This chapter sheds light on the challenges involved in diagnosing faults in analog, mixed-signal, and RF circuits. It describes some of the work being done to leverage the benefits of standardization, improve fault simulation tools, and overcome limitations on optical fault isolation techniques. One of the solutions being considered is to integrate LEDs throughout the analog circuit, thereby using light to report the status of internal signals.

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.

This chapter familiarizes readers with the basic theory of molecular dynamics and its application in the study of materials. It explains how material properties and behaviors are determined through the iterative calculation of motion equations for a collection of atoms under a given set of conditions. It also provides a walk-through on the use of LAMMPS, an open-source molecular dynamics simulator, discussing the selections and inputs of relevance to practical materials problems.

The appendix contains detailed simulation examples through which readers learn how to format and analyze problems using the LAMMPS molecular dynamics simulator. By means of simulation, readers will determine the thermal expansion coefficient of copper, generate stress-strain plots for aluminum at different temperatures, calculate the surface energy of copper for different crystal orientations, investigate diffusion effects in BCC iron, estimate the sliding friction between graphene layers, compare the stacking fault energy of silver and aluminum, and analyze the properties and behaviors of liquids and gases. All examples employ a systematic problem-solving approach and include necessary input code.

This chapter provides an overview of how the disciplines of design, material, and manufacturing contribute to engineering for functional performance. It describes the interaction of product designers and casting engineers in product development. It discusses the consequences of component failure, uncertainty in data and assumptions, and selection of the factor of safety. The chapter also presents an overview of the functional requirements for product performance and provides an overview of product design development. It also presents a partial list of the different tests that are performed on prototypes and examples of product testing. The chapter describes the requirements of a traceability system.

The casting engineer contributes to a successful component design by offering expertise in molding, core making, and material characteristics and by recommending the most suitable casting process to use to meet quality and cost targets. The casting engineer's responsibilities include recommending locator positioning; advising about lugs, hooks, or holes for casting handling through all processes; determining the choice of a parting plane and pouring orientation; designing cores for accurate positioning, suitable venting, and proper cleaning; guiding decisions about wall thicknesses and junctions; making suggestions about casting design to eliminate distortion; optimizing the gating design for slag-free metal; and establishing the feeding techniques to eliminate shrink porosity. This chapter provides the guidelines for these responsibilities. In addition, the guidelines for the use of chaplets and chills in cast iron castings; guidelines for drafts, machine stock, tolerances, and contraction or shrink rule; and guidelines for pattern layouts and nesting are also covered.

Over the revolutionary era of semiconductor technology, Computer-Aided Design Navigation (CADNav) tools have played an increasingly critical role in silicon debug and failure analysis (FA) in efforts to improve manufacturing yield while reducing time-to-market for integrated circuit (IC) products. This article encompasses the key principles of CADNav for various aspects of semiconductor FA and its importance for improved yield and profitability. An overview of the required input data and formats are described for both IC and package devices, along with key considerations and best practices recommended for fast fault localization, accurate root cause analysis, FA equipment utilization, efficient cross-team collaboration, and database management. Challenges with an FA lab ecosystem are addressed by providing an integrated database and software platform that enable design layout and schematic analysis in the FA lab for quick and accurate navigation and cross-tool collaboration.

The modeling and simulation activities in the field of high-pressure cold spray can be divided into two main parts: solid mechanics and fluid dynamics. This chapter focuses on these parts of modeling work in cold spray research. The discussion covers the objective, principal concepts, methods, and outcome of modeling and simulation of particle impact and of in-flight history of particles in cold spraying. The concept of integration of particle impact and fluid flow modeling to optimize cold spray deposition for a given material is also explained.

This chapter focuses on key requirements for obtaining third-generation advanced high-strength steels (AHSS). The discussion covers the microstructure design for AHSS, novel AHSS processing routes, the development of nanostructured AHSS, and the development of third-generation AHSS by the Integrated Computational Materials Engineering approach.

The design and optimization of sheet metal forming operations is aided by tools and techniques that have been developed and refined over several decades. This chapter covers many of these methods and practices and explains where and how they are used. It begins by showing how the stress state at any point in a material can be expressed in different ways for different purposes. It then compares and contrasts some of the more widely used yield criteria and demonstrates the use of flow rules. It also explains how to calculate power, energy, and effective strain and strain rate and how hardening laws are used to predict strain-hardening behaviors.

This chapter provides a detailed analysis of the deep drawing process. It begins by explaining that different areas of the workpiece are subjected to different types of forces and loads, equating to five deformation zones. After describing the various zones, it discusses the effect of key process parameters including the draw ratio, material properties, geometry, interface conditions, equipment operating speed, and tooling. It then walks through the steps involved in predicting stress, strain, and punch force using the slab method and finite element analysis and presents the results of simulations conducted to assess the influence of blank diameter, thickness, and holding force as well as strain-hardening and strength coefficients. It also discusses the cause of defects in deep drawn rectangular cups and presents the case study of a deep drawn rectangular cup made from an aluminum blank.

This chapter provides an overview of the blanking process and the forces and stresses involved. It discusses the factors that affect part quality and tool life, including punch and die geometry, stagger, clearance, and wear as well as punch velocities, misalignment, and snap-thru forces. It also discusses ultra-high-speed blanking, fine blanking, and shearing, and the use finite-element simulations to predict part edge quality.

This chapter discusses the use of modeling and simulation technology in the development of sheet metal forming processes. It describes the five major steps involved in finite-element analysis and the various ways functions of interest can be approximated at each point or node in a finite-element mesh. It explains how to obtain input data, what to expect in terms of output data, and how to predict specific types of defects. In addition, it presents several case studies demonstrating the use of finite elements in blanking and piercing, deep drawing of round and rectangular cups, progressive die sequencing, blank holder force optimization, sheet hydroforming, hot stamping, and springback and bending of advanced high-strength steels. It also discusses the factors that affect the accuracy of finite element simulations such as springback, thickness variations, and nonisothermal effects.

This chapter presents two case studies; one demonstrating the use of finite-element analysis (FEA) in the design of a progressive die forming operation, the other explaining how software simulations helped engineers reduce thinning and eliminate cracking and deformation observed in clutch hubs formed using a three-step transfer die process. It also discusses the role of FEA and commercial software in the design of progressive dies.