Abstract
Diagnosis of functional failures at the board level is critical for improving product yield and reducing manufacturing cost. State-of-the-art board-level diagnostic software is unable to cope with high complexity and ever-increasing clock frequencies, and the identification of the root cause of failure on a board is a major problem today. Ambiguous or incorrect repair suggestions lead to long debug times and even wrong repair actions, which significantly increases the repair cost and adversely impacts yield.
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Notes
- 1.
Exact success ratio for the deployed system are not presented here in order to protect company confidential data.
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Ye, F., Zhang, Z., Chakrabarty, K., Gu, X. (2017). Diagnosis Using Support Vector Machines (SVM). In: Knowledge-Driven Board-Level Functional Fault Diagnosis. Springer, Cham. https://doi.org/10.1007/978-3-319-40210-9_2
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DOI: https://doi.org/10.1007/978-3-319-40210-9_2
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