Phantom Test Results
Abstract
Dianna and Fred discuss phantom test results in reliability testing.
Key Points
Join Dianna and Fred as they discuss phantom test results and the challenges of reliability test methods.
Topics include:
- The importance of root cause analysis for test failures.
- How test rigs and measurement systems themselves can give false positive or false negative results.
- Why understanding customer use cases is critical for effective testing.
Hear stories about phantom test results, incorrect test criteria, and unexpected product failures driven by factors not captured in standard lab tests.
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Show Notes
In this episode of Speaking of Reliability, Fred and Dianna continue their discussion on test methods, sharing insights and challenges they’ve encountered.
They highlight issues that can arise beyond just determining sample size, such as problems with the test method itself:
- A failure to investigate why a unit failed in a binomial zero failure test, instead simply replacing it, violates the test’s purpose.
- The test rig or measurement system can be the source of false failure signals. We can address this through troubleshooting the test setup.
- Incorrectly setting test criteria, such as demanding unrealistic precision from components, can also lead to widespread false failures.
- Measurement error is identified as a factor that must be considered when designing and running tests, as it can cause perfectly good units to signal failure and vice versa, leading to chasing phantom test results.
A significant challenge they talk about is the difficulty of replicating the complex, simultaneous stresses that products can face in real-world environments. Real world scenarios are unlike controlled lab tests, which are often sequential.
Their stories illustrate how unexpected conditions were not captured in standard testing, demonstrating the critical importance of understanding actual customer use cases and environments.
They note that without understanding use cases, even seemingly good, accelerated tests can provide misleading life predictions: those phantom test results. Using tools like FMEA and understanding customer needs are essential. They help prioritize testing and ensure results are meaningful and useful for decision-makers.
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