Acceleration of Seed Ordering and Selection for High Quality Delay Test

Seed ordering and selection is a key technique to provide high-test quality with limited resources in Built-In Self Test (BIST) environment. We present a hard-to-detect delay fault selection method to accelerate the computation time in seed ordering and selection processes. This selection method can be used to restrict faults for test generation executed in an early stage in seed ordering and selection processes, and reduce a test pattern count and therefore a computation time. We evaluate the impact of the selection method both in deterministic BIST, where one test pattern is decoded from one seed, and mixed-mode BIST, where one seed is expanded to two or more patterns. The statistical delay quality level (SDQL) is adopted as test quality measure, to represent ability to detect small delay defects (SDDs). Experimental results show that our proposed method can significantly reduce computation time from 28% to 63% and base set seed counts from 21% to 67% while slightly sacrificing test quality

Innovative Techniques for Testing and Diagnosing SoCs

We rely upon the continued functioning of many electronic devices for our everyday welfare, usually embedding integrated circuits that are becoming even cheaper and smaller with improved features. Nowadays, microelectronics can integrate a working computer with CPU, memories, and even GPUs on a single die, namely System-On-Chip (SoC). SoCs are also employed on automotive safety-critical applications, but need to be tested thoroughly to comply with reliability standards, in particular the ISO26262 functional safety for road vehicles. The goal of this PhD. thesis is to improve SoC reliability by proposing innovative techniques for testing and diagnosing its internal modules: CPUs, memories, peripherals, and GPUs. The proposed approaches in the sequence appearing in this thesis are described as follows: 1. Embedded Memory Diagnosis: Memories are dense and complex circuits which are susceptible to design and manufacturing errors. Hence, it is important to understand the fault occurrence in the memory array. In practice, the logical and physical array representation differs due to an optimized design which adds enhancements to the device, namely scrambling. This part proposes an accurate memory diagnosis by showing the efforts of a software tool able to analyze test results, unscramble the memory array, map failing syndromes to cell locations, elaborate cumulative analysis, and elaborate a final fault model hypothesis. Several SRAM memory failing syndromes were analyzed as case studies gathered on an industrial automotive 32-bit SoC developed by STMicroelectronics. The tool displayed defects virtually, and results were confirmed by real photos taken from a microscope. 2. Functional Test Pattern Generation: The key for a successful test is the pattern applied to the device. They can be structural or functional; the former usually benefits from embedded test modules targeting manufacturing errors and is only effective before shipping the component to the client. The latter, on the other hand, can be applied during mission minimally impacting on performance but is penalized due to high generation time. However, functional test patterns may benefit for having different goals in functional mission mode. Part III of this PhD thesis proposes three different functional test pattern generation methods for CPU cores embedded in SoCs, targeting different test purposes, described as follows: a. Functional Stress Patterns: Are suitable for optimizing functional stress during I Operational-life Tests and Burn-in Screening for an optimal device reliability characterization b. Functional Power Hungry Patterns: Are suitable for determining functional peak power for strictly limiting the power of structural patterns during manufacturing tests, thus reducing premature device over-kill while delivering high test coverage c. Software-Based Self-Test Patterns: Combines the potentiality of structural patterns with functional ones, allowing its execution periodically during mission. In addition, an external hardware communicating with a devised SBST was proposed. It helps increasing in 3% the fault coverage by testing critical Hardly Functionally Testable Faults not covered by conventional SBST patterns. An automatic functional test pattern generation exploiting an evolutionary algorithm maximizing metrics related to stress, power, and fault coverage was employed in the above-mentioned approaches to quickly generate the desired patterns. The approaches were evaluated on two industrial cases developed by STMicroelectronics; 8051-based and a 32-bit Power Architecture SoCs. Results show that generation time was reduced upto 75% in comparison to older methodologies while increasing significantly the desired metrics. 3. Fault Injection in GPGPU: Fault injection mechanisms in semiconductor devices are suitable for generating structural patterns, testing and activating mitigation techniques, and validating robust hardware and software applications. GPGPUs are known for fast parallel computation used in high performance computing and advanced driver assistance where reliability is the key point. Moreover, GPGPU manufacturers do not provide design description code due to content secrecy. Therefore, commercial fault injectors using the GPGPU model is unfeasible, making radiation tests the only resource available, but are costly. In the last part of this thesis, we propose a software implemented fault injector able to inject bit-flip in memory elements of a real GPGPU. It exploits a software debugger tool and combines the C-CUDA grammar to wisely determine fault spots and apply bit-flip operations in program variables. The goal is to validate robust parallel algorithms by studying fault propagation or activating redundancy mechanisms they possibly embed. The effectiveness of the tool was evaluated on two robust applications: redundant parallel matrix multiplication and floating point Fast Fourier Transform

