A design for testability study on a high performance automatic gain control circuit.

A comprehensive testability study on a commercial automatic gain control circuit is presented which aims to identify design for testability (DfT) modifications to both reduce production test cost and improve test quality. A fault simulation strategy based on layout extracted faults has been used to support the study. The paper proposes a number of DfT modifications at the layout, schematic and system levels together with testability. Guidelines that may well have generic applicability. Proposals for using the modifications to achieve partial self test are made and estimates of achieved fault coverage and quality levels presente

Two improved methods for testing ADC parametric faults by digital input signals

In this paper, two improved methods are presented extending our previous work. The first one improves the results by adjusting the voltage levels of the input pulse wave stimulus. Compared with the sine wave input stimulus, the four-level pulse wave can detect even more faulty cases with the offset faults. The second one improves the results by calculating the similarity of the output spectra between the golden devices and the DUTs. Compared with the previous method [10], it is less sensitive to the jitter and the change of the rise/fall time of the input pulse wave stimulus. In these two methods, a number of golden devices are tested at first to obtain the fault-free range. At last, a signature result is obtained from both methods. It can filter out the faulty devices in a quick way before testing the specific values of the conventional dynamic and static parameters

Analog Defect Injection and Fault Simulation Techniques: A Systematic Literature Review

Since the last century, the exponential growth of the semiconductor industry has led to the creation of tiny and complex integrated circuits, e.g., sensors, actuators, and smart power. Innovative techniques are needed to ensure the correct functionality of analog devices that are ubiquitous in every smart system. The ISO 26262 standard for functional safety in the automotive context specifies that fault injection is necessary to validate all electronic devices. For decades, standardization of defect modeling and injection mainly focused on digital circuits and, in a minor part, on analog ones. An initial attempt is being made with the IEEE P2427 draft standard that started to give a structured and formal organization to the analog testing field. Various methods have been proposed in the literature to speed up the fault simulation of the defect universe for an analog circuit. A more limited number of papers seek to reduce the overall simulation time by reducing the number of defects to be simulated. This literature survey describes the state-of-the-art of analog defect injection and fault simulation methods. The survey is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodological flow, allowing for a systematic and complete literature survey. Each selected paper has been categorized and presented to provide an overview of all the available approaches. In addition, the limitations of the various approaches are discussed by showing possible future directions

Construction of an Expert System Based on Fuzzy Logic for Diagnosis of Analog Electronic Circuits

The paper presents construction of the fuzzy logic system to analog circuits soft fault diagnosis. The classical dictionary construction is replaced by fuzzy rule system. The first part refers to analog fault diagnosis, its techniques, approaches and goals. It clarifies common strategy and define differences between detecting, locating and identifying a fault in analog electronic circuit. The second part is focused on a creation of fuzzy rule expert system with use of sensitivity functions and known circuit topology. To detect, locate and identify a faulty element in a circuit the sensitivity matrix is used. The advantage of the method is its utilization in all, AC, DC and time domain. The fuzzy system, like the classical fault dictionary, can detect and locate single catastrophic faults and, on the contrary to the classical one, it also detects and locates parametric faults. Moreover, it allows identification of these faults, such that sign of the faulty parameter deviation is designated. The method has deterministic character as well as  it can be applied on the verification and production stage

Design and debugging of multi-step analog to digital converters

With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

Moving Towards Analog Functional Safety

Over the past century, the exponential growth of the semiconductor industry has led to the creation of tiny and complex integrated circuits, e.g., sensors, actuators, and smart power systems. Innovative techniques are needed to ensure the correct functionality of analog devices that are ubiquitous in every smart system. The standard ISO 26262 related to functional safety in the automotive context specifies that fault injection is necessary to validate all electronic devices. For decades, standardizing fault modeling, injection and simulation mainly focused on digital circuits and disregarding analog ones. An initial attempt is being made with the IEEE P2427 standard draft standard that started to give this field a structured and formal organization. In this context, new fault models, injection, and abstraction methodologies for analog circuits are proposed in this thesis to enhance this application field. The faults proposed by the IEEE P2427 standard draft standard are initially evaluated to understand the associated fault behaviors during the simulation. Moreover, a novel approach is presented for modeling realistic stuck-on/off defects based on oxide defects. These new defects proposed are required because digital stuck-at-fault models where a transistor is frozen in on-state or offstate may not apply well on analog circuits because even a slight variation could create deviations of several magnitudes. Then, for validating the proposed defects models, a novel predictive fault grouping based on faulty AC matrices is applied to group faults with equivalent behaviors. The proposed fault grouping method is computationally cheap because it avoids performing DC or transient simulations with faults injected and limits itself to faulty AC simulations. Using AC simulations results in two different methods that allow grouping faults with the same frequency response are presented. The first method is an AC-based grouping method that exploits the potentialities of the S-parameters ports. While the second is a Circle-based grouping based on the circle-fitting method applied to the extracted AC matrices. Finally, an open-source framework is presented for the fault injection and manipulation perspective. This framework relies on the shared semantics for reading, writing, or manipulating transistor-level designs. The ultimate goal of the framework is: reading an input design written in a specific syntax and then allowing to write the same design in another syntax. As a use case for the proposed framework, a process of analog fault injection is discussed. This activity requires adding, removing, or replacing nodes, components, or even entire sub-circuits. The framework is entirely written in C++, and its APIs are also interfaced with Python. The entire framework is open-source and available on GitHub. The last part of the thesis presents abstraction methodologies that can abstract transistor level models into Verilog-AMS models and Verilog- AMS piecewise and nonlinear models into C++. These abstracted models can be integrated into heterogeneous systems. The purpose of integration is the simulation of heterogeneous components embedded in a Virtual Platforms (VP) needs to be fast and accurate

