Long-term maintenance planning for increased efficiency in managing underground utilities

Aug 22, 2006

When utilities plan maintenance measures for network assets, they first have to decide which assets should be targeted. Nowadays these decisions are often still made from a vast empirical knowledge, accumulated in these utilities over decades. Apart from the fact that empirical-based decisions are often difficult to explain to non-technicians or economists, there is still the danger of missing an aspect due to the size of these networks. STATUS supports the planning process and the inherent decisions by providing an analytical framework, enhancing the planning process, giving long-term planning safety and continuity.

Wastewater systems as well as drinking water and gas distribution infrastructures are impacted by ageing and therefore facing a decline of their performance. Breaks, cracks, bursts, corrosion and other types of failures cause leakage/ water losses, hydraulic bottlenecks etc., up to collapsing sewers and bursting distribution mains, which leads to remarkable economical risks and environmental hazards. Maintenance planning of those systems therefore need to take economical and ecological aspects into account besides the hydraulic, operational and structural capability. Despite these problems, maintenance measures set up to tackle the problems have to deal with tight budgets additionally.
This problem cannot be solved satisfyingly by conventional assessment systems and common maintenance planning approaches. To activate all saving potentials within the planning process, the complete network data must serve as base for the planning, being analyzed with sophisticated tools, not only for the current state but forecasting the upcoming states as well. Only this prevents from misspending budgets on premature maintenance or even worse, postponed maintenance on assets with undetected top-priority.
STATUS developed by "Stein & Partner" masters the complexity of the topic with a multistage service framework for sustainable asset management of urban pipe infrastructures, which incorporates new analytical assessment approaches with existing empiri-cal knowledge of the utilities giving the customer significant benefits due to increased planning speed and accuracy as well as reduced maintenance costs.
Data management and plausibility verification

The starting point of each qualified analytical network assessment is an extensive analysis of the existing data as the accuracy and sig-nificance of the following assessment decisively depends on the completeness and consistency of the data taken as a basis.
The plausibility analysis integrated in STATUS checks in three steps the formal integrity of the data, the logical evidence of related data and the development of the data over time. The formal plausibility analysis identifies datasets that do not correspond with the predefined data format of the utility as agreed upon e.g. incorrect defect codes for sewer inspections. The logical plausibility analysis identifies inconsistencies between related data, e.g. pipe age of 100 years but pipe material HDPE. The last step indicates implausible data changes over time where the datasets as such are plausible, e.g. incorrect damage developments within an inspected sewer like vanished or "healed" defects.
Having finished the plausibility analysis all data failures detectible by such data mining techniques are uncovered. Further improvements of the data situation can only be achieved either by additional data acquisi-tion or manual data proofing. Both alternatives are time-consuming and costly.
Assessment of the present situation

The conventional systems for evaluating the present condition of net assets are only using limited information to determine the priority of maintenance action. For sewer networks in almost all cases the damage class of the worst single defect is taken, thus describing a locally limited condition. Those damage classes result from binary assessment logic, having strict class thresholds. STATUS uses fuzzy logic which results in soft class transitions rather than in strict class changes. New, innovative damage models are additionally used, reflecting the real situation far better than the common systems. This is achieved by including all relevant data available into the damage models.
By extending the common systems STATUS introduces the asset substance determining the existing wear reserve of an asset and thus indicates how to react in case of rehabilitation action induced by the asset priority. The asset substance for sewer sys-tems is determined by the severity of all defects of this asset and the local distribution within the asset. The substance of an asset is additionally analyzed from the viewpoint of structural stability, operational performance and environmental impact. For distribution systems, failure data e.g. burst rates/ leakage rates are the main indicator for condition assessment.
The result of the assessment of the present situation is a picture of the present performance level of the whole network, which is as closed to reality, due to the new approaches of STATUS. As a consequence of the significantly more differentiated and more realistic evaluation results, the risk of wrong decisions within the scope of the rehabilitation planning is clearly reduced.
Forecasting of the future asset development

For advanced and long-term maintenance planning it is necessary to forecast the devel-opment of the asset condition and substance into the future, thus determining the aging process of these assets. This ensures security in planning and gives the possibility of identi-fying assets, which are low priority at present but are likely to enter critical states very fast.
The aging process of the assets depends on a variety of influencing factors and inter-dependencies similar to the lifetime of humans and cannot be grasped mathemati-cally for a specific individual case. For the aging prediction the observed network aging of the past is mathematically projected into the future. For that purpose the cohort sur-vival model, which was developed in demography, is applied. In this case cohorts describe construction age groups that survive with decreasing probability the older they get.
According to that, the service life of an asset is a statistic random variable to which a probability distribution can be created. The probability by which a construction cohort survives a certain state is described by the survival function, derived from the service life distributions.
The example of Figure 5 illustrates, that 50-years-old water distribution pipes in the observed network are still in service probability of ca. 12 % on average under pessimistic assumptions and with an probability of 50 % under optimistic conditions.
Whereas the survival functions illustrate the average aging behavior of single charac-teristic groups, which has been observed in the past, an extended analysis is necessary for the prediction of the development of a network and single network elements, using the model of time-discrete Markov chains. It gives the possibility of determining the transition probabilities between the different states that an asset will reach until the final state.
The transition probabilities are calculated based on the specific aging functions. In Figure 6 the forecast of the substance development for a sewer section is illustrated in five-year-steps exemplarily. The initial distribution represents today's substance value distribution and the probability of a failure increases continuously.
Strategy development and analysis

The forecast of the future development of net assets with STATUS is the basis for the analysis of effectiveness maintenance deci-sions. Various key factors like budget size, burst rate, leakage rate, failure risk, ecologic and hydraulic requirements as well as further network-specific limiting conditions allow the definition and analysis of individual maintenance strategies answering questions like the budget needed to hold/ reach a certain service level or how tariffs are affected by defined strategies. Predicting and controlling rehabilitation costs, asset value, failure risks in advance is the main benefit from strategies as well as the information of how key factors of the utility will change by doing nothing or to little. The next figures illustrate consequences of different maintenance strategies, e.g. Figure 8 showing the changes in asset value.
Conclusions

In summary, with STATUS it is possible to balance utility needs like operating costs, asset values, operating stability and service level with the public target of minimizing risk and the customers’ needs of tariff and service stability. STATUS is fulfilling the request of German authorities and customers and has been widely used and approved due to its transparent and reproducible results and the significant benefit in time and costs.



This article was published with kind permission of Trenchless Australasia.

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