scholarly journals SRAM Bitcell Defect Identification Methodology Using Electrical Failure Analysis Data

2021 ◽  
Author(s):  
Hyungtae Kim ◽  
Geonho Kim ◽  
Yunrong Li ◽  
Jinyong Jeong ◽  
Youngdae Kim
Keyword(s):  
Failure Analysis ◽  
Technology Development ◽  
New Technology ◽  
Random Access ◽  
Analysis Data ◽  
Test Method ◽  
Design For Test ◽  
Defect Identification ◽  
Electrical Failure ◽  
Efficient Test

Abstract Static Random Access Memory (SRAM) has long been used for a new technology development vehicle because it is sensitive to process defects due to its high density and minimum feature size. In addition, failure location can be accurately predicted because of the highly structured architecture. Thus, fast and accurate Failure Analysis (FA) of the SRAM failure is crucial for the success of new technology learning and development. It is often quite time consuming to identify defects through conventional physical failure analysis techniques. In this paper, we present an advanced defect identification methodology for SRAM bitcell failures with fast speed and high accuracy based on the bitcell transistor analog characteristics from special design for test (DFT) features, Direct Bitcell Access (DBA). This technique has the advantage to shorten FA throughput time due to a time efficient test method and an intuitive failure analysis method based on Electrical Failure Analysis (EFA) without destructive analysis. In addition, all the defects in a wafer can be analyzed and improved simultaneously utilizing the proposed defect identification methodology. Some successful case studies are also discussed to demonstrate the efficiency of the proposed defect identification methodology.

SRAM Bitcell Defect Identification Methodology Using Electrical Failure Analysis Data

2020 ◽  
Author(s):  
Hyungtae Kim ◽  
Geonho Kim ◽  
Yunrong Li ◽  
Jinyong Jeong ◽  
Youngdae Kim
Keyword(s):  
Failure Analysis ◽  
Technology Development ◽  
New Technology ◽  
Random Access ◽  
Analysis Data ◽  
Test Method ◽  
Design For Test ◽  
Defect Identification ◽  
Electrical Failure ◽  
Efficient Test

Abstract Static Random Access Memory (SRAM) has long been used for a new technology development vehicle because it is sensitive to process defects due to its high density and minimum feature size. In addition, failure location can be accurately predicted because of the highly structured architecture. Thus, fast and accurate Failure Analysis (FA) of the SRAM failure is crucial for the success of new technology learning and development. It is often quite time consuming to identify defects through conventional physical failure analysis techniques. In this paper, we present an advanced defect identification methodology for SRAM bitcell failures with fast speed and high accuracy based on the bitcell transistor analog characteristics from special design for test (DFT) features, Direct Bitcell Access (DBA). This technique has the advantage to shorten FA throughput time due to a time efficient test method and an intuitive failure analysis method based on Electrical Failure Analysis (EFA) without destructive analysis. In addition, all the defects in a wafer can be analyzed and improved simultaneously utilizing the proposed defect identification methodology. Some successful case studies are also discussed to demonstrate the efficiency of the proposed defect identification methodology.

scholarly journals SRAM Bitcell Defect Identification Methodology Using Electrical Failure Analysis Data

2021 ◽  
Author(s):  
Hyungtae Kim ◽  
Geonho Kim ◽  
Yunrong Li ◽  
Jinyong Jeong ◽  
Youngdae Kim
Keyword(s):  
Failure Analysis ◽  
Technology Development ◽  
New Technology ◽  
Random Access ◽  
Analysis Data ◽  
Test Method ◽  
Design For Test ◽  
Defect Identification ◽  
Electrical Failure ◽  
Efficient Test

Abstract Static Random Access Memory (SRAM) has long been used for a new technology development vehicle because it is sensitive to process defects due to its high density and minimum feature size. In addition, failure location can be accurately predicted because of the highly structured architecture. Thus, fast and accurate Failure Analysis (FA) of the SRAM failure is crucial for the success of new technology learning and development. It is often quite time consuming to identify defects through conventional physical failure analysis techniques. In this paper, we present an advanced defect identification methodology for SRAM bitcell failures with fast speed and high accuracy based on the bitcell transistor analog characteristics from special design for test (DFT) features, Direct Bitcell Access (DBA). This technique has the advantage to shorten FA throughput time due to a time efficient test method and an intuitive failure analysis method based on Electrical Failure Analysis (EFA) without destructive analysis. In addition, all the defects in a wafer can be analyzed and improved simultaneously utilizing the proposed defect identification methodology. Some successful case studies are also discussed to demonstrate the efficiency of the proposed defect identification methodology.

