Search Results for data collection

This chapter concentrates almost exclusively on inspection techniques related to pressure vessels and pipework. The discussion covers the general aspects associated with inspection and the key factors relevant to it. In addition, the chapter addresses processes involved in data collection and management, namely data acquisition, reporting, trending, reviewing, and auditing. Capabilities and limitations of in-service inspection techniques are discussed in the Appendix to this chapter.

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.

This appendix identifies producers, suppliers, and service providers experienced with superalloy materials and applications. It also identifies potential sources of engineering information and property data.

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.

This chapter focuses on creep-rupture failure, or more precisely, the time required for such a failure to occur at a given stress and temperature. It begins with a review of creep-rupture phenomena and the various ways creep-rupture data are presented and analyzed. It then examines a large collection of creep-rupture data corresponding to different alloy designations and heat treatments, identifying key relationships, similarities, and differences. It also presents a test method developed by the authors in which twelve materials are tested over a range of temperature, stress, and time in order to determine multiheat constants that are then used to fit multiheat data from other materials and thus estimate rupture times.

This chapter provides an overview of the possible mechanisms of failure for heat treated steel components and discusses the techniques for examining fractures, ductile and brittle failures, intergranular failure mechanisms, and fatigue. It begins with a description of the general sources of component failure. This is followed by a section on the stages of a failure analysis, which can proceed one after the other or occur at the same time. These stages of analysis are collection of background data, preliminary visual examination, nondestructive testing, selection and preservation of specimens, mechanical testing, macroexamination, microexamination, metallographic examination, determination of the fracture mechanism, chemical analysis, exemplar testing, and analysis and writing the report. The chapter ends with a discussion on various processes involved in the determination of the fracture mechanism.

This appendix is a collection of tables containing thermal, electrical, mechanical, and physical property data for metals under various conditions. It also includes the periodic table of elements.

Critical process variables must be controlled to ensure uniform and repeatable heat-treating results. This chapter covers the subject of controlling the heat-treating process. All heat-treating equipment utilizes various sensors, timers, and other components to monitor and control the process utilizing various control methods. The chapter focuses on temperature control and measurement, including a discussion about thermocouples and devices for measuring thermal and electrical conductivity.

In this overview of diagnosis of scan logic and diagnosis driven failure analysis, the authors explore the world of diagnosis of digital semiconductors devices. After shortly outlining the technology behind diagnosis, the main part of this article describes key improvements to the basic diagnosis tools, discussing their merits for the failure analysis engineer. The article also describes the various requirements and other considerations that typically need to be taken into account to set up a full working scan diagnosis system. It summarizes the principles of design with embedded compression technologies. Finally, several successful industrial applications of diagnosis are presented.

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.

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.

Time-domain based characterization methods, mainly time-domain reflectometry (TDR) and time-domain transmissometry (TDT), have been used to locate faults in twisted cables, telegraph lines, and connectors in the electrical and telecommunication industry. This article provides a brief review of conventional TDR and its application limitations to advanced packages in semiconductor industry. The article introduces electro optical terahertz pulse reflectometry (EOTPR) and discusses how its improvements of using high frequency impulse signal addressed application challenges and quickly made it a well-adopted tool in the industry. The third part of this article introduces a new method which combines impulse signal and the TDT concept, and discusses a combo TDR and TDT method. Cases studies and application notes are shared and discussed for each technique. Application benefits and limitations of these techniques (TDR, EOTPR, and combo TDR/TDT) are summarized and compared.

This chapter discusses the setup and use of a transmission electron detector in a typical scanning electron microscope (SEM). It describes the arrangement and function of the primary components in the detector, following the signal path from the sample to a micromirror array where it is directed by the user to either a CMOS sensor (to record diffraction patterns) or a photomultiplier tube (to observe real-space images). The chapter discusses some of the nuances of digital imaging and diffraction and includes examples in which transmission electron detectors are used to analyze gold films, carbon nanotubes, zeolite sheets, and monolayer graphene. It also describes emerging techniques, including four-dimensional STEM, thermal diffuse scattering, energy filtering, aberration correction, and atomic resolution imaging.