Abstract
In this episode of the Podcast, Fred Schenkelberg and Philip Sage explore the importance of aligning test methods with real-world reliability problems rather than defaulting to familiar tools or pre-existing equipment. Through anecdotes from industry experience—including discussions on environmental chambers, vendor testing standards, and engineering challenges in fields like automotive, petrochemical, and aerospace—they highlight the pitfalls of conducting tests that fail to answer the key questions about product reliability. The hosts emphasize the necessity of defining the problem, selecting meaningful test conditions, and ensuring that test outcomes inform critical design or business decisions. Their conversation underlines a central message: possessing a tool or capability does not justify its use unless it serves the reliability objectives at hand, encapsulated by the recurring theme of conducting “the right test at the right time.”
Philip and Fred discuss Testing and over testing.
Key Points
Join Philip and Fred as they discuss:
- Don’t let access to tools dictate your test strategy; start by defining the real engineering question
- Ask, “Who needs the results to make a decision?” before launching expensive or routine tests ([22:46](/timestamps/1366))
- Tailor your experiments to your environment, product, and actual failure risks—not just to pass standards
- Leverage every testing misstep as a learning opportunity
### Join the Conversation
Have your own tales of “just throw it in the chamber”? Questions about building smarter testing strategies? We love to feature listener stories and questions! Reach us via [ACendoReliability.com](https://accendoreliability.com), LinkedIn, or the audio submission tool on our show page.
Listen to the episode, and let us know what YOU think the “right test at the right time” looks like in your world.
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.
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