Manufacturing defects can cause hard-to-detect (HTD) faults in fin field-effect transistor (FinFET) static random access memories (SRAMs). Detection of these faults, such as random read outputs and out-of-spec parametric deviations, is essential when testing FinFET SRAMs. Undetected HTD faults result in test escapes, which lead to early in-field failures. This article presents a detailed analysis of HTD faults in FinFET SRAMs by exploring their sensitization and discussing solutions to improve HTD fault coverage during manufacturing testing. We first define the fault space for SRAMs and classify all faults in the space. Following this, we perform a systematic fault analysis based on injecting resistive defects in a memory cell, inspecting its behavior, and identifying HTD faults. Furthermore, we survey existing test solutions and discuss their HTD fault coverage and limitations. Based on our analysis, it is clear that no single test solution can fully detect all HTD faults, thus leading to test escapes. Hence, there is a need for new and more efficient test solutions. Improved detection of HTD faults could be achieved by using parametric test solutions, proposing solutions that cover yet-untargeted HTD faults, combining multiple test approaches into a single solution, and further exploring stress conditions. These new approaches would reduce test escapes and therefore improve the quality of FinFET SRAMs.@en

Hard-to-detect faults such as weak and random faults in FinFET SRAMs represent an important challenge for manufacturing testing in scaled technologies, as they may lead to test escapes. This paper proposes a Design-for-Testability (DFT) scheme able to detect such faults by monitoring the bitline swing of FinFET memories. Using only five operations per cell, we are able to detect defects that cause deterministic, random, and weak faults. Compared to the state of the art, this leads to an improved detection capability at reduced area overhead.@en

Manufacturing defects in FinFET SRAMs can cause hard-to-detect faults such as Undefined State Faults (USFs). Detection of USFs is not trivial, as they may not lead to incorrect functionality. Nevertheless, undetected USFs may have a severe impact on the memory's quality: they can cause random read outputs, which might lead to test escapes and no-trouble-found devices later when the device is already in the field, as well as compromise the circuit's quality by reducing the memory cell's Static Noise Margin (SNM). Therefore, the detection of USF is critical. This paper proposes a test solution to improve the detection of USFs in FinFET SRAMs. To achieve this, we first analyze the impact of USFs on the cell's SNM and bitline swing during read operations. Then, we perform an experimental study of stress conditions' (SCs) impact on sensitizing and detecting USFs. Finally, we propose a dedicated Design-For-Testability (DFT) scheme for FinFET SRAMs to detect such faults. This scheme introduces a small area overhead while significantly improving USF detection. Hence, using the proposed DFT leads to fewer test escapes and higher-quality FinFET SRAMs.@en

Resistive defects in FinFET SRAMs are an important challenge for manufacturing test in submicron technologies, as they may cause dynamic faults, which are hard to detect and therefore may increase the number of test escapes. This paper presents a defect-oriented test that uses On-Chip Current Sensors (OCCSs) to detect weak resistive defects by monitoring the current consumption of FinFET SRAM cells. Using OCCSs, all resistive defects injected in single cells considered in this paper have been detected within a certain accuracy by applying 5 read or write operations only, independent whether they cause static or dynamic faults. The proposed approach has been validated and the detection accuracy has been evaluated. Simulation results show that the approach is even able to detect weak resistive defects that do not sensitize faults at the functional level, thus able to increase the reliability of devices.@en

Resistive Random-Access Memories (ReRAMs) represent a promising candidate to complement and/or replace CMOS-based memories used in several emerging applications. Despite all the advantages of using these novel memories, mainly due to the memristive device's CMOS manufacturing process compatibility, zero standby power consumption, as well as, high scalability and density, the use of them in real applications depends on being able to guarantee their quality after manufacturing. As observed in CMOS-based memories, ReRAMs are also susceptible to manufacturing deviations, defects, and process variations, that can cause faulty behaviors different from the ones observed in CMOS technology, increasing not only the manufacturing test complexity but also the time required to perform the test. In this context, this paper proposes to study the use of temperature to facilitate fault propagation in ReRAMs, reducing the required test time. A case study composed of a 3x3 word-based ReRAM with peripheral circuitry implemented based on a 130 nm Predictive Technology Model (PTM) library was adopted. During the proposed study, a total of 17 defects were injected in different positions of the ReRAM cell, and their respective faulty behavior was classified into traditional and unique faults, considering three temperatures (25, 100, and -40°C). The obtained results show that the temperature can, depending on the position of the defect, facilitate fault propagation, which reduces the time required for performing manufacturing testing.@en