on Product Reliability

The original windmills of Europe are feats of engineering.  I was able to get inside of a few in Holland and see all the mechanisms that have been operating for hundreds of years.  I was lucky that the wind was strong and the windmills had their sails out the days I was visiting.  A few were grinding flax seed and others designed to pump water from a low basin to a high basin to control basin water levels. Being inside of the windmill was like being an insect inside of a grandfather clock.  It was so interesting seeing how they engineered the mechanisms to optimize the balance of the system needs in such a different manner than we do with many of our currently engineered products. [Read more…]

Many product programs ( actually all) are on a tight schedule.  When Accelerated Life Testing (ALT) get’s it’s place in the process it is another mouth to feed.  ALT is not a short process.  Each round of testing typically takes weeks, and the results may drive design changes that prescribe additional testing.  It is common to want to get the ALT process going as quickly as possible.  In this haste the primary wear-out failure modes and it’s driving stresses are confidently stated, a model is created, and the test is started.

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Mean Time Between Failure (MTBF) is one of the most well know reliability metrics.  

But to anyone who works with reliability, it seems like it was developed by some evil anti-reliability mastermind to undermine the possibility of connecting reliability to anything or anyone.

Mean Time Between Failure means what?

• It’s the time between two failures? –
• It’s when the first failure occurs? –
• It’s how long the product is good for?
• It seems way to big to be a reasonable goal! “How can an air pump have an MTBF of 4 million hours?  That’s ridiculous these things are only supposed to last for five years!

This is the process of understanding everyone goes through as they are introduced to MTBF, formally or informally. [Read more…]

You have been put in charge of a program to study failure rates of brake pads.  The place to start is a testing program that will generate data for analysis.

Testing programs should begin with a specific intent.  This may be to characterize quality based failures, use life, or wear-out failure modes. When a test is complete it is easy to take all observed failures and use them in the data set to characterize the failure mode. This is a mistake.

Each of the study intents I described above can be attributed to wanting to understand a specific section of the life curve that is commonly represented by the “bathtub” curve. [Read more…]

Design of Experiments (DOE) is a phenomenal way to identify key relationships between variables and effects.  It fully leverages statistics to not only identify these relationships in a compressed time frame but any “interactions” between variables that cause a specific effect.  These interactions would not have been observed if experimentation was limited to adjusted one factor at a time (OFAT).

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Engineers have been applying Prognostics to mechanical components for many years.

For example:

• Motors, increase in current or noise
• Mechanical pumps, progressive increase in vibration
• Thermal systems, time to achieve a set temperature
• Fluid systems, change in pressure

However, most industries building systems with mechanical components choose not to use prognostics because of the cost of the instrumentation within the product. Products that have on board “smarts” can choose to include diagnostics with less effort or expense. With advances in technology, the cost of the instrumentation is dropping. This not only means that adding the hardware to support advanced metrology is more feasible but that many of these components/systems may have already been added for other functionality and controls improvements in the product. It doesn’t take much brainstorming to find creative ways to use these existing sensory systems. [Read more…]