No Evidence of Correlation: Field failures and Traditional Reliability Engineering

Historically, Reliability Engineering of Electronics has been dominated by the belief that 1) The life or percentage of complex hardware failures that occur over time can be estimated, predicted, or modeled, and 2) the Reliability of electronic systems can be calculated or estimated through statistical and probabilistic methods to improve hardware reliability.  The amazing thing about this is that during the many decades that reliability

engineers have been taught this and believe that this is true, there is little if any empirical field data from the vast majority of verified failures that shows any correlation with calculated predictions of failure rates.

Probabilistic statistical predictions based on broad assumptions of the underlying physical causes began with the first electronics reliability prediction guide in November 1956, the RCA release TR-1100, “Reliability Stress Analysis for Electronic Equipment,” which presented models for computing rates of component failures. This publication was followed by the “RADC Reliability Notebook” in October 1959 and the publication of a military reliability prediction handbook format known as MIL-HDBK-217.

It continues today with various software applications, which are progenies of the MIL-HDBK-217. Underlying these “reliability prediction assessment” methods and calculations is the assumption that the main driver of unreliability is due to components with intrinsic failure rates moderated by the absolute temperature. It has been assumed that the component failure rates follow the Arrhenius equation and that component failure rates approximately double for every 10 °C.

MIL-HDBK-217 was removed from the military as a reference document in 1996 and has not been updated; it is still being referenced unofficially by military contractors and is still believed to have some validity even without any supporting evidence. [Note: as of the winter of 2024, I heard that Mil Hdbk 217 had been reactivated as a military standard – not updated, just pulled out of retirement.]

Much of the slow change in the industry is because electronics reliability engineering has a fundamental “knowledge distribution” problem in that actual field failure data, and the root causes of those failures can never be shared with the larger reliability engineering community. Reliability data is some of the most confidential and sensitive data a manufacturer has, and short of a court order, it will never be published. Without this actual data and information being disseminated and shared, one can expect little change in the beliefs of the vast majority of the electronics reliability engineering community.

Even though the probabilistic prediction approach to reliability has been practiced and applied for decades, any engineer who has seen the root causes of verified field failures will observe that most all failures that occur before the electronic system is technologically obsolete are caused by 1) errors in manufacturing 2) overlooked design margins 3) or accidental overstress or abuse by the customer.  The timing of the root causes of these failures, which are often driven by multiple events or stresses, is random and inconsistent. Therefore, there is no basis for applying statistical or probabilistic predictive methods. Most users of predictions have observed the non-correlation between estimated and actual failure rates.

It is long past time for the electronics design and manufacturing organizations to abandon these invalid and misleading approaches, acknowledge that reliability cannot be estimated from assumptions and calculations, and start using “stress to limits” to find latent failure mechanisms before a product is released to the market.  Indeed, you cannot derive a time to failure for most systems, but no test can provide an actual field “life” estimate for a complex electronic system, nor do we need to. There is more life than is needed in most electronics for most applications.

Fortunately, there is an alternative. A more pragmatic and practical approach is to find to put most engineering and testing resources to discover overlooked design margins or the weakest link early in the design process (HALT) and then use that strength and durability to screen (HASS) for errors during manufacturing quickly.  HALT and HASS have little to do with a specific type of chamber or chamber capabilities. It is a fundamental change in the frame of reference for reliability development, moving instead from time metrics to stress/limit metrics. Many have already realized this new frame of reference. Since they have found these methods much more efficient and cost-effective for developing robust electronic systems, they have a competitive advantage. They are not about to let the world or their competitors know how successful these methods are.