A product's service 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 "a product's total life in use from the point of sale to the point of discard" and distinguished from replacement 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 from maintainability and reliability 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" or supported by its manufacturer.[ citation needed ]
Service life is not to be confused with shelf 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 from predicted life, in terms of mean time before failure (MTBF) or maintenance-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 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, 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 and longevity [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 example computer peripherals and components). 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 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 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 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 the tread and the casing.
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 events such as encountering a road hazard (a nail or a pothole), 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 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. [6]
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 [7] which gathers data from the Appliance Statistical Review and various institutes involved with the homebuilding trade.
Some Engine 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 an engine. [10]
When exposed to high temperatures, the lithium-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) and end of operational life (EOL). 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 (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.
In reliability engineering, the term availability has the following meanings:
Mean time between failures (MTBF) is the predicted elapsed time between inherent failures of a mechanical or electronic system during normal system operation. MTBF can be calculated as the arithmetic mean (average) time between failures of a system. The term is used for repairable systems while mean time to failure (MTTF) denotes the expected time to failure for a non-repairable system.
The technical meaning of maintenance involves functional checks, servicing, repairing or replacing of necessary devices, equipment, machinery, building infrastructure and supporting utilities in industrial, business, and residential installations. Over time, this has come to include multiple wordings that describe various cost-effective practices to keep equipment operational; these activities occur either before or after a failure.
In economics and industrial design, planned obsolescence is the concept of policies planning or designing a product with an artificially limited useful life or a purposely frail design, so that it becomes obsolete after a certain predetermined period of time upon which it decrementally functions or suddenly ceases to function, or might be perceived as unfashionable. The rationale behind this strategy is to generate long-term sales volume by reducing the time between repeat purchases. It is the deliberate shortening of the lifespan of a product to force people to purchase functional replacements.
Annualized failure rate (AFR) gives the estimated probability that a device or component will fail during a full year of use. It is a relation between the mean time between failure (MTBF) and the hours that a number of devices are run per year. AFR is estimated from a sample of like components—AFR and MTBF as given by vendors are population statistics that can not predict the behaviour of an individual unit.
An extended warranty, sometimes called a service agreement, a service contract, or a maintenance agreement, is a prolonged warranty offered to consumers in addition to the standard warranty on new items. The extended warranty may be offered by the warranty administrator, the retailer or the manufacturer. Extended warranties cost extra and for a percentage of the item's retail price. Some extended warranties that are purchased for multiple years state in writing that during the first year, the consumer must still deal with the manufacturer in the occurrence of malfunction. Thus, what is often promoted as a five-year extended guarantee, for example, is actually only a four-year guarantee.
The bathtub curve is a particular shape of a failure rate graph. This graph is used in reliability engineering and deterioration modeling. The 'bathtub' refers to the shape of a line that curves up at both ends, similar in shape to a bathtub. The bathtub curve has 3 regions:
Failure rate is the frequency with which an engineered system or component fails, expressed in failures per unit of time. It is usually denoted by the Greek letter λ (lambda) and is often used in reliability engineering.
Reliability engineering is a sub-discipline of systems engineering that emphasizes the ability of equipment to function without failure. Reliability is defined as the probability that a product, system, or service will perform its intended function adequately for a specified period of time, OR will operate in a defined environment without failure. Reliability is closely related to availability, which is typically described as the ability of a component or system to function at a specified moment or interval of time.
Integrated logistics support (ILS) is a technology in the system engineering to lower a product life cycle cost and decrease demand for logistics by the maintenance system optimization to ease the product support. Although originally developed for military purposes, it is also widely used in commercial customer service organisations.
Maintenance-free operating period (MFOP) is an alternative measure of performance to the mean time between failures (MTBF), defined as the time period during which a device will be able to perform each of its intended functions, requiring only a minimal degree of maintenance. It was originally proposed in 1996 by the United Kingdom's Ministry of Defence, with intended application to military aircraft.
A hard disk drive failure occurs when a hard disk drive malfunctions and the stored information cannot be accessed with a properly configured computer.
Car longevity is of interest to many car owners and includes several things: maximum service life in either mileage or time (duration), relationship of components to this lifespan, identification of factors that might afford control in extending the lifespan. Barring an accidental end to the lifespan, a car would have a life constrained by the earliest part to fail.
A spare part, spare, service part, repair part, or replacement part, is an interchangeable part that is kept in an inventory and used for the repair or refurbishment of defective equipment/units. Spare parts are an important feature of logistics engineering and supply chain management, often comprising dedicated spare parts management systems.
A prediction of reliability is an important element in the process of selecting equipment for use by telecommunications service providers and other buyers of electronic equipment, and it is essential during the design stage of engineering systems life cycle. Reliability is a measure of the frequency of equipment failures as a function of time. Reliability has a major impact on maintenance and repair costs and on the continuity of service.
Availability is the probability that a system will work as required when required during the period of a mission. The mission could be the 18-hour span of an aircraft flight. The mission period could also be the 3 to 15-month span of a military deployment. Availability includes non-operational periods associated with reliability, maintenance, and logistics.
Maintenance Philosophy is the mix of strategies that ensure an item works as expected when needed.
Health and usage monitoring systems (HUMS) is a generic term given to activities that utilize data collection and analysis techniques to help ensure availability, reliability and safety of vehicles. Activities similar to, or sometimes used interchangeably with, HUMS include condition-based maintenance (CBM) and operational data recording (ODR). This term HUMS is often used in reference to airborne craft and in particular rotor-craft – the term is cited as being introduced by the offshore oil industry after a commercial Chinook crashed in the North Sea, killing all but one passenger and one crew member in 1986.
Software reliability testing is a field of software-testing that relates to testing a software's ability to function, given environmental conditions, for a particular amount of time. Software reliability testing helps discover many problems in the software design and functionality.
Deterioration modeling is the process of modeling and predicting the physical conditions of equipment, structures, infrastructure or any other physical assets. The condition of infrastructure is represented either using a deterministic index or the probability of failure. Examples of such performance measures are pavement condition index for roads or bridge condition index for bridges. For probabilistic measures, which are the focus of reliability theory, probability of failure or reliability index are used. Deterioration models are instrumental to infrastructure asset management and are the basis for maintenance and rehabilitation decision-making. The condition of all physical infrastructure degrade over time. A deterioration model can help decision-makers to understand how fast the condition drops or violates a certain threshold.