Statistical analysis during the reliability simulation

Bestory, Corinne; Fabert, Marc; Lévi, H.

doi:10.1016/j.microrel.2007.07.079

Cited by 19 publications

(6 citation statements)

References 5 publications

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“…Reliability and safety analysis is conducted by evaluating automatically generated fault trees (FT) or reliability block diagrams (RBD). Bestory et al 9 describe electronic circuit behavior and component-based degradation models in VHDL-AMS and performs statistical reliability analysis using Monte-Carlo-Simulations over lifetime.…”

Section: Modeling System Behavior and Reliabilitymentioning

confidence: 99%

Formulation of reliability-related objective functions for design of intelligent mechatronic systems

Kaul

Meyer

Sextro

2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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State-of-the-art mechatronic systems offer inherent intelligence that enables them to autonomously adapt their behavior to current environmental conditions and to their own system state. This autonomous behavior adaptation is made possible by software in combination with complex sensor and actuator systems and by sophisticated information processing, all of which make these systems increasingly complex. This increasing complexity makes the design process a challenging task and brings new complex possibilities for operation and maintenance. However, with the risk of increased system complexity also comes the chance to adapt system behavior based on current reliability, which in turn increases reliability. The development of such an adaption strategy requires appropriate methods to evaluate reliability based on currently selected system behavior. A common approach to implement such adaptivity is to base system behavior on different working points that are obtained using multiobjective optimization. During operation, selection among these allows a changed operating strategy. To allow for multiobjective optimization, an accurate system model including system reliability is required. This model is repeatedly evaluated by the optimization algorithm. At present, modeling of system reliability and synchronization of the models of behavior and reliability is a laborious manual task and thus very error-prone. Since system behavior is crucial for system reliability, an integrated model is introduced that integrates system behavior and system reliability. The proposed approach is used to formulate reliability-related objective functions for a clutch test rig that are used to compute feasible working points using multiobjective optimization.

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Section: Modeling System Behavior and Reliabilitymentioning

confidence: 99%

Formulation of reliability-related objective functions for design of intelligent mechatronic systems

Kaul

Meyer

Sextro

2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…3 illustrates how a failure density function w θ [k] is fitted with a generalized extreme value (GEV) distribution, indicating the failure-time distribution of the circuit. In contradiction to [3], this work uses a SPICE-netlist-based reliability simulation (see section III) to analyze the failure rate. This provides a more accurate and detailed picture of how a circuit will behave under degradation, especially for nanometer CMOS where short-channel effects are emerging.…”

Section: Variability-aware Reliability Simulationmentioning

confidence: 99%

“…1. Bestory et al [3] used behavioral circuit models to calculate the circuit reliability under process variations. This approach, although it is fast, lacks accuracy especially in nanometer CMOS when short-channel effects, usually not included in behavioral models, come into play.…”

Section: Introductionmentioning

confidence: 99%

Efficient reliability simulation of analog ICs including variability and time-varying stress

Maricau

Gielen

2009

2009 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition

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Aggressive scaling to nanometer CMOS technologies causes both analog and digital circuit parameters to degrade over time due to die-level stress effects (i.e. NBTI, HCI, TDDB, etc). In addition, failure-time dispersion increases due to increasing process variability. In this paper an innovative methodology to simulate analog circuit reliability is presented. Advantages over current state of the art reliability simulators include, among others, the possibility to estimate the impact of variability and the ability to account for the effects of complex time-varying stress signals. Results show that taking time-varying stress signals into account provides circuit reliability information not visible with classic DC-only reliability simulators. Also, variability-aware reliability simulation results indicate a significant percentage of early circuit failures compared to failure-time results based on nominal design only.

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“…The latter is activated by the stress applied on the cell during its life time (erasing, programing, temperature variations, etc.). One of the major issues is the global cost of such studies [2]. One solution lies in specific device test structures integrated in the same technology as the final product.…”

Section: Introductionmentioning

confidence: 99%

An evaluation of the extrinsic cells number in a memory array using cross-correlation products and deconvolution: an instance of a microelectronics experimental inverse problem

Micolau

Postel-Pellerin

Laffont

et al. 2011

Inverse Problems in Science and Engineering

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This work is devoted to a new, fast and efficient method of evaluating the number of marginal cells in a non-volatile electrical memory array. This extraction from experimental data is fundamentally an inverse problem. The method proposed here is based on simple cross-correlation functions and de-convoluting operations. With the microelectronics device dimension downscaling, the reliability of non-volatile electrical memory has become crucial and any marginal cell can compromise the functioning of the whole array (containing hundreds of thousands of elementary cells). A specific array called Cell Array Structure Test (CAST) has been developed as a useful characterization tool to statistically study retention and endurance performance with few experimental operations. However, this device cannot easily count the low number of failed cells among hundreds of thousands. That is why we had to develop a mathematical method to extract this major quantity from measurements. This method has been validated on an EEPROM CAST -0.13 mm technology node, but it is extendable to all memory devices integrated in parallel array and more generally to any electrical measurement done in a similar configuration.

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Statistical analysis during the reliability simulation

Cited by 19 publications

References 5 publications

Formulation of reliability-related objective functions for design of intelligent mechatronic systems

Formulation of reliability-related objective functions for design of intelligent mechatronic systems

Efficient reliability simulation of analog ICs including variability and time-varying stress

An evaluation of the extrinsic cells number in a memory array using cross-correlation products and deconvolution: an instance of a microelectronics experimental inverse problem

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