Hobbs – Reliability Prediction Based on Multiple Accelerated Life Tests

When:
August 21, 2019 @ 8:30 am – 10:30 am
2019-08-21T08:30:00-07:00
2019-08-21T10:30:00-07:00
Where:
webinar

https://register.gotowebinar.com/register/7591928075232539649

By Professor Joseph Bernstein

$200

To this day, the users of our most sophisticated electronic systems that include opto-electronic, photonic, MEMS device, etc. are expected to rely on a simple reliability value (FIT) published by the supplier. The FIT is determined today in the product qualification process by use of HTOL or other standardized test, depending on the product. The manufacturer reports a zero-failure result from the given conditions of the single-point test and uses a single-mechanism model to fit an expected MTTF at the operator’s use conditions.

The zero-failure qualification is well known as a very expensive exercise that provides nearly no useful information. As a result, designers often rely on HALT testing and on handbooks such as Fides, Telecordia or Mil Handbook 217 to estimate the failure rate of their products, knowing full well that these approaches act as guidelines rather than as a reliable prediction tool. Furthermore, with zero failure required for the “pass” criterion as well as the poor correlation of expensive HTOL data to test and field failures, there is no communication for the designers to utilize this knowledge in order to build in reliability or to trade it off with performance. Prediction is not really the goal of these tests; however, current practice is to assign an expected failure rate, FIT, based only on this test even if the presumed acceleration factor is not correct.

We present, in this tutorial, a simple way to predictive reliability assessment using the common language of Failure In Time or Failure unIT (FIT). We will evaluate the goal of finding MTBF and evaluate the wisdom of various approaches to reliability prediction. Our goal is to predict reliability based on the system environment including space, military and commercial. It is our intent to show that the era of confidence in reliability prediction has arrived and that we can make reasonable reliability predictions from qualification testing at the system level.

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