Embedded nano-electronic devices have spread in daily life over the past ten years. Chip and embedded system manufacturing has thus become more challenging in recent years.When safety-critical sectors like the automobile are considered, addressing system anomalies and faults is crucial. Therefore, it is necessary to develop and research innovative ways to maintain high reliability in safety-critical sectors despite the complexity of present Systems-on-Chip (SoCs).In order to ensure high reliability, and be compliant with reliability standards, designers started to add additional circuitry to perform on-device tests. Built-In-Self-Test (BIST) is a technology that allows to conduct exhaustive tests within devices and, most importantly, without the need for external equipment. BIST can detect faults by outputting a signature at test end, which can be compared with a known value. Thus such known signatures are key, and in case of a signature mismatch it is not trivial to understand the root cause of the failure.This paper proposes a methodology to find the first failing pattern which causes the BIST’s signature to deviate and a way to collect good signatures from in-field devices, at key on/off, where BISTs are programmed and executed by the firmware at maximum frequency for an industrial case study produced by STMicroelectronics.The transition delay fault model is the primary target for the described work.

Collecting diagnostic information through dichotomic search from Logic BIST of failing in-field automotive SoCs with delay faults / Bernardi, Paolo; Filipponi, Gabriele; Reorda, Matteo Sonza; Appello, Davide; Bertani, Claudia; Tancorre, Vincenzo. - ELETTRONICO. - (2023), pp. 21-26. (Intervento presentato al convegno International Symposium on Design and Diagnostics of Electronic Circuits and Systems tenutosi a Tallinn (Estonia) nel 03-05 May 2023) [10.1109/DDECS57882.2023.10139670].

Collecting diagnostic information through dichotomic search from Logic BIST of failing in-field automotive SoCs with delay faults

Bernardi, Paolo;Filipponi, Gabriele;Reorda, Matteo Sonza;
2023

Abstract

Embedded nano-electronic devices have spread in daily life over the past ten years. Chip and embedded system manufacturing has thus become more challenging in recent years.When safety-critical sectors like the automobile are considered, addressing system anomalies and faults is crucial. Therefore, it is necessary to develop and research innovative ways to maintain high reliability in safety-critical sectors despite the complexity of present Systems-on-Chip (SoCs).In order to ensure high reliability, and be compliant with reliability standards, designers started to add additional circuitry to perform on-device tests. Built-In-Self-Test (BIST) is a technology that allows to conduct exhaustive tests within devices and, most importantly, without the need for external equipment. BIST can detect faults by outputting a signature at test end, which can be compared with a known value. Thus such known signatures are key, and in case of a signature mismatch it is not trivial to understand the root cause of the failure.This paper proposes a methodology to find the first failing pattern which causes the BIST’s signature to deviate and a way to collect good signatures from in-field devices, at key on/off, where BISTs are programmed and executed by the firmware at maximum frequency for an industrial case study produced by STMicroelectronics.The transition delay fault model is the primary target for the described work.
2023
979-8-3503-3277-3
File in questo prodotto:
File Dimensione Formato  
2023058710.pdf

accesso aperto

Descrizione: Accepted paper with copyright
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 4.51 MB
Formato Adobe PDF
4.51 MB Adobe PDF Visualizza/Apri
Collecting_diagnostic_information_through_dichotomic_search_from_Logic_BIST_of_failing_in-field_automotive_SoCs_with_delay_faults.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 5.19 MB
Formato Adobe PDF
5.19 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2979773