Built-In Self-Test (BIST) Methods for MEMS: A Review

Hantos, Gergely; Flynn, David; Desmulliez, Marc Phillipe Yves

doi:10.3390/mi12010040

Cited by 17 publications

(12 citation statements)

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“…To tackle possibly all types of defects in the memory in this research, we proposed a March-sift algorithm that successfully detects almost all types of faults, such as SAF, TF, ADF, CFs, NPSFs, WDFs, RDFs, and DRDFs, from memory under test. The BIST approaches in the research [ 10 , 15 ] are also presented in the context of self-testing. Comparative results indicate that the proposed approach is better in fault coverage with a minimum area overhead.…”

Section: Discussionmentioning

confidence: 99%

“…Memory test and repair are two separate processes involved in yield enhancement for any modern SoC design semiconductor memories. Memory built-in self-test (MBIST) is a verified and reliable method for testing embedded memory [ 7 , 8 , 9 , 10 ], whereby memories are tested for fault and the fault types using sophisticated March algorithms. The MBIST controller usually works on test algorithms for finding defects and their types in embedded memories [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Method for Test and Repair Memories Using Redundancy Mechanism for SoC

Alnatheer

Ahmed

2021

Micromachines

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The current system-on-chip (SoC)-based devices uses embedded memories of enormous size. Most of these systems’ area is dense with memories and promotes different types of faults appearance in memory. The memory faults become a severe issue when they affect the yield of the product. A memory-test and -repair scheme is an attractive solution to tackle this kind of problem. The built-in self-repair (BISR) scheme is a prominent method to handle this issue. The BISR scheme is widely used to repair the defective memories for an SoC-based system. It uses a built-in redundancy analysis (BIRA) circuit to allocate the redundancy when defects appear in the memory. The data are accessed from the redundancy allocation when the faulty memory is operative. Thus, this BIRA scheme affects the area overhead for the BISR circuit when it integrates to the SoC. The spare row and spare column–based BISR method is proposed to receive the optimal repair rate with a low area overhead. It tests the memories for almost all the fault types and repairs the memory by using spare rows and columns. The proposed BISR block’s performance was measured for the optimal repair rate and the area overhead. The area overhead, timing, and repair rate were compared with the other approaches. Furthermore, the study noticed that the repair rate and area overhead would increase by increasing the spare-row/column allocation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Method for Test and Repair Memories Using Redundancy Mechanism for SoC

Alnatheer

Ahmed

2021

Micromachines

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“…Our methods are suitable for deployment both in laboratory conditions during the manufacturing or product return stages, or during device operation, making them ideal candidates as BIST methods. While other BIST solutions, that rely on the electrostatic actuation of the sensing element [8], are mainly transducer specific, our methods allow also backwards compatibility as they are software based with the only information required being the acoustic data coming from the MEMS microphone itself. The lumped element model is introduced in section II along with a detailed explanation of the failure mode simulation.…”

Section: Introductionmentioning

confidence: 99%

On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

Hantos

Simon

Desmulliez

2022

IEEE Trans. Compon., Packag. Manufact. Technol.

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Most mobile phones today have capacitive microelectromechanical systems (MEMS) microphones that use either single or dual diaphragm. Methods to detect failures easily and non-invasively have become of critical importance for microphones mobile phone manufacturers as a basis for built-in self-test (BIST) and self-repair (BISR) strategies. In that regard, a four-layer framework is presented that includes lumped element modelling (LEM), failure mode simulation, failure mode discrimination and recovery. The frequency response of the microphone is taken as the main output to analyse. To experimentally validate this framework, this article provides a failure mode induction method based on bias voltage sweeping and four new techniques, based solely on acoustic measurements to discriminate the states of electrostatic capture for single diaphragm capacitive MEMS microphones. These include a) analysis of an acoustic signature that is unique to electrostatic capture based on cosine similarity analysis, b) -3 dB point measurement, C) +3 dB point measurement, and d) cluster analysis. Measurement of pull-in voltage and snapback voltage ranges is further demonstrated based on sensitivity measurements in laboratory conditions and response magnitude and noise power measurements in non-laboratory conditions. Up to 100% success rate in detecting electrostatic capture of diaphragm is reported for this type of device.

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“…Unlike isotropic materials, the lamination architecture of the composite facilitates the embedment of the sensor within the structure and aids in risk reduction, wherein the suite of inbuilt sensors may be tested and characterised prior to asset installation [15]. These embedded sensors can suffer from drift and failure events over their lifetime and data transmitted from such sensors can wrongly be inferred as an "event"-a precursor to a failure [16]. Challenges relating to the effective implementation of prognostic and health monitoring (PHM) systems are also associated with the need for expert elicitation of the data, the complex data analysis algorithm, and scalability of such algorithms, for example, adapting data to intrinsic variances in materials used on the structural assets [17].…”

Section: Introductionmentioning

confidence: 99%

A Review of Sensing Technologies for Non-Destructive Evaluation of Structural Composite Materials

et al. 2021

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The growing demand and diversity in the application of industrial composites and the current inability of present non-destructive evaluation (NDE) methods to perform detailed inspection of these composites has motivated this comprehensive review of sensing technologies. NDE has the potential to be a versatile tool for maintaining composite structures deployed in hazardous and inaccessible areas, such as offshore wind farms and nuclear power plants. Therefore, the future composite solutions need to take into consideration the niche requirements of these high-value/critical applications. Composite materials are intrinsically complex due to their anisotropic and non-homogeneous characteristics. This presents a significant challenge for evaluation and the associated data analysis for NDEs. For example, the quality assurance, certification of composite structures, and early detection of the failure is complex due to the variability and tolerances involved in the composite manufacturing. Adapting existing NDE methods to detect and locate the defects at multiple length scales in the complex materials represents a significant challenge, resulting in a delayed and incorrect diagnosis of the structural health. This paper presents a comprehensive review of the NDE techniques, that includes a detailed discussion of their working principles, setup, advantages, limitations, and usage level for the structural composites. A comparison between these techniques is also presented, providing an insight into the future trends for composites’ prognostic and health management (PHM). Current research trends show the emergence of the non-contact-type NDE (including digital image correlation, infrared tomography, as well as disruptive frequency-modulated continuous wave techniques) for structural composites, and the reasons for their choice over the most popular contact-type (ultrasonic, acoustic, and piezoelectric testing) NDE methods is also discussed. The analysis of this new sensing modality for composites’ is presented within the context of the state-of-the-art and projected future requirements.

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Built-In Self-Test (BIST) Methods for MEMS: A Review

Cited by 17 publications

References 84 publications

Optimal Method for Test and Repair Memories Using Redundancy Mechanism for SoC

Optimal Method for Test and Repair Memories Using Redundancy Mechanism for SoC

On the Use of Acoustic Methods for the Detection of Electrostatic Capture of Diaphragm in Capacitive MEMS Microphones

A Review of Sensing Technologies for Non-Destructive Evaluation of Structural Composite Materials

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