Installation of new infrastructure assets creates streams of services and improvements to existing services for users. Benefits accrue to these uses as well as a wider set of stakeholders. Maintaining the service potential is a critical element in ensuring that value for money is achieved from the initial capital investment.
However, many governments and asset managers are under significant pressure to trim maintenance budgets and scrimp on operating costs. In some contexts, this emerges as an extreme build-neglect-build scenario. Many Pacific Island nations experience this, as do a number of smaller Australian local government authorities. The full lifecycle cost of infrastructure assets is not factored into the budget planning processes of these organisations. Similarly, many private sector operators of infrastructure have commercial and financial incentives to focus on next quarter financial performance rather than long-term service provision from these assets.
The back end of infrastructure is seen as much less interesting, but it is where all the benefits are generated. So approaches to operating and maintaining these infrastructure assets is as equally critical as the planning and investment decisions to deliver them.
Two broad maintenance strategies are predictive maintenance and condition based maintenance. Predictive maintenance is like regular scheduled servicing based on the design performance of an infrastructure asset. It is less costly to implement but also less likely to match the actual performance of the asset. Condition based maintenance requires the collection of data and information about the actual performance of the asset and provision of a tailored asset maintenance response.
The approaches set up an economic challenge. Should an infrastructure manager simply maintain its assets according to schedule and only collect data and information on condition at the times of regularly scheduled servicing? Or should some initial data costs be incurred to change and adapt design-based, predictive maintenance? Decisions to underfund reasonable maintenance activities need to be made with good information and in an appropriate strategic context.
So it depends. In one sector, for example, the response is clear but not clear-cut. Analysis of wind turbine maintenance to address gearbox, generator and blade failure scenarios shows that for small wind turbines, predictive maintenance is more cost effective than condition based maintenance. Condition based strategies were based on an array of sensor data (optical, oil, vibration and temperature). However, for larger turbines, condition based maintenance where there is a high expected gearbox failure rate is a much better approach. In that instance, the cost of collecting additional data and information enables timelier and more appropriate servicing of the turbines.
For these reasons, infrastructure owners and managers need to ensure there are effective asset management and maintenance policies included in their strategic asset management frameworks. It is not enough to supply the assets, as only the services from them will be able to generate the full suite of expected benefits. This can only be achieved when the design potential of these assets is realised over time.