MBIST Driven SRAM Failure Analysis Using Laser Voltage Imaging and Laser Voltage Probing

2019 ◽  
Author(s):  
Jessica Yang ◽  
Omprakash Rengaraj ◽  
Puneet Gupta ◽  
Rudolf Schlangen
Keyword(s):  
Failure Analysis ◽  
Photon Emission ◽  
Random Access ◽  
Random Access Memory ◽  
Fault Isolation ◽  
Static Random Access Memory ◽  
Production Testing ◽  
Access Memory ◽  
Electrical Failure ◽  
Voltage Imaging

Abstract Static Random-Access Memory (SRAM) failure analysis (FA) is important during chip-level reliability evaluation and yield improvement. Single-bit, paired-bit, and quad-bit failures—whose defect should be at the failing bit-cell locations—can be directly sent for Physical Failure Analysis (PFA). For one or multiple row/column failures with too large of a suspected circuit area, more detailed fault isolation is required before PFA. Currently, Photon Emission Microscopy (PEM) is the most commonly used Electrical Failure Analysis (EFA) technique for this kind of fail [1]. Soft-Defect Localization / Dynamic Laser Stimulation (SDL/DLS) can also be applied on soft (Vmin) row/column fails for further isolation [2]. However, some failures do not have abnormal emission spots or DLS sensitivity and require different localization techniques. Laser Voltage Imaging (LVI) and Laser Voltage Probing (LVP) are widely established for logic EFA, [3] but require periodic activation via ATE which may not be possible using MBIST hardware and test-patterns optimized for fast production testing. This paper discusses the test setup challenges to enable LVI & LVP on SRAM fails and includes two case studies on <14 nm advanced process silicon.

Volume Electrical Failure Analysis for Product-Specific Yield Enhancement

2010 ◽  
Author(s):  
Steven Kasapi ◽  
Joy Liao ◽  
Bruce Cory ◽  
Izak Kapilevich ◽  
Richard Portune ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Test Pattern ◽  
New Technology ◽  
Significant Benefit ◽  
Yield Enhancement ◽  
Specific Yield ◽  
Design Knowledge ◽  
Electrical Failure ◽  
Defect Localization ◽  
Technology Nodes

Abstract Yield on specific designs often falls far short of predicted yield, especially at new technology nodes. Product-specific yield ramp is particularly challenging because the defects are, by definition, specific to the design, and often require some degree of design knowledge to isolate the failure. Despite the wide variety of advanced electrical failure analysis (EFA) techniques available today, they are not routinely applied during yield ramp. EFA techniques typically require a significant amount of test pattern customization, fixturing modification, or design knowledge. Unless the problem is critical, there is usually not time to apply advanced EFA techniques during yield ramp, despite the potential of EFA to provide valuable defect insight. We present a volume-oriented workflow integrating a limited set of electrical failure analysis (EFA) techniques. We believe this workflow will provide significant benefit by improving defect localization and identification beyond what is available using test-based techniques.

Electrical Failure Analysis and Characterization of Leakage Paths Leading to Single Cell Failures in 128Mbit SDRAMs

2003 ◽  
Author(s):  
M. Versen ◽  
A. Schramm
Keyword(s):  
Failure Analysis ◽  
Single Cell ◽  
Case Studies ◽  
Leakage Current ◽  
Random Access ◽  
Electrical Failure ◽  
Leakage Path ◽  
Short Summary ◽  
Order Of Magnitude

Abstract A common failure signature in dynamic random access memories (DRAMs) is the single cell failure. The charge is lost and thereby the information stored in trench capacitors can be destroyed by high resistive leakage paths. The nature of the leakage path determines the properties of the failure such as temperature-, voltage- and timing-dependencies and its stability. In this study, high resistive leakage paths were investigated and delimited from classical shorts by estimating the order of magnitude of the leakage current and by comparison to a simple resistive leakage path. Such an investigation is the basis for a defect-based test approach that leads to multiparameter tests [1]. An introduction to the problem is given in the first section, while the second section deals with the characterization of the defects in two case studies. A short summary is given in the end.

Symptom or Cause? A Case Study

2015 ◽  
Author(s):  
Anuradha Swaminathan ◽  
Joy Liao ◽  
Howard Marks
Keyword(s):  
Failure Analysis ◽  
Continuous Wave ◽  
Analysis Data ◽  
Continuous Wave Laser ◽  
Electrical Failure ◽  
Root Cause ◽  
First Case ◽  
Successful Analysis ◽  
28 Nm

Abstract Although there are many advanced technologies and techniques for silicon diagnostics, effective failure analysis to root cause is getting increasingly challenging, as very often the electrical failure analysis data would point to a symptom that is the result of the defect rather than the actual location of the defect. Therefore, a combination of multiple techniques is often employed so that sensitivity of "the cause of the problem" can be observed. This work compiles a successful analysis with the aid of continuous wave laser voltage probing and soft defect localization techniques and presents three cases that are voltage-sensitive fails. The first case is a 28 nm device which failed at-speed scan. The second case is a 28 nm device failing RAM register BIST with high Vmin and the third case is a scan shift failure in a less than 28nm device.

