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Communication Dans Un Congrès Année : 2021

Cell-Aware Diagnosis of Customer Returns Using Bayesian Inference

Résumé

This paper presents a new cell-aware diagnosis flow that can be used to address a specific scenario (test protocol) one may encounter during diagnosis of customer returns. In this flow, we use a Bayesian classification method to precisely identify defect candidates. Experiments done on benchmark circuits as well as on a test chip from STMicroelectronics have proven the efficacy of our flow in terms of diagnosis accuracy and resolution.
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Dates et versions

hal-03266815 , version 1 (14-10-2021)

Identifiants

Citer

Safa Mhamdi, Patrick Girard, Arnaud Virazel, Alberto Bosio, Aymen Ladhar. Cell-Aware Diagnosis of Customer Returns Using Bayesian Inference. ISQED 2021 - 22nd International Symposium on Quality Electronic Design, Apr 2021, Santa Clara (virtual), United States. pp.48-53, ⟨10.1109/ISQED51717.2021.9424337⟩. ⟨hal-03266815⟩
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