A methodology for measuring transistor ageing effects towards accurate reliability simulation

Maricau, Elie; Gielen, Georges

doi:10.1109/iolts.2009.5195978

Cited by 2 publications

(2 citation statements)

References 6 publications

(11 reference statements)

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“…There is a clear understanding of the underlying degradation process. There exists vast literature such as: fatigue models for modelling initiation and propagation of cracks in structural components [25], electrolytic overstress ageing [26], Arrhenius equation for prediction of resistance drift [27], physics inspired power model [28] or log-linear model for degradation of current drain [29], physics-inspired exponential degradation model for aluminum electrolytic capacitors [30] etc. Given the behavioral model of damage progression, the current SOH is popularly obtained in probabilistic domain with the help of Bayesian estimation techniques.…”

Section: Data Driven Prognosticsmentioning

confidence: 99%

Particle Filter Based Integrated Health Monitoring in Bond Graph Framework

Jha

Dauphin-Tanguy

Ould-Bouamama

2017

Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems

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This chapter presents a holistic method to addresses the issue of health monitoring of system parameters in Bond Graph (BG). The advantages of BGs are integrated with Bayesian estimation techniques for efficient diagnostics and prognostics of faults. In particular, BG in Linear fractional transformations (LFT) are used for modelling the global uncertain system and sequential Monte Carlo method based Particle filters (PF) are used for estimation of state of health (SOH) and subsequent prediction of the remaining useful life (RUL). In this work, the method is described with respect to a single system parameter which is chosen as prognostic candidate. The prognostic candidate undergoes progressive degradation and its degradation model is assumed to be known a priori. The system operates in control feedback loop. The detection of degradation initiation is achieved using BG LFT based robust fault detection technique. The latter forms an efficient diagnostic module. PFs are exploited for efficient Bayesian inference of SOH of the prognostic candidate. Moreover, prognostics is achieved by assessment of RUL in probabilistic domain. The issue of prognostics is formulated as joint stateparameter estimation problem, a hybrid prognostic approach, wherein the fault model is constructed by considering the statistical degradation model of the prognostic candidate. The observation equation is constructed from nominal part of the BG-LFT derived Analytical Redundancy Relations (ARR). Various uncertainties which arise because of noise on ARR based measurements, degradation process, environmental conditions etc. are effectively managed by PF. This allows the production of effective predictions of the RUL of the prognostic candidate with suitable confidence bounds. The method is applied over a mechatronic system in real time and performance is assessed using suitable metrics.

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Section: Data Driven Prognosticsmentioning

confidence: 99%

Particle Filter Based Integrated Health Monitoring in Bond Graph Framework

Jha

Dauphin-Tanguy

Ould-Bouamama

2017

Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems

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“…NBTI and HCI are dominant wearout effects and have thus been more intensively studied [27]. Conventionally, aging effects are studied under DC stress conditions where it is easier to measure transistor parameters [18,22,25]. However, AC stress conditions are more realistic for high-frequency long-term CMOS operation; hence works such as those of [19,36,27] discuss such long-term models, while other works introduce the relationship between DC and AC stress conditions [37].…”

Section: Related Workmentioning

confidence: 99%

Use it or lose it

Vitkovskiy

Gratz

Soteriou

2013

Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture

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Moore's Law scaling is continuing to yield even higher transistor density with each succeeding process generation, leading to today's multi-core Chip Multi-Processors (CMPs) with tens or even hundreds of interconnected cores or tiles. Unfortunately, deep sub-micron CMOS process technology is marred by increasing susceptibility to wearout. Prolonged operational stress gives rise to accelerated wearout and failure, due to several physical failure mechanisms, including Hot Carrier Injection (HCI) and Negative Bias Temperature Instability (NBTI). Each failure mechanism correlates with different usage-based stresses, all of which can eventually generate permanent faults. While the wearout of an individual core in many-core CMPs may not necessarily be catastrophic for the system, a single fault in the interprocessor Network-on-Chip (NoC) fabric could render the entire chip useless, as it could lead to protocol-level deadlocks, or even partition away vital components such as the memory controller or other critical I/O. In this paper, we develop critical path models for HCI-and NBTI-induced wear due to the actual stresses caused by real workloads, applied onto the interconnect microarchitecture. A key finding from this modeling being that, counter to prevailing wisdom, wearout in the CMP on-chip interconnect is correlated with lack of load observed in the NoC routers, rather than high load. We then develop a novel wearout-decelerating scheme in which routers under low load have their wearout-sensitive components exercised, without significantly impacting cycle time, pipeline depth, area or power consumption of the overall router. We subsequently show that the proposed design yields a 13.8×-65× increase in CMP lifetime.

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A methodology for measuring transistor ageing effects towards accurate reliability simulation

Cited by 2 publications

References 6 publications

Particle Filter Based Integrated Health Monitoring in Bond Graph Framework

Particle Filter Based Integrated Health Monitoring in Bond Graph Framework

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