Fault-Independent Test-Generation for Software-Based Self-Testing

Software-based self-test (SBST) is being widely used in both manufacturing and in-the-field testing of processor-based devices and Systems-on-Chips. Unfortunately, the stuck-at fault model is increasingly inadequate to match the new and different types of defects in the most recent semiconductor technologies, while the explicit and separate targeting of every fault model in SBST is cumbersome due to the high complexity of the test-generation process, the lack of automation tools, and the high CPU-intensity of the fault-simulation process. Moreover, defects in advanced semiconductor technologies are not always covered by the most commonly used fault-models, and the probability of defect-escapes increases even more. To overcome these shortcomings we propose the first fault-independent SBST method. The proposed method is almost fully automated, it offers high coverage of non-modeled faults by means of a novel SBST-oriented probabilistic metric, and it is very fast as it omits the time-consuming test-generation/fault-simulation processes. Extensive experiments on the OpenRISC OR1200 processor show the advantages of the proposed method

Fault-Independent Test-Generation for Software-Based Self-Testing

Software-based self-test (SBST) is being widely used in both manufacturing and in-the-field testing of processor-based devices and Systems-on-Chips. Unfortunately, the stuck-at fault model is increasingly inadequate to match the new and different types of defects in the most recent semiconductor technologies, while the explicit and separate targeting of every fault model in SBST is cumbersome due to the high complexity of the test-generation process, the lack of automation tools, and the high CPU-intensity of the fault-simulation process. Moreover, defects in advanced semiconductor technologies are not always covered by the most commonly used fault-models, and the probability of defect-escapes increases even more. To overcome these shortcomings we propose the first fault-independent SBST method. The proposed method is almost fully automated, it offers high coverage of non-modeled faults by means of a novel SBST-oriented probabilistic metric, and it is very fast as it omits the time-consuming test-generation/fault-simulation processes. Extensive experiments on the OpenRISC OR1200 processor show the advantages of the proposed method

Fault-Independent Test-Generation for Software-Based Self-Testing

Software-based self-test (SBST) is being widely used in both manufacturing and in-the-field testing of processor-based devices and Systems-on-Chips. Unfortunately, the stuck-at fault model is increasingly inadequate to match the new and different types of defects in the most recent semiconductor technologies, while the explicit and separate targeting of every fault model in SBST is cumbersome due to the high complexity of the test-generation process, the lack of automation tools, and the high CPU-intensity of the fault-simulation process. Moreover, defects in advanced semiconductor technologies are not always covered by the most commonly used fault-models, and the probability of defect-escapes increases even more. To overcome these shortcomings we propose the first fault-independent method for generating software-based self-test procedures. The proposed method is almost fully automated, it offers high coverage of non- modeled faults by means of a novel SBST-oriented probabilistic metric, and it is very fast as it omits the time-consuming test- generation/fault-simulation processes. Extensive experiments on the OpenRISC OR1200 processor show the advantages of the proposed method

Optimizing Test Pattern Generation Using Top-Off ATPG Methodology for Stuck–AT, Transition and Small Delay Defect Faults

The ever increasing complexity and size of digital circuits complemented by Deep Sub Micron (DSM) technology trends today pose challenges to the efficient Design For Test (DFT) methodologies. Innovation is required not only in designing the digital circuits, but also in automatic test pattern generation (ATPG) to ensure that the pattern set screens all the targeted faults while still complying with the Automatic Test Equipment (ATE) memory constraints. DSM technology trends push the requirements of ATPG to not only include the conventional static defects but also to include test patterns for dynamic defects. The current industry practices consider test pattern generation for transition faults to screen dynamic defects. It has been observed that just screening for transition faults alone is not sufficient in light of the continuing DSM technology trends. Shrinking technology nodes have pushed DFT engineers to include Small Delay Defect (SDD) test patterns in the production flow. The current industry standard ATPG tools are evolving and SDD ATPG is not the most economical option in terms of both test generation CPU time and pattern volume. New techniques must be explored in order to ensure that a quality test pattern set can be generated which includes patterns for stuck-at, transition and SDD faults, all the while ensuring that the pattern volume remains economical. This thesis explores the use of a “Top-Off” ATPG methodology to generate an optimal test pattern set which can effectively screen the required fault models while containing the pattern volume within a reasonable limit

