The Difference Between Lifetime Expectancy and Mean Time Between Failure (MTBF)

Apr 25, 2025
Close-up of a rack-mounted server with multiple hard drive bays and status indicator LEDs
Failure analysis and lifetime expectancy calculations are essential when evaluating equipment service life and maintenance costs. Two ratings used for such evaluations — mean time between failure (MTBF) and lifetime expectancy — are sometimes confused, so let’s explore the difference in meaning.

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The Importance of Reliability Measures

Enterprise-level equipment deployment requires an understanding of purchase cost, maintenance cost, and the replacement timeline. These three factors are used to calculate the total cost of ownership (TCO). Further, the maintenance factors and lifetime expectancy may impact the overall quality of service. Mean time between failure (MTBF) and lifetime expectancy are two critical reliability measures used to predict service level and TCO. Both are targeted at different aspects of reliability.

What is Mean Time Between Failure?

Factors affecting MTBF
MTBF refers to the probability of a failure occurring in a piece of equipment. It is primarily useful with repairable equipment or swappable components. MTBF is used to estimate the statistical need for repair services.

You can calculate MTBF directly by counting failures and dividing the number of failures into the total operating time. However, MTBF is typically estimated by a statistical analysis of the components used in the product and their individual track records. MTBF is expressed in hours. For example, an MTBF of 100,000 hours indicates that, on average, you can expect a failure every 100,000 hours of equipment service. MTBF calculations assume a constant rate of failure during a product’s service life. However, actual failures are more common early in the product’s life and late, near the end of the product’s life.

MTBF is a more useful metric for large installations than for individual products. For example, an average personal computer (PC) power supply has an MTBF of 100,000 or more hours (11 or more years). It is rare for a PC to operate without being declared obsolete long before 11 years have passed. Therefore, a user does not need to plan for a power failure during his or her PC’s lifetime.

However, the example of a data center, with thousands of servers, tells a different story. Statistical averaging, along with MTBF, would show that some of those power supplies will fail before their useful life is up. The quantity of spare replacement supplies on hand will be based on the overall MTBF for the power supplies in the installation.

What is Lifetime Expectancy?

Factors affecting lifetime expectancy
A product’s lifetime expectancy is defined as the time between manufacture and discard. When deploying an individual piece of equipment or a large number of units, lifetime expectancy is used to estimate replacement cycles, upgrade periods, and the TCO.

In the data center example above, the server power supplies may have a projected life expectancy of 10 years. Many could last for much longer than 10 years. However, the likelihood of failure would start to increase to the point at which unplanned downtime would become intolerable. As a result of that scenario, data center management would plan to replace each server power supply at or near the 10-year mark.

Key Difference Between the Two

Fundamentally, lifetime expectancy is used to plan for scheduled upgrades and asset replacement, while the MTBF is used to plan for maintenance cycles and downtime mitigation. MTBF is reported as a constant rate throughout the product’s life. Lifetime expectancy is often visualized with a “bathtub curve,” as Figure 1 shows.

Typical bathtub curve depicting lifetime expectancy
Fig. 1: Typical bathtub curve depicting lifetime expectancy
Both figures are used for purchase decisions and TCO. Lifetime expectancy plays a greater role in asset management and long-term planning. MTBF factors into maintenance, quality of service, and lifecycle costing.

Repair vs. Replacement: Both Are Influential Factors

MTBF and lifetime expectancy can be useful tools when deploying commercial and industrial equipment, but the two differ in meaning and purpose. When planning for overall unit replacement or upgrade, rely on lifetime expectancy. When estimating repair costs or premature failure replacement costs, use MTBF. In the real world, both factors are crucial and the two, when taken together, are valuable tools for TCO analysis.
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