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

Fault-based Analysis of Industrial Cyber-Physical Systems

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

Power supply current [IPS] based testing of CMOS amplifier circuit with and without floating gate input transistors

This work presents a case study, which attempts to improve the fault diagnosis and testability of the power supply current based testing methodology applied to a typical two-stage CMOS operational amplifier and is extended to operational amplifier with floating gate input transistors*. The proposed test method takes the advantage of good fault coverage through the use of a simple power supply current measurement based test technique, which only needs an ac input stimulus at the input and no additional circuitry. The faults simulating possible manufacturing defects have been introduced using the fault injection transistors. In the present work, variations of ac ripple in the power supply current IPS, passing through VDD under the application of an ac input stimulus is measured to detect injected faults in the CMOS amplifier. The effect of parametric variation is taken into consideration by setting tolerance limit of ± 5% on the fault-free IPS value. The fault is identified if the power supply current, IPS falls outside the deviation given by the tolerance limit. This method presented can also be generalized to the test structures of other floating-gate MOS analog and mixed signal integrated circuits

Constraint-driven RF test stimulus generation and built-in test

With the explosive growth in wireless applications, the last decade witnessed an ever-increasing test challenge for radio frequency (RF) circuits. While the design community has pushed the envelope far into the future, by expanding CMOS process to be used with high-frequency wireless devices, test methodology has not advanced at the same pace. Consequently, testing such devices has become a major bottleneck in high-volume production, further driven by the growing need for tighter quality control. RF devices undergo testing during the prototype phase and during high-volume manufacturing (HVM). The benchtop test equipment used throughout prototyping is very precise yet specialized for a subset of functionalities. HVM calls for a different kind of test paradigm that emphasizes throughput and sufficiency, during which the projected performance parameters are measured one by one for each device by automated test equipment (ATE) and compared against defined limits called specifications. The set of tests required for each product differs greatly in terms of the equipment required and the time taken to test individual devices. Together with signal integrity, precision, and repeatability concerns, the initial cost of RF ATE is prohibitively high. As more functionality and protocols are integrated into a single RF device, the required number of specifications to be tested also increases, adding to the overall cost of testing, both in terms of the initial and recurring operating costs. In addition to the cost problem, RF testing proposes another challenge when these components are integrated into package-level system solutions. In systems-on-packages (SOP), the test problems resulting from signal integrity, input/output bandwidth (IO), and limited controllability and observability have initiated a paradigm shift in high-speed analog testing, favoring alternative approaches such as built-in tests (BIT) where the test functionality is brought into the package. This scheme can make use of a low-cost external tester connected through a low-bandwidth link in order to perform demanding response evaluations, as well as make use of the analog-to-digital converters and the digital signal processors available in the package to facilitate testing. Although research on analog built-in test has demonstrated hardware solutions for single specifications, the paradigm shift calls for a rather general approach in which a single methodology can be applied across different devices, and multiple specifications can be verified through a single test hardware unit, minimizing the area overhead. Specification-based alternate test methodology provides a suitable and flexible platform for handling the challenges addressed above. In this thesis, a framework that integrates ATE and system constraints into test stimulus generation and test response extraction is presented for the efficient production testing of high-performance RF devices using specification-based alternate tests. The main components of the presented framework are as follows: Constraint-driven RF alternate test stimulus generation: An automated test stimulus generation algorithm for RF devices that are evaluated by a specification-based alternate test solution is developed. The high-level models of the test signal path define constraints in the search space of the optimized test stimulus. These models are generated in enough detail such that they inherently define limitations of the low-cost ATE and the I/O restrictions of the device under test (DUT), yet they are simple enough that the non-linear optimization problem can be solved empirically in a reasonable amount of time. Feature extractors for BIT: A methodology for the built-in testing of RF devices integrated into SOPs is developed using additional hardware components. These hardware components correlate the high-bandwidth test response to low bandwidth signatures while extracting the test-critical features of the DUT. Supervised learning is used to map these extracted features, which otherwise are too complicated to decipher by plain mathematical analysis, into the specifications under test. Defect-based alternate testing of RF circuits: A methodology for the efficient testing of RF devices with low-cost defect-based alternate tests is developed. The signature of the DUT is probabilistically compared with a class of defect-free device signatures to explore possible corners under acceptable levels of process parameter variations. Such a defect filter applies discrimination rules generated by a supervised classifier and eliminates the need for a library of possible catastrophic defects.Ph.D.Committee Chair: Chatterjee, Abhijit; Committee Member: Durgin, Greg; Committee Member: Keezer, David; Committee Member: Milor, Linda; Committee Member: Sitaraman, Sures