Understanding the Impact of Process Variability: A Tool to Build Student Intuition

2009 ◽  
Vol 7 (2) ◽  
pp. 423-428 ◽  
Author(s):  
John B. Jensen ◽  
Hemant V. Kher
Keyword(s):  
Process Variability ◽  
The Impact

Sensor Optimization for Fault Diagnosis in Single Fixture Systems: A Methodology

1999 ◽  
Vol 121 (1) ◽  
pp. 109-117 ◽  
Author(s):  
A. Khan ◽  
D. Ceglarek ◽  
J. Shi ◽  
J. Ni ◽  
T. C. Woo
Keyword(s):  
Fault Diagnosis ◽  
Diagnostic Procedures ◽  
Analytical Methodology ◽  
Process Variability ◽  
Variation Reduction ◽  
Sensor Optimization ◽  
Automobile Assembly ◽  
Fault Type ◽  
Fixture Configuration ◽  
The Impact

Fixture fault diagnosis is a critical component of currently evolving techniques aimed at manufacturing variation reduction. The impact of sensor location on the effectiveness of fault-type discrimination in such diagnostic procedures is significant. This paper proposes a methodology for achieving optimal fault-type discrimination through an optimized configuration of defined “sensor locales.” The optimization is presented in the context of autobody fixturing—a predominant cause of process variability in automobile assembly. The evaluation criterion for optimization is an improvement in the ability to provide consistency of best match, in a pattern recognition sense, of any fixture error to a classified, anticipated error set. The proposed analytical methodology is novel in addressing optimization by incorporating fixture design specifications in sensor locale planning—constituting a Design for Fault Detectability approach. Examples of the locale planning for a single fixture sensor layout and an application to an industrial fixture configuration are presented to illustrate the proposed methodology.

scholarly journals Simulation and Analysis of Uncooled Microbolometer for Serial Readout Architecture

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Musaed Alhussein ◽  
Syed Irtaza Haider
Keyword(s):  
Thermal Image ◽  
Thermal Imager ◽  
Design Environment ◽  
Johnson Noise ◽  
Thermal Detector ◽  
Process Variability ◽  
Bias Power ◽  
Self Heating ◽  
Uncooled Microbolometer ◽  
The Impact

A detailed thermal behavior and theoretical analysis of uncooled resistive microbolometer is presented along with the proposed thermal imager simulator. An accurate model of a thermal detector is required to design a readout circuit that can compensate for the noise due to process variability and self-heating. This paper presents a realistic simulation model of microbolometer that addresses the fixed pattern noise, Johnson noise, and self-heating. Different simulations were performed to study the impact of infrared power and bias power on the performance of microbolometers. The microbolometers were biased with different bias currents along with different thermal parameters of the reference microbolometer to analyze the impact of self-heating on the thermal image. The proposed thermal imager simulator is used as a tool to visually analyze the impact of noise on the quality of a thermal image. This simulator not only helps in compensating the noise prior to the implementation in Analog Design Environment, but also can be used as a platform to explore different readout architectures. In this work, serial readout architecture was simulated with a row of blind microbolometers that served as a reference. Moreover, the algorithm for the proposed thermal imager simulator is presented.

scholarly journals Process Variability—Technological Challenge and Design Issue for Nanoscale Devices

Micromachines ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 6 ◽  
Author(s):  
Jürgen Lorenz ◽  
Eberhard Bär ◽  
Sylvain Barraud ◽  
Andrew Brown ◽  
Peter Evanschitzky ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Process Variations ◽  
Electrical Performance ◽  
Process Equipment ◽  
Process Variability ◽  
Circuit Performance ◽  
Technological Challenge ◽  
Device Properties ◽  
The Impact ◽  
Full Simulation

Current advanced transistor architectures, such as FinFETs and (stacked) nanowires and nanosheets, employ truly three-dimensional architectures. Already for aggressively scaled bulk transistors, both statistical and systematic process variations have critically influenced device and circuit performance. Three-dimensional device architectures make the control and optimization of the device geometries even more important, both in view of the nominal electrical performance to be achieved and its variations. In turn, it is essential to accurately simulate the device geometry and its impact on the device properties, including the effect caused by non-idealized processes which are subject to various kinds of systematic variations induced by process equipment. In this paper, the hierarchical simulation system developed in the SUPERAID7 project to study the impact of variations from equipment to circuit level is presented. The software system consists of a combination of existing commercial and newly developed tools. As the paper focuses on technological challenges, especially issues resulting from the structuring processes needed to generate the three-dimensional device architectures are discussed. The feasibility of a full simulation of the impact of relevant systematic and stochastic variations on advanced devices and circuits is demonstrated.

