Virtual qualification is the first stage of the overall qualification process. It is the application of Physics of Failure (PoF) based reliability assessment to determine if a proposed product can survive its anticipated life cycle

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Hilaire Ananda Perera
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http://www.linkedin.com/in/hilaireperera
Virtual qualification facilitates selection of cost‐effective test parameters for validating reliability
assessment and design and also aids in the selection of components by providing information on their
impact on reliability. Because the virtual qualification process does not involve manufactured prototypes
and physical testing, it is a much more economical and time‐efficient process compared to a
manufactured product qualification process [28].
The flowchart of the virtual qualification process is shown in the above Figure. The inputs consist of life‐
cycle profile and product characteristics. The life‐ cycle profile can be further categorized as
environmental and operational stresses as shown. The inputs are fed into a PoF model and simulation
software where stress analysis, reliability assessment, and stresses sensitivity analysis are performed.
The outputs of virtual qualification are predicted TTF based on the most dominant failure mechanisms,
stress margin conditions, and screening and accelerated testing conditions.
In addition to TTF prediction and reliability assessment, virtual qualification combined with advanced
optimization techniques can be used to optimize the design criteria including cost, electrical
performance, thermal management, physical attributes, and reliability. By examining potential trade‐
offs between the aforementioned criteria, ideal values can be achieved for specific applications.
In the virtual qualification process, it is imperative to use the most accurate inputs including
material properties, design configuration, dimensions, and operational and environmental conditions.
Furthermore, the failure mechanism models used in TTF prediction and reliability assessment must be
valid. If the data or models on which the virtual qualification is performed is inaccurate or unreliable,
any qualification results based on the data or models are suspicious.
25. Cunningham, J., Valentin, R., Hillman, C, Dasgupta, A., and Osterman, M., “A demonstration of
virtual qualification for the design of electronic hardware,” Proceedings of the Institute of
Environmental Sciences and Technology Meeting, April 24, 2001.
26. Hu, J., Barker, D., Dasgupta, A., and Arora, A., “The role of failure mechanism identification in
accelerated testing,” Journal of the Institute of Environmental Sciences, vol. 36, no. 4, pp. 39–45,
1993.
27. Caruso, H. and Dasgupta, A., “A fundamental overview of analytical acceler‐ ated testing
models,” Journal of the Institute of Environmental Sciences, vol. 41, no. 1, pp. 16–30, 1998.
28. McCluskey, P., Pecht, M., and Azarm, S., “Reducing time‐to‐market using virtual qualification,”
Proceedings of the Institute of Environmental Sciences Conference, pp. 148–152, 1997