Consider as an example solar photovoltaic (PV) cells. Ideally, they should operate for 25 years without failure. The product development time is less than a year for a new panel. You want to estimate the reliability of the cells over the 25-year duration. A simplistic way to determine the reliability is to set up and operate solar systems for 25 years and track the number of failures over time. However, this is not practical or useful.

Another method is to only test units as above for one year, then use the available information to make a decision. Although product failures may occur (most likely as the result of manufacturing and installation errors), delimitation of coatings or sealants, solder joint fatigue, PV cell degradation, and other longer term failure mechanisms will likely not manifest themselves. You could make an estimate, but it would not be very accurate beyond the one year of use replicated in the testing.

For our solar cell example, if UV radiation degrades one of the coatings, you can ‘accelerate’ this by exposing the cells and coatings to UV radiation more often per day then in normal use. If in normal use the panel would have 10 hours of direct daylight per 24-hour day, then by using UV lamps you could expose the units 24 hours per day, for a 2.4x acceleration. Thus, instead of 25 years, the testing would require a little more than 10 years. However, this is still not good enough.

An exploration of the UV damage mechanism reveals that it may be part of a chemical reaction that clouds the coating. This chemical reaction most likely can be accelerated with temperature. With a little work you find that the expected coating temperature during use is 40°C or less 90% of the time. By increasing the temperature (and being careful not to melt the coating) you may find another acceleration factor of 10. The specifics of the acceleration are related to the activation energy of the specific chemical reaction, the testing temperature, and the use temperature.

Therefore, with a little understanding of the use conditions (10 hours of daylight per day) and the specific failure mechanism in question (UV- and temperature-driven chemical reaction) you can achieve a 24x acceleration factor. It will still take a little more than a year to fully test out to 25 years, yet you may be able to use the data out to 24 years as a rough estimate and update the data when the final results become available.

This is just a simple example. There is a lot more to ALT design, yet the most important aspect by far is understanding the failure mechanism.

HALT
In addition to ALT, another common testing method is highly accelerated life testing (HALT). Upon first inspection, one might assume that HALT is simply a faster version of ALT. However, this extrapolation is not true in most cases.

ALT is characterized by testing the unit above expected stress levels or more often and above specification levels to create the failure mechanisms that would have occurred eventually at nominal stress levels. This is generally done by using one stress parameter, yet it could entail the use of multiple stresses. In contrast, HALT could be called a discovery evaluation. The testing is also above specification limits and may include multiple stresses at the same time. The intent is to continue to step up the stress to cause failures—in other words, to discover the difference between the specification limits and performance limits (or destruct limits, at which point the units fails such that it does not recover).

ALT VS. HALT
ALT answers the question of when the unit fails. HALT addresses what will fail or how much margin exists within the design.

ALT can be as simple as increasing the occurrence of some function, say opening and closing a car door. If one expected (or observed or measured with existing cars) that the driver’s door will undergo four open/close cycles per day on average, then simply opening and closing the door more often per day would be a simple way to accelerate failure mechanisms related to the open/close cycle.

There are many models that relate the effect of the stress applied to the failure rate or expected life distribution. For example, the Arrhenius model relates temperature to the rate of a chemical reaction, say corrosion. The activation energy value is specific to the specific failure mechanism and should be chosen with care.

Using a model permits the design of an ALT test that uses only one stress condition and relies on the model to translate the testing results to use conditions. Other ALT approaches include step stress and degradation. In most cases, careful design of the ALT includes understanding the failure mechanisms and statistics.

HALT is the exploration of the stress on the product’s performance with the intent to quickly identify the weakest elements of the design. The use of multiple stresses and relatively rapid step increases in one or more of the stresses makes modeling the effects very difficult if not impossible to model.

HALT is good at finding weaknesses in a design or the assembly process. HALT reveals areas with insufficient margin and that are more likely to fail given normal material and use variations. HALT is also typically done with only a few units for testing (often four or fewer).

HALT is also relatively quickly accomplished relative to ALT. HALT may take a day to a week to accomplish, depending on the size and complexity of the product, whereas ALT may take a day to months to accomplish, mostly depending on the ability to accelerate the failure mechanism in a meaningful manner.

ALT and HALT are two types of tools available to reliability professionals. The testing methods are quite different and serve in different ways. A useful way to keep the two definitions separate is to think of HALT as precipitating failures and ALT as predicting failures.

Bio:

Fred Schenkelberg is an experienced reliability engineering and management consultant with his firm FMS Reliability. His passion is working with teams to create cost-effective reliability programs that solve problems, create durable and reliable products, increase customer satisfaction, and reduce warranty costs. If you enjoyed this articles consider subscribing to the ongoing series Musings on Reliability and Maintenance Topics.