is a combination of a decreasing hazard of early failure (red dotted line) and an increasing hazard of wear-out failure (yellow dotted line), plus some constant hazard of random failure (green, lower solid line).
Schematic deterioration of an asset over time. The increase in performance indicators represent a maintenance action.
A road deteriorates over time, and its surface roughness increases. The road is located in Texas.