Accelerating Technology Development and Yield Ramp on First Silicon Utilizing a Wafer-Level Dynamic EFA System

2016 ◽  
Author(s):  
Li-Qing Chen ◽  
Ming-Sheng Sun ◽  
Jui-Hao Chao ◽  
Soon Fatt Ng ◽  
Kapilevich Izak ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Technology Development ◽  
Photon Emission ◽  
Wafer Level ◽  
Success Story ◽  
Electrical Failure ◽  
Analysis Techniques ◽  
Soft Failure ◽  
Scan Chain ◽  
Hard Failure

Abstract This paper presents the success story of the learning process by reporting four cases using four different failure analysis techniques. The cases covered are IDDQ leakage, power short, scan chain hard failure, and register soft failure. Hardware involved in the cases discussed are Meridian WS-DP, a wafer-level electrical failure analysis (EFA) system from DCG Systems, V9300 tester from Advantest, and a custom cable interface integrating WSDP and V9300 with the adaption of direct-probe platform that is widely deployed for SoC CP test. Four debug cases are reported in which various EFA techniques are proven powerful and effective, including photon emission, OBIRCH, Thermal Frequency Imaging, LVI, LVP, and dynamic laser stimulation.

Improved Electrical Failure Analysis/Fault Isolation Tool Development on Server Motherboard Platforms Based on Historic Failure Modes

2004 ◽  
Author(s):  
Patrick G. Opdahl
Keyword(s):  
Failure Analysis ◽  
Failure Modes ◽  
Resource Constraints ◽  
Analysis Data ◽  
Fault Isolation ◽  
Tool Development ◽  
Success Rates ◽  
Complete Coverage ◽  
Electrical Failure ◽  
Silicon Devices

Abstract Electrical fault isolation constitutes the first steps in characterizing and isolating the failure modes and root causes of a failing motherboard. Ideally the Failure Analysis Test tools provide complete coverage of all motherboard buses and silicon devices. Time and resource constraints for tool development prevent complete coverage, however, so the challenge is to provide the highest level of debug test coverage in the shortest development schedule. A simplified Fault Isolation process has been created based on historical failure analysis data to reduce the development time and resources to create tools which allow diagnosing failure root causes on high-end server motherboards. This strategy prioritizes the most common types of electrical failure modes and the types of Electrical Failure Analysis / Fault Isolation (EFA-FI) tools best suited to diagnose these modes. The benefits of this strategy include shorter EFA-FI development times, equivalent success rates in failure root cause, lower costs, and more effective EFA-FI tools that can be used within the Design Team and at either OEM or Contract Manufacturing sites.

Detection and Characterization of an Electrical Failure Induced during Laser Ablation of Packages

2008 ◽  
Author(s):  
P. Schwindenhammer ◽  
H. Murray ◽  
P. Descamps ◽  
P. Poirier
Keyword(s):  
Laser Ablation ◽  
Integrated Circuits ◽  
Failure Analysis ◽  
Ablation Process ◽  
Thermally Induced ◽  
Electrical Failure ◽  
Electrical Phenomenon ◽  
Semiconductor Packages ◽  
Complex Semiconductor

Abstract Decapsulation of complex semiconductor packages for failure analysis is enhanced by laser ablation. If lasers are potentially dangerous for Integrated Circuits (IC) surface they also generate a thermal elevation of the package during the ablation process. During measurement of this temperature it was observed another and unexpected electrical phenomenon in the IC induced by laser. It is demonstrated that this new phenomenon is not thermally induced and occurs under certain ablation conditions.

Application of Fast Laser Deprocessing Techniques in Physical Failure Analysis on SRAM Memory of Advance Technology

2014 ◽  
Author(s):  
H.H. Yap ◽  
P.K. Tan ◽  
G.R. Low ◽  
M.K. Dawood ◽  
H. Feng ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Integrated Circuit ◽  
Cost Effective ◽  
Tetraethyl Orthosilicate ◽  
Ic Design ◽  
Advance Technology ◽  
Defect Identification ◽  
Technology Scaling ◽  
And Function ◽  
Metal Layers

Abstract With technology scaling of semiconductor devices and further growth of the integrated circuit (IC) design and function complexity, it is necessary to increase the number of transistors in IC’s chip, layer stacks, and process steps. The last few metal layers of Back End Of Line (BEOL) are usually very thick metal lines (>4μm thickness) and protected with hard Silicon Dioxide (SiO2) material that is formed from (TetraEthyl OrthoSilicate) TEOS as Inter-Metal Dielectric (IMD). In order to perform physical failure analysis (PFA) on the logic or memory, the top thick metal layers must be removed. It is time-consuming to deprocess those thick metal and IMD layers using conventional PFA workflows. In this paper, the Fast Laser Deprocessing Technique (FLDT) is proposed to remove the BEOL thick and stubborn metal layers for memory PFA. The proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in PFA.

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