A product's service life is its expected lifetime, or the acceptable period of use in service.
It is the time that any manufactured item can be expected to be 'serviceable' or supported
by its manufacturer.
Expected service life consists of business policy, using tools and calculations from
maintainability and reliability analysis.
Service life is a unique commitment made by the item's manufacturer and is usually specified
as a median.
Actual service life is the maximal recorded life of a product.
Service life is different from a predicted life, or MTTFMFOP.
Predicted life is useful such that a manufacturer may estimate, by hypothetical modeling and
calculation, a general rule for which it will honor warranty claims, or planning for mission
fulfillment.
The difference between service life and predicted life is most clear when considering mission
time and reliability in comparison to MTBF and service life.
For example: A missile system can have a mission time of less than one minute, a service life
of 20 years, active MTBF of 20 minutes, dormant MTBF of 50 years and a reliability of .999999.
A consumer item will have different expectations about service and longevity based upon factors
such as use, cost, and quality.
Product strategy Manufacturers will commit to very conservative
service life, usually 2 to 5 years for most commercial and consumer products.
However, for large and expensive durable goods, the items are not consumable, and service
lives and maintenance activity will factor large in the service life.
Again, an airliner might have a mission time of 11 hours, a predicted active MTBF of 10,000
hours with maintenance, a reliability of .99999 and a service life of 40 years.
The most common model for item lifetime is the bathtub curve, a plot of the varying failure
rate as a function of time.
During early life, the bathtub shows increased failures, usually witnessed during product
development.
The middle portion of the bathtub, or 'useful life', is a slightly inclined, nearly constant
failure rate period where the consumer enjoys the benefit conferred by the product.
As the time increases further, the curve reaches a period of increasing failures, modeling
the product's wearout phase.
For an individual product, the component parts may each have independent service lives, resulting
in several bathtub curves.
For instance, a tire will have a service life partitioning related to the tread and the
casing.
Examples For maintainable items, those wear-out items
that are determined by logistical analysis to be provisioned for sparing and replacement
will assure a longer service life than manufactured items without such planning.
A simple example is automotive tires - failure to plan for this wear out item would limit
automotive service life to the extent of a single set of tires.
An individual tire's life follows the bathtub curve, to boot.
After installation, there is a not-small probability of failure which may be related to material
or workmanship or even to the process for mounting the tire which may introduce some
small damage.
After the initial period, the tire will perform, given no defect introducing event such as
encountering a road hazard, for a long duration relative to its expected service life which
is a function of several variables.
After a period, the failure probability will rise; for some tires, this will occur after
the tread is worn out.
Then, a secondary market for tires puts a retread on the tire thereby extending the
service life.
It is not uncommon for an 80,000-mile tire to perform well beyond that limit.
It may be difficult to obtain reliable longevity data about many consumer products as, in general,
efforts at actuarial analysis are not taken to the same extent as found with that needed
to support insurance decisions.
However, some attempts to provide this type of information have been made.
An example is the collection of estimates for household components provided by the Old
House Web which gathers data from the Appliance Statistical Review and various institutes
involved with the homebuilding trade.
BOL and EOL For certain products, such as those that cannot
be serviced during their operational life for technical reasons, a manufacturer may
calculate a product's expected performance at both the beginning of operational life
and end of operational life.
Batteries and other components that degrade over time may affect the operation of a product.
The performance of mission critical components is therefore calculated for EOL, with the
components exceeding their specification at BOL.
For example, with spaceflight hardware, which must survive in the harsh environment of space,
the capacity to generate electricity from solar panels or radioisotope thermoelectric
generator is likely to reduce throughout a mission, but must still meet a specific requirement
at EOL in order to complete the mission.
A spacecraft may also have a BOL mass that is greater than its EOL mass as propellant
is depleted during its operational life.
See also Planned obsolescence
References