In reliability engineering, the term availability has the following meanings:
- The degree to which a system, subsystem or equipment is in a specified operable and committable state at the start of a mission, when the mission is called for at an unknown, i.e. a random, time.
- The probability that an item will operate satisfactorily at a given point in time when used under stated conditions in an ideal support environment.
Normally high availability systems might be specified as 99.98%, 99.999% or 99.9996%.
The simplest representation of availability (A) is a ratio of the expected value of the uptime of a system to the aggregate of the expected values of up and down time (that results in the "total amont of time" C of the observation window)
Another equation for availability (A) is a ratio of the Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR), or
If we define the status function as
therefore, the availability A(t) at time t > 0 is represented by
Average availability must be defined on an interval of the real line. If we consider an arbitrary constant , then average availability is represented as
Limiting (or steady-state) availability is represented by
Limiting average availability is also defined on an interval as,
Availability is the probability that an item will be in an operable and committable state at the start of a mission when the mission is called for at a random time, and is generally defined as uptime divided by total time (uptime plus downtime).
Methods and techniques to model availabilityEdit
- Reliability models
- Maintainability models
- Maintenance concepts
- Common cause failure
- Level of repair
- Repair status
- Dormant failures
- Test coverage
- Active operational times / missions / sub system states
- Logistical aspects like; spare part (stocking) levels at different depots, transport times, repair times at different repair lines, manpower availability and more.
- Uncertainty in parameters
Furthermore, these methods are capable to identify the most critical items and failure modes or events that impact availability.
Definitions within systems engineeringEdit
Availability, inherent (Ai)  The probability that an item will operate satisfactorily at a given point in time when used under stated conditions in an ideal support environment. It excludes logistics time, waiting or administrative downtime, and preventive maintenance downtime. It includes corrective maintenance downtime. Inherent availability is generally derived from analysis of an engineering design:
- The impact of a repairable-element (refurbishing/remanufacture isn't repair, but rather replacement) on the availability of the system, in which it operates, equals mean time between failures MTBF/(MTBF+ mean time to repair MTTR).
- The impact of a one-off/non-repairable element (could be refurbished/remanufactured) on the availability of the system, in which it operates, equals the mean time to failure (MTTF)/(MTTF + the mean time to repair MTTR).
It is based on quantities under control of the designer.
Availability, achieved (Aa)  The probability that an item will operate satisfactorily at a given point in time when used under stated conditions in an ideal support environment (i.e., that personnel, tools, spares, etc. are instantaneously available). It excludes logistics time and waiting or administrative downtime. It includes active preventive and corrective maintenance downtime.
Availability, operational (Ao)  The probability that an item will operate satisfactorily at a given point in time when used in an actual or realistic operating and support environment. It includes logistics time, ready time, and waiting or administrative downtime, and both preventive and corrective maintenance downtime. This value is equal to the mean time between failure (MTBF) divided by the mean time between failure plus the mean downtime (MDT). This measure extends the definition of availability to elements controlled by the logisticians and mission planners such as quantity and proximity of spares, tools and manpower to the hardware item.
Refer to Systems engineering for more details
- MTTF in hours = 81.5 × 365 × 24 = 713940 (This is a reliability parameter and often has a high level of uncertainty!)
- Inherent availability (Ai) = 713940 / (713940+1) = 713940 / 713941 = 99.999860%
- Inherent unavailability = 1 / 713940 = 0.000140%
Outage due to equipment in hours per year = 1/rate = 1/MTTF = 0.01235 hours per year.
Availability is well established in the literature of stochastic modeling and optimal maintenance. Barlow and Proschan  define availability of a repairable system as "the probability that the system is operating at a specified time t." Blanchard  gives a qualitative definition of availability as "a measure of the degree of a system which is in the operable and committable state at the start of mission when the mission is called for at an unknown random point in time." This definition comes from the MIL-STD-721. Lie, Hwang, and Tillman  developed a complete survey along with a systematic classification of availability.
Availability measures are classified by either the time interval of interest or the mechanisms for the system downtime. If the time interval of interest is the primary concern, we consider instantaneous, limiting, average, and limiting average availability. The aforementioned definitions are developed in Barlow and Proschan , Lie, Hwang, and Tillman , and Nachlas . The second primary classification for availability is contingent on the various mechanisms for downtime such as the inherent availability, achieved availability, and operational availability. (Blanchard , Lie, Hwang, and Tillman ). Mi  gives some comparison results of availability considering inherent availability.
Availability considered in maintenance modeling can be found in Barlow and Proschan  for replacement models, Fawzi and Hawkes  for an R-out-of-N system with spares and repairs, Fawzi and Hawkes  for a series system with replacement and repair, Iyer  for imperfect repair models, Murdock  for age replacement preventive maintenance models, Nachlas [1998, 1989] for preventive maintenance models, and Wang and Pham  for imperfect maintenance models. A very comprehensive recent book is by Trivedi and Bobbio .
- Elsayed, E., Reliability Engineering, Addison Wesley, Reading, MA,1996
- "Inherent Availability (AI)". Glossary of Defense Acquisition Acronyms and Terms. Department of Defense. Archived from the original on 13 April 2014. Retrieved 10 April 2014.
- "Achieved Availability (AI)". Glossary of Defense Acquisition Acronyms and Terms. Department of Defense. Archived from the original on 13 April 2014. Retrieved 10 April 2014.
- "Operational Availability (AI)". Glossary of Defense Acquisition Acronyms and Terms. Department of Defense. Archived from the original on 12 March 2013. Retrieved 10 April 2014.
- "Mandatory Reporting of Conventional Generation Performance Data" (PDF). Generating Availability Data System. North American Electric Reliability Corporation. July 2011. pp. 7, 17. Retrieved 13 March 2014.
This article incorporates public domain material from the General Services Administration document: "Federal Standard 1037C". (in support of MIL-STD-188) K. Trivedi and A. Bobbio, Reliability and Availability Engineering: Modeling, Analysis and Applications, Cambridge University Press, 2017.