Abstract
Screening electronic components in space industry is a difficult challenge because there are many tests, and the sample sizes are small. In statistics, this situation is called HDLSS (High Dimension Low Sample Size) and specific methods must be developed to propose an efficient screening, with a good detection of outliers which could transform in future reliability issues. In this paper we present the six challenges of screening and we propose a solution which is a complex algorithm, including a new multivariate approach, a dimension reduction for low sample size, and a controlled projection pursuit method adapted to a very large number of tests. A case-study at Microchip will be presented, with actual examples and a demo of the software. Measurement issues and detectability will also be discussed. Finally, the summary of the results at Microchip and the perspectives and future work will be addressed.
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