Semiconductor memories are superb drivers for process yield and reliability improvement because of their highly structured architecture and use of aggressive layout rules. This combination provides outstanding failure signature analysis possibilities for the entire design, manufacturing, and test process. This article discusses five key disciplines of the signature analysis process that need to be orchestrated within the organization: design for test practices, test floor data collection methodology, post-test data analysis tools, root cause theorization, and physical failure analysis strategies.

Statistics, data analysis, root cause analysis, and problem-solving processes play a key role in failure investigations. This chapter explains how to collect failure investigation data, how to build and maintain a database for company-related failures, and how to use corresponding statistics including type of failure, material, and root cause. It describes the purpose and benefits of conducting a root cause analysis and the factors, namely relative failure importance and company value, that determine when an investigation should be performed. The chapter also discusses the four-step problem-solving process as it applies to failure investigation, how to assemble an investigation team, and the details of organization and planning. It concludes with a case history of the Firestone 500 steel-belted tire failure, stressing the importance of a systematic approach to failure investigations.

Tensile tests are performed for several reasons related to materials development, comparison, selection, and quality control. The properties derived from tensile tests are used in selecting materials for engineering applications. Tensile properties often are used to predict or estimate the behavior of a material under forms of loading other than uniaxial tension. This chapter provides a brief overview of tensile specimens and test machines, stress-strain curves, true stress and strain, and test methodology and data analysis.

This chapter discusses composite testing procedures, including tension, compression, shear, flexure, and fracture toughness testing as well as adhesive shear, peel, and honeycomb flatwise tension testing. It also discusses specimen preparation, environmental conditioning, and data analysis.

After the failure analysis team hypothesizes failure causes, prepares a failure mode assessment and assignment, and evaluates all potential failure causes, it may find in some cases that several causes are still suspect but cannot be confirmed. In this situation, an experiment is necessary to confirm or rule out suspected causes. This chapter discusses two predominant methods for doing this, namely analysis of variance (ANOVA) and Taguchi methods (a more powerful technique based on ANOVA).

High strain rate tensile testing is used to understand the response of materials to dynamic loading. The behavior of materials under high strain rate tensile loads may differ considerably from that observed in conventional tensile tests. This chapter discusses the processes involved in determining strain rate effects in tension by conventional tensile tests and covers expanding ring tests, flat plate impact tests, split-Hopkinson pressure bar tests, and rotating wheel tests.

This chapter assesses the potential impact of neural networks on package-level failure analysis, the challenges presented by next-generation semiconductor packages, and the measures that can be taken to maximize FA equipment uptime and throughput. It presents examples showing how neural networks have been trained to detect and classify PCB defects, improve signal-to-noise ratios in SEM images, recognize wafer failure patterns, and predict failure modes. It explains how new packaging strategies, particularly stacking and disintegration, complicate fault isolation and evaluates the ability of various imaging methods to locate defects in die stacks. It also presents best practices for sample preparation, inspection, and navigation and offers suggestions for improving the reliability and service life of tools.

X-ray imaging systems have long played a critical role in failure analysis laboratories. This article begins by listing several favorable traits that make X-rays uniquely well suited for non-destructive evaluation and testing. It then provides information on X-ray equipment and X-ray microscopy and its application in failure analysis of integrated circuit (IC) packaging and IC boards. The final section is devoted to the discussion on nanoscale 3D X-ray microscopy and its applications.

Failure analysis can sometimes involve considerations of statistics and probability. This chapter reviews some of the basic types of statistical distributions in order to understand some basic principles in their use. The main focus is on the uses of the normal distribution, which is the most commonly used statistical distribution. The chapter also includes a section discussing the reliability and probability of passing.

Machine vision is a means of simulating the image recognition and analysis capabilities of the human eye/brain system with electronic and electromechanical techniques. This chapter discusses four basic steps in the machine vision process, namely image formation, image preprocessing, image analysis, and image interpretation. Details of the processes involved, equipment used, and the factors to be considered are also presented. In addition, the applications of machine vision are discussed.

This chapter describes tensile testing of advanced ceramic materials, a category that includes both noncomposite, or monolithic, ceramics and ceramic-matrix composites (CMCs). The chapter presents four key considerations that must be considered when carrying out tensile tests on advanced monolithic ceramics and CMCs. These include effects of flaw type and location on tensile tests, separation of flaw populations, design strength and scale effects, and lifetime predictions and environmental effects. The chapter discusses the advantages, problems, and complications of four basic categories of tensile testing techniques as applied to ceramics and CMCs. These categories are true direct uniaxial tensile tests at ambient temperatures, indirect tensile tests, tests where failure is presumed to result from tensile stresses, and high-temperature tensile tests.

This chapter discusses the role of inverse analysis in providing input data for finite element simulations of metal forming processes. It describes the basic procedures for determining flow stress and friction by inverse analysis and for comparing experimental measurements with corresponding computed data. It also includes an example in which flow stress and friction were measured in compressed aluminum rings and the results used to verify the accuracy of predicted values.