You run numbers, and the results are solid. Your product prototype has cleared all the reliability tests with flying colors. Yet, six months after rollout, the field failures start stacking up. Support is overwhelmed. Customers are frustrated. And your so-called MTBF number? Completely off the mark.
It’s not just frustrating, as it’s expensive. It also means something fundamental got missed early on.
If this sounds familiar, you’re not alone. Many reliability engineers and operations managers rely on Mean Time Between Failures (MTBF) to estimate the duration of system or component operation before a failure occurs. But here’s the problem: the MTBF calculation most teams use is built in a bubble. It’s neat, it’s clean, but it doesn’t account for how ugly the real world can get.
Let’s break down nine factors that quietly sabotage your MTBF assumptions and what you can start doing about them.
1. Heat Is Quietly Wrecking Your Numbers
Most test environments are clean, cool, and tightly controlled. However, your product is unlikely to be used in such an environment. It might sit in a poorly ventilated panel. It might be installed outdoors in a box that turns into an oven. That might even be sitting next to a motor radiating constant heat.
Heat is one of the fastest accelerators of electronic failure. It weakens solder joints, warps boards, dries out electrolytic capacitors, and reduces the lifespan of everything from sensors to wiring insulation. If your MTBF calculation assumes room temperature or a fixed 25°C condition, you’re not calculating failure—you’re doing wishful thinking.
Thermal testing should never be a checkbox. It’s a mirror. It shows you what your product actually goes through when people start using it.
2. Vibration and Shock Are Invisible in Spreadsheets
Some products just sit there. Others live in moving trucks, forklifts, aircraft, oil rigs, or production lines with constant shaking. The difference between the two environments is massive, and yet both may get the same lab treatment.
Vibration testing is often skipped early in design due to cost or time. However, if your product vibrates for 10 hours a day, stress builds up quickly. Screws loosen. PCB traces crack. Connectors degrade. These issues rarely appear in traditional MTBF testing.
The lesson here? Don’t trust spreadsheets to account for physical forces. Build in mechanical abuse testing that mirrors real deployment. If vibration is in play, you need to model it, not ignore it.
3. Power Cycling Is Killing Components Slowly
Products don’t just run forever once they’re powered on. They restart. Get unplugged. Switched off. Put it into sleep mode and back. Every power cycle creates stress not just on the power supply, but on MOSFETs, regulators, relays, storage devices, and firmware state machines.
This is where many MTBF calculation models deviate from the correct path. They test for steady-state performance, not transitional stress. The result? A unit that looks great in the lab, but starts failing in the field after just a few hundred real-world cycles. These kinds of failures rarely show up when you rely strictly on the classic MTBF formula, which assumes steady-state operation and doesn’t factor in real-world transitions like start-stop cycles or load surges.
Make sure your reliability tests account for power cycling. And when possible, design for soft-start, debounce, and graceful shutdown, even if it adds complexity. It pays for itself in reduced returns and longer life.
4. You’re Using Average Numbers That Don’t Tell the Full Story
Statistical averages are comforting. But they’re not trustworthy by themselves.
If your failure distribution has a long tail or early infant mortality, the mean tells you almost nothing about what most customers will experience. In some cases, the “average” lifetime may even conceal the fact that 30% of units are failing prematurely.
To build a smarter MTBF model, go beyond averages. Use Weibull analysis or other life distribution methods to understand variance and its implications. Pay attention to the outliers, because in the real world, they’re often the ones that generate the support tickets.
If you’re just starting to work with reliability metrics, a solid beginner’s guide on MTBF modeling can help you avoid these early pitfalls and see why relying on averages alone can lead you down the wrong path.
5. Environmental Contaminants Are Destroying Your Assumptions
Your electronics might look sealed, but are they truly protected?
Dust, moisture, pollen, animal hair, salt fog, and industrial chemicals often creep into areas that weren’t considered during initial test runs. These things corrode contacts, cause bridging shorts, or interfere with cooling. And yet, most initial reliability tests are conducted in clean, filtered, lab-grade environments.