Evaluation of hemifield sector analysis protocol in multifocal visual evoked potential (MFVEP) objective perimetry for the diagnosis and early detection of glaucomatous field defects

Visual field assessment is a core component of glaucoma diagnosis and monitoring, and the Standard Automated Perimetry (SAP) test is considered up until this moment, the gold standard of visual field assessment. Although SAP is a subjective assessment and has many pitfalls, it is being constantly used in the diagnosis of visual field loss in glaucoma. Multifocal visual evoked potential (mfVEP) is a newly introduced method used for visual field assessment objectively. Several analysis protocols have been tested to identify early visual field losses in glaucoma patients using the mfVEP technique, some were successful in detection of field defects, which were comparable to the standard SAP visual field assessment, and others were not very informative and needed more adjustment and research work. In this study, we implemented a novel analysis approach and evaluated its validity and whether it could be used effectively for early detection of visual field defects in glaucoma. OBJECTIVES: The purpose of this study is to examine the effectiveness of a new analysis method in the Multi-Focal Visual Evoked Potential (mfVEP) when it is used for the objective assessment of the visual field in glaucoma patients, compared to the gold standard technique. METHODS: 3 groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes) and glaucoma suspect patients (38 eyes). All subjects had a two standard Humphrey visual field HFA test 24-2 and a single mfVEP test undertaken in one session. Analysis of the mfVEP results was done using the new analysis protocol; the Hemifield Sector Analysis HSA protocol. Analysis of the HFA was done using the standard grading system. RESULTS: Analysis of mfVEP results showed that there was a statistically significant difference between the 3 groups in the mean signal to noise ratio SNR (ANOVA p<0.001 with a 95% CI). The difference between superior and inferior hemispheres in all subjects were all statistically significant in the glaucoma patient group 11/11 sectors (t-test p<0.001), partially significant 5/11 (t-test p<0.01) and no statistical difference between most sectors in normal group (only 1/11 was significant) (t-test p<0.9). sensitivity and specificity of the HAS protocol in detecting glaucoma was 97% and 86% respectively, while for glaucoma suspect were 89% and 79%. DISCUSSION: The results showed that the new analysis protocol was able to confirm already existing field defects detected by standard HFA, was able to differentiate between the 3 study groups with a clear distinction between normal and patients with suspected glaucoma; however the distinction between normal and glaucoma patients was especially clear and significant. CONCLUSION: The new HSA protocol used in the mfVEP testing can be used to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patient. Using this protocol can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. Sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucoma field loss

AN INTELLIGENT SYSTEM FOR THE DEFECT INSPECTION OF SPECULAR PAINTED CERAMIC TILES

Product visual inspection is still performed manually or semi automatically in most industries from simple ceramic tile grading to complicated automotive body panel paint defect and surface quality inspection. Moreover, specular surfaces present additional challenges to conventional vision systems due to specular reflections, which may mask the true location of objects and lead to incorrect measurements. Some sophisticated optical inspection methods have already been developed for high precision surface defect inspection in recent years. Unfortunately, most of them are highly computational. Systems built on those methods are either inapplicable or costly to achieve real-time inspection. This thesis describes an integrated low-cost intelligent system developed to automatically capture and extract regular defects of the ceramic tiles with uniformly colored specular coatings. The proposed system is implemented on a group of smart cameras using its on-board processing ability to achieve real-time inspection. The results of this study will be used to facilitate the design of a robust, low-cost, closed-loop inspection system for a class of products with smooth specular coatings. The experimental results on real test panels demonstrate the effectiveness and robustness of proposed system

Efficient verification/testing of system-on-chip through fault grading and analog behavioral modeling

