1,226 research outputs found

    Fault simulation for structural testing of analogue integrated circuits

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    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

    Fault-based Analysis of Industrial Cyber-Physical Systems

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    The fourth industrial revolution called Industry 4.0 tries to bridge the gap between traditional Electronic Design Automation (EDA) technologies and the necessity of innovating in many indus- trial fields, e.g., automotive, avionic, and manufacturing. This complex digitalization process in- volves every industrial facility and comprises the transformation of methodologies, techniques, and tools to improve the efficiency of every industrial process. The enhancement of functional safety in Industry 4.0 applications needs to exploit the studies related to model-based and data-driven anal- yses of the deployed Industrial Cyber-Physical System (ICPS). Modeling an ICPS is possible at different abstraction levels, relying on the physical details included in the model and necessary to describe specific system behaviors. However, it is extremely complicated because an ICPS is com- posed of heterogeneous components related to different physical domains, e.g., digital, electrical, and mechanical. In addition, it is also necessary to consider not only nominal behaviors but even faulty behaviors to perform more specific analyses, e.g., predictive maintenance of specific assets. Nevertheless, these faulty data are usually not present or not available directly from the industrial machinery. To overcome these limitations, constructing a virtual model of an ICPS extended with different classes of faults enables the characterization of faulty behaviors of the system influenced by different faults. In literature, these topics are addressed with non-uniformly approaches and with the absence of standardized and automatic methodologies for describing and simulating faults in the different domains composing an ICPS. This thesis attempts to overcome these state-of-the-art gaps by proposing novel methodologies, techniques, and tools to: model and simulate analog and multi-domain systems; abstract low-level models to higher-level behavioral models; and monitor industrial systems based on the Industrial Internet of Things (IIOT) paradigm. Specifically, the proposed contributions involve the exten- sion of state-of-the-art fault injection practices to improve the ICPSs safety, the development of frameworks for safety operations automatization, and the definition of a monitoring framework for ICPSs. Overall, fault injection in analog and digital models is the state of the practice to en- sure functional safety, as mentioned in the ISO 26262 standard specific for the automotive field. Starting from state-of-the-art defects defined for analog descriptions, new defects are proposed to enhance the IEEE P2427 draft standard for analog defect modeling and coverage. Moreover, dif- ferent techniques to abstract a transistor-level model to a behavioral model are proposed to speed up the simulation of faulty circuits. Therefore, unlike the electrical domain, there is no extensive use of fault injection techniques in the mechanical one. Thus, extending the fault injection to the mechanical and thermal fields allows for supporting the definition and evaluation of more reliable safety mechanisms. Hence, a taxonomy of mechanical faults is derived from the electrical domain by exploiting the physical analogies. Furthermore, specific tools are built for automatically instru- menting different descriptions with multi-domain faults. The entire work is proposed as a basis for supporting the creation of increasingly resilient and secure ICPS that need to preserve functional safety in any operating context

    Test analysis & fault simulation of microfluidic systems

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    This work presents a design, simulation and test methodology for microfluidic systems, with particular focus on simulation for test. A Microfluidic Fault Simulator (MFS) has been created based around COMSOL which allows a fault-free system model to undergo fault injection and provide test measurements. A post MFS test analysis procedure is also described.A range of fault-free system simulations have been cross-validated to experimental work to gauge the accuracy of the fundamental simulation approach prior to further investigation and development of the simulation and test procedure.A generic mechanism, termed a fault block, has been developed to provide fault injection and a method of describing a low abstraction behavioural fault model within the system. This technique has allowed the creation of a fault library containing a range of different microfluidic fault conditions. Each of the fault models has been cross-validated to experimental conditions or published results to determine their accuracy.Two test methods, namely, impedance spectroscopy and Levich electro-chemical sensors have been investigated as general methods of microfluidic test, each of which has been shown to be sensitive to a multitude of fault. Each method has successfully been implemented within the simulation environment and each cross-validated by first-hand experimentation or published work.A test analysis procedure based around the Neyman-Pearson criterion has been developed to allow a probabilistic metric for each test applied for a given fault condition, providing a quantitive assessment of each test. These metrics are used to analyse the sensitivity of each test method, useful when determining which tests to employ in the final system. Furthermore, these probabilistic metrics may be combined to provide a fault coverage metric for the complete system.The complete MFS method has been applied to two system cases studies; a hydrodynamic “Y” channel and a flow cytometry system for prognosing head and neck cancer.Decision trees are trained based on the test measurement data and fault conditions as a means of classifying the systems fault condition state. The classification rules created by the decision trees may be displayed graphically or as a set of rules which can be loaded into test instrumentation. During the course of this research a high voltage power supply instrument has been developed to aid electro-osmotic experimentation and an impedance spectrometer to provide embedded test

    Machine learning and its applications in reliability analysis systems

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    In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

