Diagnosis of assembly failures for System-in-Package RF tuners

Erdogan, E.S.; Ozev, Sule; Cauvet, Philippe

doi:10.1109/iscas.2008.4541910

Cited by 6 publications

(4 citation statements)

References 7 publications

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“…Rule-based diagnosis approaches represent the experience of skilled diagnosticians in the form of rules which generally take the form "IF symptom(s) THEN fault(s)" [45,42], as illustrated in Fig. 1.…”

Section: Overview Of Diagnosis Approaches For Analog Circuits 41 Rule...mentioning

confidence: 99%

Machine Learning Support for Diagnosis of Analog Circuits

Stratigopoulos

2022

Machine Learning Support for Fault Diagnosis of System-on-Chip

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We discuss the state-of-the-art on fault diagnosis for analog circuits with a focus on techniques that leverage machine learning. For a chip that has failed either in post-manufacturing testing or in the field of operation, fault diagnosis is launched to identify the root-cause of failure at sub-block level and transistor-level. In this context, machine learning can be used to build a smart system that predicts the fault that has occurred from diagnostic measurements extracted on the chip. We discuss the different elements of a diagnosis flow for analog circuits, including fault modeling, fault simulation, diagnostic measurement extraction and selection, and the machine learning algorithms that compose the prediction system. We also demonstrate a machine learning-based diagnosis flow on an industrial case study.

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Section: Overview Of Diagnosis Approaches For Analog Circuits 41 Rule...mentioning

confidence: 99%

Machine Learning Support for Diagnosis of Analog Circuits

Stratigopoulos

2022

Machine Learning Support for Fault Diagnosis of System-on-Chip

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“…They can also provide valuable feedback for achieving faulttolerance through calibration, tuning, or even reconfigurability [42,43,44,45,46]. Finally, DFT and BIST techniques can provide valuable feedback for diagnosis purposes [47,48,49,50,51,52,53,54,55,56,57,58,59]. Diagnosing the root-causes of failures in the first prototypes helps to reduce design iterations and to meet the time-to-market goal.…”

Section: Integrated Test -An Overviewmentioning

confidence: 99%

Analog and Mixed-Signal Test

Stratigopoulos¹,

Kaminska²

2017

Electronic Design Automation for IC System Design, Verification, and Testing

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“…Finally, DFT and BIST techniques can provide valuable feedback for diagnosis purposes [47,48,49,50,51,52,53,54,55,56,57,58,59]. Diagnosing the root-causes of failures in the first prototypes helps to reduce design iterations and to meet the time-to-market goal.…”

Section: Integrated Test -An Overviewmentioning

confidence: 99%

Analog and Mixed Signal Test

Kaminska¹

2006

Industrial Information Technology

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Diagnosis of assembly failures for System-in-Package RF tuners

Cited by 6 publications

References 7 publications

Machine Learning Support for Diagnosis of Analog Circuits

Machine Learning Support for Diagnosis of Analog Circuits

Analog and Mixed-Signal Test

Analog and Mixed Signal Test

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