A sound Stochastic Aging Model, subsequently abbreviated to SAM, allows the network operator to validate and to optimize its maintenance, operating and rehabilitation decisions. The avoided costs due to the minimization of defect consequential risks and the positive effect on the total asset net value coming from the activation of potential savings and optimised budget planning and allocation can sum up to amounts totalling millions over time, depending on network size and condition. Simple stated SAM enables an increase in asset value because investment is done neither early, when existing asset value would be wasted, nor too late, when rehabilitation costs are too expensive.
A SAM analyses the existing, individual aging behaviour of a network. Based on this analysis and taking into account the maintenance decisions of the utility from the past, present and future (modelled in different utility specific strategies) SAM predicts the condition and system state (fabric decay) change at an object level at the present time (forecast today) and for the future. The prognosis of changes of condition and fabric decay until the end of service (determined as probability of failure of the object beyond the previously defined risk limit), allows a state-of-the-art prediction of the remaining service life of an object.
Default risks can thus be identified and the budget allocation of the rehabilitation/investment plans can be optimised regarding their timings and necessity depending on the remaining fabric decay reserve (pipe deterioration reserve). With this knowledge and incorporation of the strategic objectives of the utility, the technical and economical/financial consequences of rehabilitation measures can be simulated and possible alternatives can be compared against each other. Based on this strategy, simulations optimized solutions can be developed to achieve these goals.