Fault simulation for structural testing of analogue integrated circuits

In this thesis the ANTICS analogue fault simulation software is described which provides a statistical approach to fault simulation for accurate analogue IC test evaluation. The traditional figure of fault coverage is replaced by the average probability of fault detection. This is later refined by considering the probability of fault occurrence to generate a more realistic, weighted test metric. Two techniques to reduce the fault simulation time are described, both of which show large reductions in simulation time with little loss of accuracy. The final section of the thesis presents an accurate comparison of three test techniques and an evaluation of dynamic supply current monitoring. An increase in fault detection for dynamic supply current monitoring is obtained by removing the DC component of the supply current prior to measurement

Quiescent current testing of CMOS data converters

Power supply quiescent current (IDDQ) testing has been very effective in VLSI circuits designed in CMOS processes detecting physical defects such as open and shorts and bridging defects. However, in sub-micron VLSI circuits, IDDQ is masked by the increased subthreshold (leakage) current of MOSFETs affecting the efficiency of I¬DDQ testing. In this work, an attempt has been made to perform robust IDDQ testing in presence of increased leakage current by suitably modifying some of the test methods normally used in industry. Digital CMOS integrated circuits have been tested successfully using IDDQ and IDDQ methods for physical defects. However, testing of analog circuits is still a problem due to variation in design from one specific application to other. The increased leakage current further complicates not only the design but also testing. Mixed-signal integrated circuits such as the data converters are even more difficult to test because both analog and digital functions are built on the same substrate. We have re-examined both IDDQ and IDDQ methods of testing digital CMOS VLSI circuits and added features to minimize the influence of leakage current. We have designed built-in current sensors (BICS) for on-chip testing of analog and mixed-signal integrated circuits. We have also combined quiescent current testing with oscillation and transient current test techniques to map large number of manufacturing defects on a chip. In testing, we have used a simple method of injecting faults simulating manufacturing defects invented in our VLSI research group. We present design and testing of analog and mixed-signal integrated circuits with on-chip BICS such as an operational amplifier, 12-bit charge scaling architecture based digital-to-analog converter (DAC), 12-bit recycling architecture based analog-to-digital converter (ADC) and operational amplifier with floating gate inputs. The designed circuits are fabricated in 0.5 μm and 1.5 μm n-well CMOS processes and tested. Experimentally observed results of the fabricated devices are compared with simulations from SPICE using MOS level 3 and BSIM3.1 model parameters for 1.5 μm and 0.5 μm n-well CMOS technologies, respectively. We have also explored the possibility of using noise in VLSI circuits for testing defects and present the method we have developed

ENHANCEMENT OF MARKOV RANDOM FIELD MECHANISM TO ACHIEVE FAULT-TOLERANCE IN NANOSCALE CIRCUIT DESIGN

As the MOSFET dimensions scale down towards nanoscale level, the reliability of circuits based on these devices decreases. Hence, designing reliable systems using these nano-devices is becoming challenging. Therefore, a mechanism has to be devised that can make the nanoscale systems perform reliably using unreliable circuit components. The solution is fault-tolerant circuit design. Markov Random Field (MRF) is an effective approach that achieves fault-tolerance in integrated circuit design. The previous research on this technique suffers from limitations at the design, simulation and implementation levels. As improvements, the MRF fault-tolerance rules have been validated for a practical circuit example. The simulation framework is extended from thermal to a combination of thermal and random telegraph signal (RTS) noise sources to provide a more rigorous noise environment for the simulation of circuits build on nanoscale technologies. Moreover, an architecture-level improvement has been proposed in the design of previous MRF gates. The redesigned MRF is termed as Improved-MRF. The CMOS, MRF and Improved-MRF designs were simulated under application of highly noisy inputs. On the basis of simulations conducted for several test circuits, it is found that Improved-MRF circuits are 400 whereas MRF circuits are only 10 times more noise-tolerant than the CMOS alternatives. The number of transistors, on the other hand increased from a factor of 9 to 15 from MRF to Improved-MRF respectively (as compared to the CMOS). Therefore, in order to provide a trade-off between reliability and the area overhead required for obtaining a fault-tolerant circuit, a novel parameter called as ‘Reliable Area Index’ (RAI) is introduced in this research work. The value of RAI exceeds around 1.3 and 40 times for MRF and Improved-MRF respectively as compared to CMOS design which makes Improved- MRF to be still 30 times more efficient circuit design than MRF in terms of maintaining a suitable trade-off between reliability and area-consumption of the circuit

[Delta] IDDQ testing of a CMOS 12-bit charge scaling digital-to-analog converter

This work presents design, implementation and test of a built-in current sensor (BICS) for ∆IDDQ testing of a CMOS 12-bit charge scaling digital-to-analog converter (DAC). The sensor uses power discharge method for the fault detection. The sensor operates in two modes, the test mode and the normal mode. In the test mode, the BICS is connected to the circuit under test (CUT) which is DAC and detects abnormal currents caused by manufacturing defects. In the normal mode, BICS is isolated from the CUT. The BICS is integrated with the DAC and is implemented in a 0.5 μm n-well CMOS technology. The DAC uses charge scaling method for the design and a low voltage (0 to 2.5 V) folded cascode op-amp. The built-in current sensor (BICS) has a resolution of 0.5 μA. Faults have been introduced into DAC using fault injection transistors (FITs). The method of ∆IDDQ testing has been verified both from simulation and experimental measurements

Analog Fault Identification in RF Circuits using Artificial Neural Networks and Constrained Parameter Extraction

The increase of analog and mixed-signal circuitry in modern RF and microwave integrated circuits demands for improved analog fault diagnosis methods. While digital fault diagnosis is well established, the analog counterpart is relatively much less mature due to the intrinsic complexity in analog faults and their corresponding identification. In this work, we present an artificial neural network (ANN) modeling approach to efficiently emulate the injection of analog faults in RF circuits. The resulting meta-model is used for fault identification by applying an optimization-based process using a constrained parameter extraction formulation. The proposed methodology is illustrated by a faulty analog CMOS RF circuit

Analog Gross Fault Identification in RF Circuits using Neural Models and Constrained Parameter Extraction

The demand and relevance of efficient analog fault diagnosis methods for modern RF and microwave integrated circuits increases with the growing need and complexity of analog and mixed-signal circuitry. The well-established digital fault diagnosis methods are insufficient for analog circuitry due to the intrinsic complexity in analog faults and their corresponding identification process. In this work, we present an artificial neural network (ANN) modeling approach to efficiently emulate the injection of analog faults in RF circuits. The resulting meta-model is used for fault identification by applying an optimization-based process using a constrained parameter extraction formulation. A generalized neural modeling formulation to include auxiliary measurements in the circuit is proposed. This generalized formulation significantly increases the uniqueness of the faults identification process. The proposed methodology is illustrated by two faulty analog circuits: a CMOS RF voltage amplifier and a reconfigurable bandpass microstrip filter

Stochastic Digital Circuits for Probabilistic Inference

We introduce combinational stochastic logic, an abstraction that generalizes deterministic digital circuit design (based on Boolean logic gates) to the probabilistic setting. We show how this logic can be combined with techniques from contemporary digital design to generate stateless and stateful circuits for exact and approximate sampling from a range of probability distributions. We focus on Markov chain Monte Carlo algorithms for Markov random fields, using massively parallel circuits. We implement these circuits on commodity reconfigurable logic and estimate the resulting performance in time, space and price. Using our approach, these simple and general algorithms could be affordably run for thousands of iterations on models with hundreds of thousands of variables in real time