A product'sservice life is its period of use in service. Several related terms describe more precisely a product's life, from the point of manufacture, storage, and distribution, and eventual use.Service life has been defined as "aproduct's total life in use from the point of sale to the point of discard" and distinguished fromreplacement life, "the period after which the initial purchaser returns to the shop for a replacement".[3] Determining a product's expected service life as part of business policy (product life cycle management) involves using tools and calculations frommaintainability andreliability analysis. Service life represents a commitment made by the item's manufacturer and is usually specified as a median. It is the time that any manufactured item can be expected to be "serviceable" orsupported by itsmanufacturer.[citation needed]
Service life is not to be confused withshelf life, which deals with storage time, or with technical life, which is the maximum period during which it can physically function.[3] Service life also differs frompredicted life, in terms ofmean time before failure (MTBF) ormaintenance-free operating period (MFOP). Predicted life is useful such that a manufacturer may estimate, by hypothetical modeling and calculation, a general rule for which it will honorwarranty 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, amissile system can have a mission time of less than one minute, service life of 20 years, active MTBF of 20 minutes, dormant MTBF of 50 years, and reliability of 99.9999%.
Consumers will have different expectations about service life andlongevity[4][5] based upon factors such as use, cost, and quality.
Manufacturers will commit to very conservative service life, usually 2 to 5 years for most commercial and consumer products (for examplecomputerperipherals andcomponents). However, for large and expensivedurable goods, the items are notconsumable, 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 without maintenance (or 15,000 hours with maintenance), reliability of .99999, and a service life of 40 years.
The most common model for item lifetime is thebathtub curve, a plot of the varyingfailure rate as a function of time. During early life, the bathtub shows increased failures, usually witnessed duringproduct development. The middle portion of the bathtub, or 'useful life', is a slightly inclined, nearlyconstant failure rate period where the consumer enjoys the benefit conferred by the product. As time increases further, the curve reaches a period of increasing failures, modeling the product's wear-out 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 thetread and the casing.
For maintainable items, those wear-out items that are determined by logistical analysis to be provisioned forsparing and replacement will assure a longer service life than manufactured items without such planning. A simple example is automotivetires - failure to plan for this wear out item would limitautomotive service life to the extent of a single set of tires.
An individual tire's life follows thebathtub 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 events such as encountering a road hazard (a nail or apothole), for a long duration relative to its expected service life which is a function of several variables (design, material, process). 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 aretread on the tire thereby extending the service life. It is not uncommon for an 80,000-mile tire to perform well beyond that limit.[6]
It may be difficult to obtain reliable longevity data about manyconsumer products as, in general, efforts atactuarial analysis are not taken to the same extent as found with that needed to supportinsurance 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[7] which gathers data from the Appliance Statistical Review and various institutes involved with the homebuilding trade.
SomeEngine manufacturers, such as for example Navistar and Volvo, use a so-called B-life rating,[8]based on the durability data of the engine manufacturer,[9] B10 and B50 index for measuring the life expectancy of anengine.[10]
When exposed to high temperatures, thelithium-ion batteries in smartphones are easily damaged and can fail faster than expected, in addition to letting the device run out of battery too often. Debris and other contaminants that enter through small cracks in the phone can also infringe on smartphone life expectancy. One of the most common factors that cause smartphones and other electronic devices to die quickly is physical impact and breakage, which can severely damage the internal pieces.[11]
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 (BOL) andend of operational life (EOL). Batteries and other components that degrade over time may affect the operation of a product. The performance ofmission critical components is therefore calculated for EOL, with the components exceeding theirspecification at BOL. For example, withspaceflight hardware, which must survive in the harsh environment of space, the capacity to generate electricity fromsolar panels orradioisotope thermoelectric generator (RTG) 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.
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