Robot Reliability Claims Explained: MTBF, MTTR, Availability, and Failure Definitions

A supplier says their robot has an MTBF of 80,000 hours. That sounds impressive. But what does it actually mean for your operation? Can you plan around it? Should you trust it?

The short answer: not without asking more questions. MTBF, MTTR, and availability are useful metrics, but they are statistical estimates, not guarantees. And they are only as meaningful as the definitions, sample sizes, and conditions behind them. This article explains what these terms mean, where they come from, and how to evaluate supplier reliability claims without getting lost in the numbers.

The Standard Behind the Terms

IEC 60050-192, International Electrotechnical Vocabulary: Dependability, provides terminology for reliability, availability, and maintainability. Procurement documents should identify the edition and exact definitions used, because abbreviations in commercial proposals may be used differently.

Related IEC standards provide the broader framework. IEC 60300 series covers dependability management guidelines. IEC 60812 covers FMEA methodology. But for understanding what a supplier means when they say “MTBF” or “availability,” IEC 60050-192 is the terminology reference point.

MTBF: The Most Misunderstood Metric

What It Is

MTBF (Mean Time Between Failures) represents the average time between consecutive failures in a repairable system. Per IEC 60050-192 (International Electrotechnical Vocabulary, Part 192: Dependability), MTBF applies only to repairable systems. It is the mean accumulated operating time between consecutive failures of a repairable item, an operating-time measure that does not include restoration time. Mean time to restoration is a separate maintainability measure. When comparing supplier MTBF values, require the exact failure definition, operating-time basis, test or field source, and exclusions.

What It Is Not

MTBF is a statistical expectation, not a guarantee. It does not tell you when a specific robot will fail. It does not promise that the robot will run for 80,000 hours without breaking. It tells you that, across a population of robots under certain conditions, the average interval between failures is 80,000 hours.

A larger MTBF is meaningful only when the compared estimates use compatible failure definitions, operating conditions, and statistical models. It is not a minimum service life or a promise about an individual unit.

Why Small Samples Mislead

The NIST reliability handbook explains MTBF estimates and confidence bounds for a constant-rate model using accumulated test time and failure counts. A point estimate alone hides uncertainty. Even a test with no failures supports a confidence bound under the model assumptions, rather than proof of infinite reliability.

For a small fleet or short observation period, request total exposure, the observed failure count, confidence limits, and evidence that the assumed model fits the data. Different loads, environments, and duty cycles can make otherwise precise estimates irrelevant to your application.

MTTR: Recovery Time Depends on What You Count

MTTR can mean mean time to repair or mean time to restoration in different sources. Do not rely on the acronym alone. Specify the start and end events and whether the reported duration includes active work, fault diagnosis, logistics, and return-to-service checks. Possible reporting boundaries include:

• The time to physically repair the robot
• The time including waiting for spare parts
• The time including waiting for remote support to respond
• The time until the business process is fully restored

A supplier quoting a 2-hour MTTR may mean the hands-on repair time only. If you also need to wait for parts shipping and remote support, your actual downtime could be much longer. Always clarify what is included in the MTTR definition. For contracted service response commitments, see robot service-level agreements.

Availability: The Formula Is Simple, the Boundaries Are Not

For a simple repairable two-state model, inherent availability is commonly expressed as MTBF / (MTBF + MTTR), with MTBF measured as operating time and MTTR defined here as active corrective maintenance time. This calculation excludes logistics and administrative delays. Do not substitute a broader end-to-end restoration metric without changing the stated availability model.

The complication is the measurement boundary. Equipment availability and process output are not identical: an available robot may be idle because material is missing. Operational availability needs an agreed required-service period and a definition of counted downtime, including how support, network, infrastructure, and maintenance delays are treated. For post-deployment performance tracking, see robot fleet KPIs.

Two suppliers quoting “99% availability” may be measuring different things. One may exclude planned maintenance, network failures, and human errors. The other may include them. Without knowing the exclusion list, the numbers are not comparable.

How OEMs Handle Reliability Data

ABB Robotics

ABB describes condition-based maintenance using operational data and robot-specific recommendations. Monitoring capability should be evaluated separately from any numerical reliability claim: request evidence for the exact model and use case.

FANUC

FANUC ZDT monitors robot health and supports maintenance alerts. The availability of monitoring does not by itself establish a fleet MTBF or guaranteed recovery time. Confirm compatibility and the response process for your installation.

Third-Party Certification Example

If a supplier presents a third-party MTBF certificate, request the underlying report, tested configuration, test duration, failure criteria, statistical model, and confidence level. Determine whether the result comes from testing, calculation, or field observations. A certificate supports only its stated scope and conditions; it is not a guarantee of performance in your facility.

What to Request From Your Supplier

A single MTBF number is not enough. Request the following information to make reliability claims comparable across suppliers:

Failure definition. What counts as a failure? Does a software reboot count? Is an operator error that triggers a safety stop included? Are planned maintenance events excluded? Without a clear failure definition, the MTBF number is ambiguous.

Statistical window. What time period does the data cover? When did data collection start and end? How many cumulative operating hours or task cycles are in the dataset?

Sample size. How many robots and how many sites contributed to the statistics? One robot in a lab for three months produces a very different confidence level than 500 robots across 20 sites for two years.

Exclusion list. What events were excluded from the failure count? Planned maintenance, network outages, facility infrastructure issues, and human interventions are commonly excluded, but the specific list varies.

Product version. What hardware revision and firmware version does the data cover? Different versions of the same model can have significantly different reliability profiles.

Operating conditions. What load, environment temperature, and shift patterns were in effect? These are key factors influencing failure rates.

Data source. Is the MTBF from design verification testing, field data, or accelerated life testing? Each source has different implications for how the number relates to your real-world operation.

Third-party certification. Was the reliability claim independently verified? If so, by whom, and what did the verification cover? For systematic incident and failure tracking, consider robot fleet incident management practices.

A Comparison Template

When evaluating multiple suppliers, use a consistent set of fields rather than comparing raw numbers:

The point is not to find the supplier with the highest MTBF. It is to find the supplier whose reliability data is transparent, well-documented, and applicable to your operating conditions.

Common Pitfalls

Treating MTBF as a guarantee. It is a statistical expectation, not a warranty. A robot with an 80,000-hour MTBF can still fail in week one.

Comparing MTBF numbers without checking definitions. Two suppliers quoting 60,000-hour MTBF may be counting different things. If one excludes software issues and the other does not, the numbers are not comparable.

Comparing MTBF without context. A higher number can reflect different failure definitions, operating conditions, or estimation methods. Compare the evidence and uncertainty before ranking suppliers.

Confusing test evidence with field experience. Testing and operational records provide different evidence. Check how closely either dataset represents the configuration and conditions you intend to use.

Ignoring MTTR. A robot with a high MTBF but a long MTTR may have worse operational availability than one with a lower MTBF but fast recovery. Availability depends on both.

What to Ask Your Supplier

• How do you define “failure” in your MTBF calculation?
• What sample size and observation window produced this MTBF figure?
• What events are excluded from the failure count?
• What hardware revision and firmware version does this data cover?
• Under what operating conditions was this data collected?
• Is this MTBF from design verification testing or field data?
• What does your MTTR include: repair time only, or also parts logistics and remote support?
• Do you distinguish between technical availability and operational availability?
• Has the reliability claim been independently verified? By whom?