In asset management, the whole life costing model is normally initiated to meet the following two broad strategic objectives:

  • to ensure sufficient funding is available to maintain the asset portfolio
  • to ensure minimum whole-life cost is achieved while maintaining safety

If interventions are delayed due to resources constraints such as lack of funding, the consequences on safety and implications on later costs are not known to us, it could result in much greater costs later as a penalty. We conduct research on the whole life costing model that provides a means of answering the question of what will be the future cost of recovering the degraded portfolio condition.

Our research starts with a study of the historical maintenance records. We find, in many industries, it is quite common that most of the maintenance records are stored in paper format rather than electronically, which is impractical to use as it takes tens of thousands man hours to interpret. It is therefore acknowledged that a statistical estimation of costs and timing of interventions is needed. First, we investigate a sample of assets to gather some detailed information. Second, in many industries, although the companies may not know the detailed status of all their assets, a large amount of general and local knowledge and expertise is inevitable acquired in routine data collection practices. Adopting Bayes linear methods, we estimate the costs and timing of interventions based on the detailed information from a sample of assets combined with the experts’ knowledge.

Whole life costing model is built based on the statistical estimation of costs and timing of interventions. The program of work for any given maintainable item is a set of interventions with times relative to the start of the whole life cost plan. Once the whole life costing model is set up and running, the inspection and intervention information will be fed into the system when they become available, the optimal cycle lengths will be determined, and least whole life cost plan will be achieved.