Design for Board and System Level Structural Test and Diagnosis

Vo, Toai; Wang, Zhiyuan; Eaton, Tam; Ghosh, P.S.; Li, Huai; Lee, Young; Wang, Weili; Fang, Rong; Singletary, D.; Gu, Xinli

doi:10.1109/test.2006.297631

Cited by 34 publications

(29 citation statements)

References 5 publications

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“…Even if the correct root cause is eventually identified, the process can take technicians up to several weeks to collect all the syndromes before successful diagnosis. Currently used diagnostic software is not able to accurately and rapidly locate the root cause in reasonable time [2]. In addition, the development of diagnostic software is becoming increasingly difficult as electronic systems become more complex and failures become more subtle.…”

Section: Problem Statement and Paper Contributionsmentioning

confidence: 99%

“…Current systems consist of a large number of ASICs, memory devices, and passive components, as well as hundreds of I/Os. The operating frequencies of highspeed chips on a board can be in the range of several GHz, and high-speed I/O rates are also in the GHz range [2]. Due to the prevalence of high-density and high-frequency designs in current boards, defects-per-million rates continue to increase and subtle functional failures are becoming increasingly difficult to detect and diagnose for root-cause identification [3], [4].…”

Section: Introductionmentioning

confidence: 99%

“…However, traditional structural test techniques are not sufficient to guarantee product quality. Some defects are not detected until functional tests are carried out on the board [2], [6], [7]. * The work of F. Ye and K. Chakrabarty at Duke University was supported by a grant from Huawei Technologies Co. Ltd.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Board-Level Functional Fault Diagnosis Using Decision Trees

Zhang

Chakrabarty

et al. 2012

2012 IEEE 21st Asian Test Symposium

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Functional fault diagnosis at board-level is desirable for high-volume production since it improves product yield. However, to ensure diagnosis accuracy and effective board repair, a large number of syndromes must be used. Therefore, the diagnosis cost can be prohibitively high due to the increase in diagnosis time and the complexity of syndrome collection/analysis. We propose an adaptive diagnosis method based on decision trees (DTs). Faulty components are classified according to the discriminative ability of the syndromes in DT training. The diagnosis procedure is constructed as a binary tree, with the most discriminative syndrome as the root and final repair suggestions are available as the leaf nodes of the tree. The syndrome to be collected in the next step is determined based on the observations of syndromes collected thus far in the diagnosis procedure. The number of syndromes required for diagnosis can also be significantly reduced compared to the number of syndromes used for system training. Diagnosis results for two complex boards from industry, currently in volume production, and additional synthetic data highlight the effectiveness of the proposed approach.

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Section: Problem Statement and Paper Contributionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Board-Level Functional Fault Diagnosis Using Decision Trees

Zhang

Chakrabarty

et al. 2012

2012 IEEE 21st Asian Test Symposium

Self Cite

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“…However, test and diagnosis are more complex at board-level when functional test is applied. Moreover, external memory, noise, power-supply variations, and clock skew on a board test aggravate the problem of board-level diagnosis [6].…”

Section: Introductionmentioning

confidence: 99%

Mimicking of Functional State Space with Structural Tests for the Diagnosis of Board-Level Functional Failures

Fang

Wang

et al. 2010

2010 19th IEEE Asian Test Symposium

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A common scenario in industry today is "No Trouble Found" (NTF) due to functional failures. A component on a board fails during board-level functional test, but it passes the Automatic Test Equipment (ATE) test when it is returned to the supplier for warranty replacement or service repair. To find the root cause of NTF, we define an innovative deterministic test, namely functional scan test. We also propose two approaches for using functional scan test to adequately mimic functional state space. The first approach allows us to select a given number of initial states in linear time and functional scan tests resulting from these selected states are used to mimic the functional state space effectively. The second approach adopts a state-injection technique. Experiments on an industry design show that by using either multiple initial states or state injection, functional scan test with appropriate functional constraints can mimic the functional state space well, measured by appropriate coverage metrics. Therefore, it is feasible to use functional scan test to detect board-level functional failures in a controlled deterministic environment and diagnose the root cause to faulty wires/gates inside a component. It is also shown that the proposed method outperforms a random method in selecting the given number of effective initial states.

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“…However, the diagnosis of functional failures is challenging and timeconsuming due to the following reasons [4]. First, functional test typically includes hundreds of thousands to millions of cycles.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Selection of Diagnosis-Oriented Fault-Insertion Points for System Test

Zhang

Wang

et al. 2010

2010 19th IEEE Asian Test Symposium

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Hardware fault-insertion test is a promising method to diagnose functional failures and target "no trouble found (NTF)" problems in electronic systems. However, it is costly and impractical to equip all the potential fault sites with fault-insertion hardware. We present an optimization method to select the most effective outputs of a module where fault insertion logic must be placed to facilitate diagnosis. Faults inserted at the selected outputs are able to generate fault syndromes that are most similar to the errors produced by defects inside the module. This approach also ensures that the ambiguous fault candidates from other modules are maximally removed from the set of suspects. A fault syndrome is defined by the order of error occurrence at the observation points, and it is referred as an error flow. The similarity between two error flows is measured by the metric of edit distance. An integer linear programming model is used to maximize diagnostic effectiveness with a small number of fault-insertion points. Results on diagnostic accuracy for an opensource RISC highlight the effectiveness of the proposed method compared to a baseline random fault-insertion scheme.

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Design for Board and System Level Structural Test and Diagnosis

Cited by 34 publications

References 5 publications

Adaptive Board-Level Functional Fault Diagnosis Using Decision Trees

Adaptive Board-Level Functional Fault Diagnosis Using Decision Trees

Mimicking of Functional State Space with Structural Tests for the Diagnosis of Board-Level Functional Failures

Optimization and Selection of Diagnosis-Oriented Fault-Insertion Points for System Test

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