Availability is the ability of a service or a system to be functional when it is requested for use or operation. Availability of a system is a function of often the system fails (reliability) and how efficiently it can be maintained when it does fail. There are different approaches to maintenance, but fundamentally, depending on if a system has failed, when it is projected to fail, how it has failed, and the requirements placed on the enterprise that the system is a member of, there are decisions that need to be made about how to and when to maintain it.
For infrastructure-critical systems (such as wind farms), customers are moving towards buying the availability of a system through “availability contracts,” instead of actually buying the system itself. Evaluating an availability requirement is a challenge for the supporters of wind farms because determining how to deliver (and the cost of delivering) a specific availability is not trivial, and understanding how to “flow” availability contract requirements to a supply chain is unclear.
The development of “design for availability” approaches, where “design” refers to not only system design, but more importantly the design of the logistics to support the system, is in its infancy. The optimum design and/or management of a single member of a population (e.g., one turbine) to meet an availability requirement is not generally the optimum for meeting the availability requirement for the population of systems (e.g., a wind farm). The figure below shows an example for an avionics subsystem where both of the shown maintenance solutions satisfy the same fleet availability requirement. The data-driven PHM solution (right-most distribution) is preferable because it allows longer inventory lead times (ILT).
Computed maximum allowable inventory lead time (ILT) for unscheduled
maintenance policy, and for a data-driven PHM approach.
ILT is the duration of time between ordering spares and receiving them.
ILT can be an important differentiator between sources for critical parts.