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Reliability Prediction for Microelectronics. Edition No. 1. Quality and Reliability Engineering Series

  • Book

  • 400 Pages
  • March 2024
  • John Wiley and Sons Ltd
  • ID: 5867435
RELIABILITY PREDICTION FOR MICROELECTRONICS

Wiley Series in Quality & Reliability Engineering

REVOLUTIONIZE YOUR APPROACH TO RELIABILITY ASSESSMENT WITH THIS GROUNDBREAKING BOOK

Reliability evaluation is a critical aspect of engineering, without which safe performance within desired parameters over the lifespan of machines cannot be guaranteed. With microelectronics in particular, the challenges to evaluating reliability are considerable, and statistical methods for creating microelectronic reliability standards are complex. With nano-scale microelectronic devices increasingly prominent in modern life, it has never been more important to understand the tools available to evaluate reliability.

Reliability Prediction for Microelectronics meets this need with a cluster of tools built around principles of reliability physics and the concept of remaining useful life (RUL). It takes as its core subject the ‘physics of failure’, combining a thorough understanding of conventional approaches to reliability evaluation with a keen knowledge of their blind spots. It equips engineers and researchers with the capacity to overcome decades of errant reliability physics and place their work on a sound engineering footing.

Reliability Prediction for Microelectronics readers will also find: - Focus on the tools required to perform reliability assessments in real operating conditions- Detailed discussion of topics including failure foundation, reliability testing, acceleration factor calculation, and more- New multi-physics of failure on DSM technologies, including TDDB, EM, HCI, and BTI

Reliability Prediction for Microelectronics is ideal for reliability and quality engineers, design engineers, and advanced engineering students looking to understand this crucial area of product design and testing.

Table of Contents

Author Biography xiii

Series Foreword xv

Preface xix

Scope xxi

Introduction xxiii

1 Conventional Electronic System Reliability Prediction 1

1.1 Electronic Reliability Prediction Methods 2

1.2 Electronic Reliability in Manufacturing, Production, and Operations 27

1.3 Reliability Criteria 34

1.4 Reliability Testing 42

2 The Fundamentals of Failure 55

2.1 The Random Walk 56

2.2 Diffusion 61

2.3 Solutions for the Diffusion Equation 63

2.4 Drift 69

2.5 Statistical Mechanics 70

2.6 Chemical Potential 74

2.7 Thermal Activation Energy 77

2.8 Oxidation and Corrosion 81

2.9 Vibration 85

2.10 Summary 89

3 Physics-of-Failure-based Circuit Reliability 91

3.1 Problematic Areas 92

3.2 Reliability of Complex Systems 113

3.3 Physics-of-Failure-based Circuit Reliability Prediction Methodology 119

4 Transition State Theory 133

4.1 Stress-Related Failure Mechanisms 134

4.2 Non-Arrhenius Model Parameters 138

4.3 Physics of Healthy 171

5 Multiple Failure Mechanism in Reliability Prediction 179

5.1 MTOL Testing System 183

5.2 MTOL Matrix: A Use Case Application 191

5.3 Comparison of DSM Technologies (45, 28, and 20 nm) 200

5.4 16 nm FinFET Reliability Profile Using the MTOL Method 204

5.5 16 nm Microchip Health Monitoring (MHM) from MTOL Reliability 215

6 System Reliability 229

6.1 Definitions 230

6.2 Series Systems 232

6.3 Weibull Analysis of Data 241

6.4 Weibull Analysis to Correlate Process Variations and BTI Degradation 247

7 Device Failure Mechanism 255

7.1 Time-Dependent Dielectric Breakdown 257

7.2 Hot Carrier Injection 265

7.3 Negative Bias Temperature Instability 276

7.4 Electromigration 282

7.5 Soft Errors due to Memory Alpha Particles 285

8 Reliability Modeling of Electronic Packages 289

8.1 Failure Mechanisms of Electronic Packages 293

8.2 Failure Mechanisms’ Description and Models 297

8.3 Failure Models 310

8.4 Electromigration 315

8.5 Corrosion Failure 317

8.6.1 Creep 322

8.7 Reliability Prediction of Electronic Packages 325

8.8 Reliability Failure Models 325

References 331

Index 363

Authors

Joseph B. Bernstein Ariel University, Israel. Alain Bensoussan Universite Paris-Dauphine et INRIA. Emmanuel Bender Ariel University, Israel.