Availability
Inreliability engineering,the termavailabilityhas the following meanings:
- The degree to which asystem,subsystemor 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.
Normallyhigh availabilitysystems might be specified as 99.98%, 99.999% or 99.9996%.
Representation
[edit]The simplest representation ofavailability(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 amount of time"Cof the observation window)
Another equation foravailability(A) is a ratio of the Mean Time To Failure (MTTF) and Mean Time Between Failure (MTBF), or
If we define the status functionas
therefore, the availabilityA(t) at timet> 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[1]
Limiting average availability is also defined on an intervalas,
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 availability
[edit]Reliability Block DiagramsorFault Tree Analysisare developed to calculate availability of a system or a functional failure condition within a system including many factors like:
- Reliability models
- Maintainability models
- Maintenance concepts
- Redundancy
- Common cause failure
- Diagnostics
- 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 engineering
[edit]Availability, inherent (Ai)[2] 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, equalsmean time between failuresMTBF/(MTBF+mean time to repairMTTR).
- The impact of a one-off/non-repairable element (could be refurbished/remanufactured) on the availability of the system, in which it operates, equals themean time to failure(MTTF)/(MTTF + themean time to repairMTTR).
It is based on quantities under control of the designer.
Availability, achieved (Aa)[3] 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)[4] 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 toSystems engineeringfor more details
Basic example
[edit]If we are using equipment which has amean time to failure(MTTF) of 81.5 years andmean time to repair(MTTR) of 1 hour:
- 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%
—Ả≥〈〉〈〉〈〉
- Inherent unavailability= 1 / 713940 = 0.000140%
Outage due to equipment in hours per year = 1/rate = 1/MTTF = 0.01235 hours per year.
Literature
[edit]Availabilityis well established in the literature ofstochastic modelingandoptimal maintenance.Barlow and Proschan [1975] define availability of a repairable system as "the probability that the system is operating at a specified time t." Blanchard [1998] 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 [1977] 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 systemdowntime.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 [1975], Lie, Hwang, and Tillman [1977], and Nachlas [1998]. 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 [1998], Lie, Hwang, and Tillman [1977]). Mi [1998] gives some comparison results of availability considering inherent availability.
Availability considered in maintenance modeling can be found in Barlow and Proschan [1975] for replacement models, Fawzi and Hawkes [1991] for an R-out-of-N system withsparesand repairs, Fawzi and Hawkes [1990] for a series system with replacement and repair, Iyer [1992] for imperfect repair models, Murdock [1995] for age replacement preventive maintenance models, Nachlas [1998, 1989] for preventive maintenance models, and Wang and Pham [1996] for imperfect maintenance models. A very comprehensive recent book is by Trivedi and Bobbio [2017].
Applications
[edit]Availability factoris used extensively inpower plant engineering.For example, theNorth American Electric Reliability Corporationimplemented theGenerating Availability Data Systemin 1982.[5]
See also
[edit]- Dependability
- Reliability engineering
- Safety engineering
- List of system quality attributes
- Spurious trip level
- Condition-based maintenance
- Fault reporting
- High availability
- RAMS
References
[edit]- ^Elsayed, E.,Reliability Engineering,Addison Wesley, Reading, MA,1996
- ^"Inherent Availability (AI)".Glossary of Defense Acquisition Acronyms and Terms.Department of Defense. Archived fromthe originalon 13 April 2014.Retrieved10 April2014.
- ^"Achieved Availability (AI)".Glossary of Defense Acquisition Acronyms and Terms.Department of Defense. Archived fromthe originalon 13 April 2014.Retrieved10 April2014.
- ^"Operational Availability (AI)".Glossary of Defense Acquisition Acronyms and Terms.Department of Defense. Archived fromthe originalon 12 March 2013.Retrieved10 April2014.
- ^"Mandatory Reporting of Conventional Generation Performance Data"(PDF).Generating Availability Data System.North American Electric Reliability Corporation. July 2011. pp. 7, 17.Archived(PDF)from the original on 2022-10-09.Retrieved13 March2014.
Sources
[edit]This article incorporatespublic domain materialfromFederal Standard 1037C.General Services Administration.Archived fromthe originalon 2022-01-22.(in support ofMIL-STD-188).
- K. Trivedi and A. Bobbio,Reliability and Availability Engineering: Modeling, Analysis and Applications,Cambridge University Press, 2017.