Process Variability Analysis in Interconnect, Logic, and Arithmetic Blocks of 16-nm FinFET FPGAs

2021 ◽  
Vol 14 (3) ◽  
pp. 1-30
Author(s):  
Endri Taka ◽  
Konstantinos Maragos ◽  
George Lentaris ◽  
Dimitrios Soudris
Keyword(s):  
Correlation Analysis ◽  
Strong Correlation ◽  
Operating Conditions ◽  
Experimental Results ◽  
Moderate Correlation ◽  
Process Variability ◽  
Variability Analysis ◽  
And Performance ◽  
The Impact ◽  
Actual Test

In the current work, we study the process variability of logic, interconnect, and arithmetic/DSP resources in commercial 16-nm FPGAs. We create multiple, soft-macro sensors for each distinct resource under evaluation, and we deploy them across the FPGA fabric to measure intra-die variation, as well as across multiple FPGAs to measure inter-die variation. The derived results are used to create device-signature variability maps characterizing the distribution of variability across the die. Our study includes decoupling of variability to systematic and stochastic parts, exploration of variability under various voltage and temperature conditions and correlation analysis between the variability maps of the different resources. Furthermore, we scrutinize the impact of variability on the performance of actual test circuits and correlate the retrieved results with the sensor-based maps. Our experimental results on four Zynq XCZU7EV FPGAs showed significant intra- and inter-die variability, up to 7.8% and 8.9%, respectively, with a small increase under certain operating conditions. The correlation analysis demonstrated a strong correlation between the logic and arithmetic resources, whereas the interconnects showed a slightly weaker correlation in specific devices. Finally, a relatively moderate correlation was calculated between the variability maps and performance of test circuits due their dissimilar operating behavior versus our sensors.

scholarly journals FinFET Inverter Designs: Behavior and Challenges of Process Variability

2021 ◽  
Vol 16 (2) ◽  
pp. 1-13
Author(s):  
Leonardo Barlette De Moraes ◽  
Alexandra Lackmann Zimpeck ◽  
Cristina Minhardt ◽  
Ricardo Augusto Da Luz Reis
Keyword(s):  
Energy Consumption ◽  
Radiation Effects ◽  
Noise Immunity ◽  
Supply Voltage ◽  
Cost Benefit Analysis ◽  
Schmitt Trigger ◽  
Modern Technology ◽  
Cmos Inverter ◽  
Process Variability ◽  
The Impact

Abstract— Technology scaling alongside the increasing process variability impact in modern technology nodes are themain reasons to control deviations over metrics in IC nanome-ter designs. Schmitt Triggers are traditionally used for noise immunity enhancement, and have been recently applied to mitigate radiation effects and process variability impact. The main contribution of this work is to trace the relationship between transistor sizing, supply voltage, and process variability to get a low energy consumption circuit while still keeping low levels of deviations due to the impact of process-induced variability. It is shown that a cost-benefit analysis can highlight sets of sizing and supply voltage where it can provide a 37.51% decrease in energy consumption while only increasing its sensibility by 7.42%. Furthermore, it is presented that the dependence of supply voltage and sensibility to process variability is not directly related, with slight decreases in the supply volt-ages bringing better results. Overall, the traditional CMOS inverter is still the fastest and most energy-efficient circuit, although, when comparing noise immunity characteristics, the 6-Transistor Schmitt Trigger presents higher noise margins, slopes, gains, and hysteresis ratios. The improvements,although, may increase propagation times, energy consumption, and area.

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