Getting Comfortable with using Reliability Results

We want to engage a reliability engineer in an analysis for our product design. They can help us produce some great information from which we can make decisions. You might be feeling uncomfortable about our team making a design decision based on those results. You don’t quite understand how the reliability engineer came up with the answer. You want to know where that information comes from so you can gauge the level of project risk of our decision.

We peel-back the curtain on reliability engineering methods. We explore reliability engineering's roots and development, from the 1950's through today, to better understand the results of an analysis. Having a general understanding of reliability methods can help us get comfortable with using the results.

The key takeaways from today:  

Reliability engineers use failure data. There are many methods for them to do this, and the methods they use are dependent upon what product is being developed. There is no one reliability plan that applies to everything. 

To better understand the reliability prediction we’re studying, we can consider where we got the failure data and which failure mechanisms we’re considering. Early calculations will use failure data that is not specific to our product. When we start to evaluate an engineering design, failure data from using physics of failure and finite element analysis can help us consider different design choices for different failure mechanisms. When we have parts, the failure data from testing our product may focus on one failure mechanism; the models of different failure mechanisms may be combined, or the team can use a worst-case method. 

Finally, use your reliability engineering friends’ skills throughout the design development process, from early concept evaluations through product launch and field monitoring. They can help you make decisions for a robust design and avoid costly mistakes. Reliability predictions can evolve as the product design evolves and are a useful tool for decision-making.  

An interesting case study of Physics of Failure:

Chary, Geetha V., Ed Habtour, Gary S. Drake. “Improving the Reliability in the Next Generation of US Army Platforms through Physics of Failure Analysis.” Journal of Failure Analysis and Prevention, iss. 12, Dec. 2011, pp. 74-85. 

Just two standards-based methods that are still being maintained:

Telcordia SR-332 Originally developed for the Telecom industry, it has expanded to be used widely for other commercial and military applications. It uses a black box technique.

217Plus Handbook™ of 217Plus Reliability Prediction Models (The 217Plus Standard) Originally named PRISM, it was developed with the Reliability Analysis Center (RAC) and Reliability Information Analysis Center (RIAC). It is meant to replace the older MIL-HDBK-217 with more reliability data and models. It considers all phases of a product life cycle as a function of calendar hours.

A case for not using those standards-based methods for reliability prediction:

Jais, C. & Werner, B. & Das, D. Reliability Predictions – Continued Reliance on a Misleading Approach. Proceedings - Annual Reliability and Maintainability Symposium, 2013.

Other QDD podcasts that might interest you:

If this episode spoke to you, there are 3 other Quality during Design podcasts you may want to revisit. They get into more detail about some of today’s concepts. 

Episode 6: HALT! Watch out for that weakest link, describes highly accelerated life testing. 

Episode 31: 5 Aspects of Good Reliability Goals and Requirements, where we build up a reliability requirement based on 5 aspects. 

Episode 37: Results-Driven Decisions, Faster: Accelerated Stress Testing as a Reliability Life Test, where we describe more about reliability life testing and more specifically about accelerated stress testing. 

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