If you’re not modeling the environments your product will operate in, such as factories, farms, garages, or outdoor enclosures, your MTBF calculation is missing a major risk factor. Even low-cost conformal coatings, mesh filters, or better IP-rated enclosures can improve outcomes drastically.
6. Poor Installation and Handling Practices
You can design the world’s most rugged component, but if a technician drops it during install or over-tightens the fasteners, that durability goes out the window.
Here’s the truth: humans make mistakes. Connectors get forced the wrong way. Mounting brackets are skipped. Static discharge happens without grounding. And while these aren’t technical design flaws, they do contribute to real-world failure rates.
Your MTBF model might not have a field for “bad install,” but your support logs probably do. Ensure that you factor in human behavior, particularly when your product relies on field installation or third-party handling. Consider how training, clearer manuals, or protective packaging could cut failure rates before they begin.
7. Unrealistic Test Conditions (AKA “Happy Path” Testing)
Many test plans are built around what’s supposed to happen. However, customers don’t always behave as we hope. They overload circuits, stack devices in unventilated spaces, skip firmware updates, and sometimes misuse your product in ways no test plan ever imagined.
If your MTBF model assumes perfect use, it’s simply not accurate. It’s marketing.
You’ll get much better results by deliberately building “abuse cases” into your test plan. What happens if someone leaves it outside overnight? Or forgets to clean the air filters for six months? Or runs it 24/7 instead of the recommended 8 hours? These aren’t edge cases. They’re reality. And your MTBF calculation needs to reflect that.
8. Supply Chain Substitutions Fly Under the Radar
Procurement makes a small change. “This capacitor has the same specs.” No one updates the BOM. The lab doesn’t retest. You keep shipping.
Three months later, failure rates spike and no one knows why.
Swapping vendors, materials, or even die revisions within chips can significantly impact long-term reliability. Even if the part numbers match, the performance might not. That’s where understanding the failure rate role of each component becomes critical; small changes in materials or internal specs can shift how and when things break, often without any visible clue until it’s too late. If the change isn’t run through reliability testing again, your MTBF model becomes obsolete the second that change goes live.
Create a policy where every material substitution, no matter how minor, triggers a review of its potential impact on MTBF. It may seem bureaucratic, but it’s far less expensive than warranty returns or dealing with angry customers.
9. MTBF ≠ Warranty Stop Treating It Like It Does.
This one causes endless confusion.
If a device has a calculated MTBF of 100,000 hours, it doesn’t mean it will last 11 years. It means, statistically, across a large group of units, failures will occur on average every 100,000 hours. That doesn’t tell you when the first failure will happen, or even how steep the failure curve is over time.
Plenty of devices with high MTBF ratings fail within the first six months due to weak early-life design, process flaws, or bad luck. That’s why MTBF calculation should never be used as a substitute for solid warranty modeling. They’re connected—but not interchangeable.
Always pair MTBF results with burn-in data, service histories, and accelerated stress testing. It’s the only way to get the full picture.
What Can You Do Differently?
The takeaway isn’t to throw MTBF out—it’s to treat it with care. If you want your MTBF numbers to mean something, you have to:
- Involve real-world users, installers, and support staff in the discussion about reliability.
- Update your models as new field data becomes available.
- Treat every version change, part substitution, and design tweak as a reason to re-test.
- Simulate failure, not just ideal operation.
- Stop pretending that averages reflect reality.
Because they don’t. People don’t use things the way we want. They use them as needed, and your models should start there.
There’s no perfect way to calculate MTBF. But there is a responsible way: ground it in reality, not assumptions. The companies that do this don’t just ship products—they build trust. They reduce returns. They sleep better.
If your MTBF calculation has let you down before, that’s not a failure. It’s feedback. Take it seriously. Fix the blind spots. And your next estimate won’t just look good on paper—it’ll hold up in the field.
