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The Automotive Functional Safety standard ISO 26262 introduced a PMHF (Probabilistic Metric for random Hardware Failures) in Part 5 and Part 10 by calculating the system failure rates and assessing the ASIL (Automotive Safety and Integrity Level) for functional safety. The new version of the standard expands the PMHF concept by further promoting a new metric “average probability of failure per hour over the operational lifetime of the item”, which has not been commonly used by the reliability engineering community. In order to clarify how PMHF is calculated within the content of ISO 26262, this paper will discuss how to calculate both the failure rate and the average probability of failure per hour in terms of definitions, sources of the data, applications, and advantages and disadvantages.

In early design activities (typically before the hardware is built), a reliability prediction is often required for the electronic components and systems in order to assess their future reliability and in many cases to meet customer specifications. These specifications may include the allocated reliability for a particular electronic unit and in the cases of functional safety products to meet the ASIL (Automotive Safety and Integrity Level) requirement specified by the functional safety standard ISO 26262. The standard allows for the use of “statistics based on field returns or tests” as a valid alternative to the handbook-based reliability prediction. This paper presents a newly developed SAE-J3083 standard “Reliability Prediction for Automotive Electronics Based on Field Return Data”, which covers the types of the required data, ways to collect it, and the methodology of how to process this data to calculate the failure rates and meet the expected safety goals.

This paper discusses the effect of the field stress variance on the value of demonstrated reliability in the automotive testing. In many cases the acceleration factor for a reliability demonstration test is calculated based on a high percentile automotive stress level, typically corresponding to severe user or environmental conditions. In those cases the actual field (‘true’) reliability for the population will be higher than that demonstrated by a validation test. This paper presents an analytical approach to estimating ‘true’ field reliability based on the acceleration model and stress variable distribution over the vehicle population. The method is illustrated by an example of automotive electronics reliability demonstration testing.