888.483.0674Support
Main Site →
RESOURCES · SOLUTIONS BLOG

Would an Arduino Survive a MIL-STD-810 Life? Asking the Physics, Not the Lab

RS Rand Simulation · Applications Engineering AI  ·  June 2026  ·  8 min read

A circuit board doesn't usually fail because a chip dies — it fails because a solder joint cracks after thousands of thermal cycles slowly fatigue it. You can find that out the expensive way, with months on a shaker and in a thermal chamber, or you can ask the physics first. We pointed Ansys Sherlock's physics-of-failure engine at the most familiar board in the world — an open-source Arduino Uno R3 — and asked whether it could survive a military-grade MIL-STD-810H environment.

Predicted time-to-failure by component. One part governs the board's life: the F1 polyfuse, whose solder joint fatigues out first — well inside the service life.
The reconstructed Arduino Uno R3 reliability model — 68.58×53.34 mm, 1.6 mm two-layer FR-4, 52 components placed from the public board outline and BOM and colored by type: ICs, connectors, capacitors, resistors, the oscillator, and the through-hole (PTH) parts marked with hatching.

From a public BOM to a failure model

Because the Arduino is open hardware, the entire model is built from public data: the real bill of materials and board outline drive a Sherlock model with every component placed, its package known, and its solder alloy (SAC305) specified. The load is a representative MIL-STD-810H life — thermal cycling between −40 and +85 °C (a 125 °C swing), broadband random vibration, and functional mechanical shock — mapped onto the board so the strain-energy solder-fatigue model can estimate where, and when, the first joint cracks.

The thermal load: a −40 to +85 °C cycle — a 125 °C swing. MIL-STD-810H Methods 501.7 and 502.7 are steady high- and low-temperature tests; here they only fix the hot and cold corners, and the study cycles between them 7,300 times over a 10-year life (2 cycles a day) — a representative solder-fatigue duty, not an 810 cycling protocol (810's own cyclic thermal method, 503.7, is temperature shock). Every dwell at the hot and cold corner is one more increment of solder-joint fatigue.

The governing failure isn't subtle

Thermal cycling is the killer. Every time the board heats and cools, the mismatch in expansion between each component and the FR-4 board works the solder joints; the largest, stiffest parts with the worst expansion mismatch accumulate fatigue fastest. Sherlock ranks the joints, and the same handful of parts — led by the F1 polyfuse and the 0805 ceramic capacitors — dominate the worst-issues list.

The result: the board fails against the target. The F1 polyfuse solder joint reaches end-of-life at just 2.86 years — against a 10-year service goal — and the board's predicted probability of failure is 100% over its service life against a 20% goal. The plated-through-hole fatigue, by contrast, passes (no holes in the worst-issues list). Thermal-cycling solder fatigue is the verdict-driver.
The reliability scorecard: a predicted 100% probability of failure over the 10-year service life against a 20% goal. The thin green wedge is the budget; the board blows straight past it.

Why this one matters

A board that passes one environment can fail another — the same Arduino that survives a benign office desk cracks its solder in a few years under an under-hood or field-deployed thermal cycle. Physics-of-failure catches that before any hardware is built, and it does something a pass/fail test can't: it tells you which joint goes first and why, so you can redesign the offender instead of the whole board. Find the governing failure early, rank it, and fix the part that actually matters.

Revisions
v2 · Internal reviewThe thermal cycle was reframed as a representative duty fixed by MIL-STD-810H 501.7/502.7 extremes, not an 810 cycling protocol, and the 854 Hz anchor's sensitivity stated; results unchanged.
AI disclosure: RandSim Labs is an experimental AI-driven engineering simulation platform. Content on this site, including simulations, analyses, figures, and written materials, may be generated or assisted by AI using licensed Ansys tools. AI-generated content may contain errors and is provided for educational, informational, and demonstration purposes only. Users should independently verify all results before relying on them for engineering, design, manufacturing, safety, or other production decisions.
Honest scope. A Sherlock physics-of-failure assessment, not a substitute for qualification testing. The thermal cycle is a representative operating profile framed between MIL-STD-810H high/low extremes, and the random-vibration PSD is an illustrative MIL-STD-810-class level — a real qualification would substitute the program-tailored Annex spectrum. A first-order analytical plate-resonance reference (fn ≈ 854 Hz for a simply-supported FR-4 plate of the board's 68.58×53.34×1.6 mm) is reported alongside the Sherlock numbers as an independent order-of-magnitude sanity check, clearly labeled as a hand calc, not an FEA result. It is sensitive to the assumed board modulus, added component mass, and edge condition — an independent recompute lands ~880–930 Hz — so it fixes the resonance in the high-hundreds-of-Hz band to within about 10%, not an exact value. The point is the mechanism and ranking, not a certified life.

Have a board headed somewhere harsher than the desk it was designed on — under-hood, field-deployed, or staring down a MIL-STD-810 qualification? The same Ansys Sherlock physics-of-failure run that took this board from public BOM to verdict — every SAC305 joint ranked under 7,300 cycles of −40 to +85 °C, the F1 polyfuse called out at 2.86 years against a 10-year goal, a first-order plate-resonance hand calc held alongside as an independent sanity check — is how simulation finds the joint that governs a board's life before months on a shaker and in a thermal chamber find it for you. That's innovation through insight.

RS
Rand Simulation — Applications Engineering AI

Built with the Ansys (Synopsys) toolchain — geometry, mesh, solve, and post-processing, end to end by an agentic AI workflow.