    AI/ML Algorithms and Applications in VLSI Design and Technology

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    An evident challenge ahead for the integrated circuit (IC) industry in the nanometer regime is the investigation and development of methods that can reduce the design complexity ensuing from growing process variations and curtail the turnaround time of chip manufacturing. Conventional methodologies employed for such tasks are largely manual; thus, time-consuming and resource-intensive. In contrast, the unique learning strategies of artificial intelligence (AI) provide numerous exciting automated approaches for handling complex and data-intensive tasks in very-large-scale integration (VLSI) design and testing. Employing AI and machine learning (ML) algorithms in VLSI design and manufacturing reduces the time and effort for understanding and processing the data within and across different abstraction levels via automated learning algorithms. It, in turn, improves the IC yield and reduces the manufacturing turnaround time. This paper thoroughly reviews the AI/ML automated approaches introduced in the past towards VLSI design and manufacturing. Moreover, we discuss the scope of AI/ML applications in the future at various abstraction levels to revolutionize the field of VLSI design, aiming for high-speed, highly intelligent, and efficient implementations

    High Speed Test Interface Module Using MEMS Technology

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    With the transient frequency of available CMOS technologies exceeding hundreds of gigahertz and the increasing complexity of Integrated Circuit (IC) designs, it is now apparent that the architecture of current testers needs to be greatly improved to keep up with the formidable challenges ahead. Test requirements for modern integrated circuits are becoming more stringent, complex and costly. These requirements include an increasing number of test channels, higher test-speeds and enhanced measurement accuracy and resolution. In a conventional test configuration, the signal path from Automatic Test Equipment (ATE) to the Device-Under-Test (DUT) includes long traces of wires. At frequencies above a few gigahertz, testing integrated circuits becomes a challenging task. The effects on transmission lines become critical requiring impedance matching to minimize signal reflection. AC resistance due to the skin effect and electromagnetic coupling caused by radiation can also become important factors affecting the test results. In the design of a Device Interface Board (DIB), the greater the physical separation of the DUT and the ATE pin electronics, the greater the distortion and signal degradation. In this work, a new Test Interface Module (TIM) based on MEMS technology is proposed to reduce the distance between the tester and device-under-test by orders of magnitude. The proposed solution increases the bandwidth of test channels and reduces the undesired effects of transmission lines on the test results. The MEMS test interface includes a fixed socket and a removable socket. The removable socket incorporates MEMS contact springs to provide temporary with the DUT pads and the fixed socket contains a bed of micro-pins to establish electrical connections with the ATE pin electronics. The MEMS based contact springs have been modified to implement a high-density wafer level test probes for Through Silicon Vias (TSVs) in three dimensional integrated circuits (3D-IC). Prototypes have been fabricated using Silicon On Insulator SOI wafer. Experimental results indicate that the proposed architectures can operate up to 50 GHz without much loss or distortion. The MEMS probes can also maintain a good elastic performance without any damage or deformation in the test phase

    Symbolic tolerance and sensitivity analysis of large scale electronic circuits

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    Available from British Library Document Supply Centre-DSC:DXN029693 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

    System-level design and RF front-end implementation for a 3-10ghz multiband-ofdm ultrawideband receiver and built-in testing techniques for analog and rf integrated circuits

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    This work consists of two main parts: a) Design of a 3-10GHz UltraWideBand (UWB) Receiver and b) Built-In Testing Techniques (BIT) for Analog and RF circuits. The MultiBand OFDM (MB-OFDM) proposal for UWB communications has received significant attention for the implementation of very high data rate (up to 480Mb/s) wireless devices. A wideband LNA with a tunable notch filter, a downconversion quadrature mixer, and the overall radio system-level design are proposed for an 11-band 3.4-10.3GHz direct conversion receiver for MB-OFDM UWB implemented in a 0.25mm BiCMOS process. The packaged IC includes an RF front-end with interference rejection at 5.25GHz, a frequency synthesizer generating 11 carrier tones in quadrature with fast hopping, and a linear phase baseband section with 42dB of gain programmability. The receiver IC mounted on a FR-4 substrate provides a maximum gain of 67-78dB and NF of 5-10dB across all bands while consuming 114mA from a 2.5V supply. Two BIT techniques for analog and RF circuits are developed. The goal is to reduce the test cost by reducing the use of analog instrumentation. An integrated frequency response characterization system with a digital interface is proposed to test the magnitude and phase responses at different nodes of an analog circuit. A complete prototype in CMOS 0.35mm technology employs only 0.3mm2 of area. Its operation is demonstrated by performing frequency response measurements in a range of 1 to 130MHz on 2 analog filters integrated on the same chip. A very compact CMOS RF RMS Detector and a methodology for its use in the built-in measurement of the gain and 1dB compression point of RF circuits are proposed to address the problem of on-chip testing at RF frequencies. The proposed device generates a DC voltage proportional to the RMS voltage amplitude of an RF signal. A design in CMOS 0.35mm technology presents and input capacitance <15fF and occupies and area of 0.03mm2. The application of these two techniques in combination with a loop-back test architecture significantly enhances the testability of a wireless transceiver system

    34th Midwest Symposium on Circuits and Systems-Final Program

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    Organized by the Naval Postgraduate School Monterey California. Cosponsored by the IEEE Circuits and Systems Society. Symposium Organizing Committee: General Chairman-Sherif Michael, Technical Program-Roberto Cristi, Publications-Michael Soderstrand, Special Sessions- Charles W. Therrien, Publicity: Jeffrey Burl, Finance: Ralph Hippenstiel, and Local Arrangements: Barbara Cristi
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