Expect to Pass Validation using Accelerated Tests

by | May 24, 2022 | Blog

Validation Testing (DV and PV) is a critical and expensive endeavor.  The part build process must align with the latest prototype (DV) or production (PV) processes and be fully documented for posterity.  Depending on the product and application, the validation test plan consists of a battery of tests, some of which are lengthy – often six months or more.  Because of this, DV and PV test plans are invariably on the critical path for a customer program.  Test failures that require fixing the design and repeating DV or PV jeopardize project timing and company profits.  Further, they jeopardize the customer program along with your company’s reputation.

For these reasons, the best policy is that you should not start validation unless you expect to pass.  And how can you expect to pass unless you’ve given your parts a chance to fail on test exposures that are similar to those that your product will see on test and in the field. This is often done during the design verification or design confirmation phase of a program.

These test exposures take different forms.  In each case we are less concerned with accurate and lengthy field-correlated tests than we are in quickly finding and fixing failure modes.  These techniques are listed here from shortest to longest and qualitative to quantitative methodologies.

  1. A HALT (Highly Accelerated Life Test) usually takes less than a week to run and is a purely qualitative activity using just a few parts/assemblies. The tests are run in specially designed HALT chambers and utilize both steady state and stepped profiles of temperature, vibration, humidity and electrical power.  Hit it with a sledge hammer (figuratively), fix the failure modes that arise, and continue on until you approach the limits of the technology.
  2. A Proportional Overstress Test is a semi-quantitative step-stress methodology run on 3 to 6 pcs that applies increasing levels of stress in succeeding steps until failures are observed. The selection of stress values for each environment (temp, vibe, volts, etc.) and the duration of each step are such that they are applied “proportionally” to field exposure, so that any particular environment is not over-represented on test.
  3. Alternatively, you might develop a highly accelerated version of an existing or legacy test that the team is familiar with using equivalent damage calculations. It has the advantage of running on existing test equipment, it is designed to exercise the failure mode(s) that keeps the project team up at night, and is still quite short, e.g., a 3-month PTC test reduced to 9 days.  Though somewhat quantitative, the correlation to life in the field is usually not firmly grounded due to excessive acceleration.
  4. An ALT (Accelerated Life Test) is a quantitative methodology for estimating reliability (R/C) at customer use-level conditions by running tests to failure in the lab at multiple elevated stress levels. At each stress level four to eight parts are run to failure or suspension. A life/stress model (e.g., Arrhenius or Power Law) is then used with the corresponding life distributions to project the distribution of times-to-failure at customer use conditions.

With each approach, the cost to iterate (fix) the design is relatively low since the test was short and it’s early in the program.  Hard tools are not yet cut and significant capital investments have not been made.  And since you have given your parts a chance to fail early in the development cycle and your design has improved as a result, you have some basis for expecting to be successful in validation.

As you move along into validation and consider DV and PV test plans, the more apt question at that point is: Am I giving the right parts a chance to fail on the right tests?  In short this means that in validation we wish to test representative parts on tests that have been rigorously correlated to field use conditions.  Otherwise, you risk making ill-informed design and program decisions and inaccurate assessments of product reliability.

I will cover this in my next article.