textThis dissertation presents several cost-effective production test solutions using fault grading and mixed-signal design verification cases enabled by analog behavioral modeling. Although the latest System-on-Chip (SOC) is getting denser, faster, and more complex, the manufacturing technology is dominated by subtle defects that are introduced by small-scale technology. Thus, SOC requires more mature testing strategies. By performing various types of testing, better quality SoC can be manufactured, but test resources are too limited to accommodate all those tests. To create the most efficient production test flow, any redundant or ineffective tests need to be removed or minimized. Chapter 3 proposes new method of test data volume reduction by combining the nonlinear property of feedback shift register (FSR) and dictionary coding. Instead of using the nonlinear FSR for actual hardware implementation, the expanded test set by nonlinear expansion is used as the one-column test sets and provides big reduction ratio for the test data volume. The experimental results show the combined method reduced the total test data volume and increased the fault coverage. Due to the increased number of test patterns, total test time is increased. Chapter 4 addresses a whole process of functional fault grading. Fault grading has always been a ”desire-to-have” flow because it can bring up significant value for cost saving and yield analysis. However, it is very hard to perform the fault grading on the complex large scale SOC. A commercial tool called Z01X is used as a fault grading platform, and whole fault grading process is coordinated and each detailed execution is performed. Simulation- based functional fault grading identifies the quality of the given functional tests against the static faults and transition delay faults. With the structural tests and functional tests, functional fault grading can indicate the way to achieve the same test coverage by spending minimal test time. Compared to the consumed time and resource for fault grading, the contribution to the test time saving might not be acceptable as very promising, but the fault grading data can be reused for yield analysis and test flow optimization. For the final production testing, confident decisions on the functional test selection can be made based on the fault grading results. Chapter 5 addresses the challenges of Package-on-Package (POP) testing. Because POP devices have pins on both the top and the bottom of the package, the increased test pins require more test channels to detect packaging defects. Boundary scan chain testing is used to detect those continuity defects by relying on leakage current from the power supply. This proposed test scheme does not require direct test channels on the top pins. Based on the counting algorithm, minimal numbers of test cycles are generated, and the test achieved full test coverage for any combinations of pin-to-pin shortage defects on the top pins of the POP package. The experimental results show about 10 times increased leakage current from the shorted defect. Also, it can be expanded to multi-site testing with less test channels for high-volume production. Fault grading is applied within different structural test categories in Chapter 6. Stuck-at faults can be considered as TDFs having infinite delay. Hence, the TDF Automatic Test Pattern Generation (ATPG) tests can detect both TDFs and stuck-at faults. By removing the stuck-at faults being detected by the given TDF ATPG tests, the tests that target stuck-at faults can be reduced, and the reduced stuck-at fault set results in fewer stuck-at ATPG patterns. The structural test time is reduced while keeping the same test coverage. This TDF grading is performed with the same ATPG tool used to generate the stuck-at and TDF ATPG tests. To expedite the mixed-signal design verification of complex SoC, analog behavioral modeling methods and strategies are addressed in Chapter 7 and case studies for detailed verification with actual mixed-signal design are ad- dressed in Chapter 8. Analog modeling effort can enhance verification quality for a mixed-signal design with less turnaround time, and it enables compatible integration of the mixed-signal design cores into the SoC. The modeling process may reveal any potential design errors or incorrect testbench setup, and it results in minimizing unnecessary debugging time for quality devices. Two mixed-signal design cases were verified by me using the analog models. A fully hierarchical digital-to-analog converter (DAC) model is implemented and silicon mismatches caused by process variation are modeled and inserted into the DAC model, and the calibration algorithm for the DAC is successfully verified by model-based simulation at the full DAC-level. When the mismatch amount is increased and exceeded the calibration capability of the DAC, the simulation results show the increased calibration error with some outliers. This verification method can identify the saturation range of the DAC and predict the yield of the devices from process variation. A phase-locked loop (PLL) design cases were also verified by me using the analog model. Both open-loop PLL model and closed-loop PLL model cases are presented. Quick bring-up of open-loop PLL model provides low simulation overhead for widely-used PLLs in the SOC and enables early starting of design verification for the upper-level design using the PLL generated clocks. Accurate closed-loop PLL model is implemented for DCO-based PLL design, and the mixed-simulation with analog models and schematic designs enables flexible analog verification. Only focused analog design block is set to the schematic design and the rest of the analog design is replaced by the analog model. Then, this scaled-down SPICE simulation is performed about 10 times to 100 times faster than full-scale SPICE simulation. The analog model of the focused block is compared with the scaled-down SPICE simulation result and the quality of the model is iteratively enhanced. Hence, the analog model enables both compatible integration and flexible analog design verification. This dissertation contributes to reduce test time and to enhance test quality, and helps to set up efficient production testing flows. Depending on the size and performance of CUT, proper testing schemes can maximize the efficiency of production testing. The topics covered in this dissertation can be used in optimizing the test flow and selecting the final production tests to achieve maximum test capability. In addition, the strategies and benefits of analog behavioral modeling techniques that I implemented are presented, and actual verification cases shows the effectiveness of analog modeling for better quality SoC products.Electrical and Computer Engineerin