Electronic devices intended for safety-critical industries, such as automotive, undergo extensive testing to ensure their reliability and compliance with safety standards. It is critical to constantly monitor, even in mission mode, that no failure due to wear and tear can compromise their reliability. Using self-testing circuitry such as Logic Built-In Self-Test (LBIST), it is possible to implement key-on and key-off tests to monitor the reliability status of the device also during its operational lifetime. This paper proposes a methodology based on LBIST data collection launched at key-on and key-off via CPU to improve the logic diagnosis of devices returned from the field. The proposed methodology exploits the reprogramming of pattern generation and signature compaction registers to retrieve information about all the failing and successful patterns instead of the sole generic fail information. As such, the proposal achieves better diagnostic effectiveness than other state-of-the-art methodologies. Experimental results show that the diagnosis has a significant increase in accuracy for an industrial automotive device manufactured by STMicroelectronics.
Enhancing Logic Diagnosis of field returns through Logic BIST in Automotive SoCs / Bernardi, Paolo; Filipponi, Gabriele; Iaria, Giusy; Bertani, Claudia; Tancorre, Vincenzo. - (2025). (Intervento presentato al convegno 2025 IEEE Latin American Test Symposium tenutosi a San Andres Islas (COL) nel 11-14 March 2025) [10.1109/LATS65346.2025.10963955].
Enhancing Logic Diagnosis of field returns through Logic BIST in Automotive SoCs
Paolo Bernardi;Gabriele Filipponi;Giusy Iaria;
2025
Abstract
Electronic devices intended for safety-critical industries, such as automotive, undergo extensive testing to ensure their reliability and compliance with safety standards. It is critical to constantly monitor, even in mission mode, that no failure due to wear and tear can compromise their reliability. Using self-testing circuitry such as Logic Built-In Self-Test (LBIST), it is possible to implement key-on and key-off tests to monitor the reliability status of the device also during its operational lifetime. This paper proposes a methodology based on LBIST data collection launched at key-on and key-off via CPU to improve the logic diagnosis of devices returned from the field. The proposed methodology exploits the reprogramming of pattern generation and signature compaction registers to retrieve information about all the failing and successful patterns instead of the sole generic fail information. As such, the proposal achieves better diagnostic effectiveness than other state-of-the-art methodologies. Experimental results show that the diagnosis has a significant increase in accuracy for an industrial automotive device manufactured by STMicroelectronics.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2999289