This article provides an overview of the general methods of metal powder production. It details the primary methods for particle sizing used in additive manufacturing: sieving, laser diffraction and scattering, and digital image analysis. Methods of interpreting and understanding particle size distribution (PSD) data are presented, with an emphasis on the differences between count- and volume-based PSDs. The article then outlines practices for both qualitative and quantitative assessment of particle morphology.

Data formats play an integral role in leveraging the flexibility of additive manufacturing and achieving consistent part quality. This article compares and contrasts data formats optimized for design, materials, processes, and inspection methods. It also discusses the types of data associated with the six phases of additive manufacturing, namely design, build, design with build plan, design with machine-specific build plan, post-processed part, and qualified part.

This article reviews the main theoretical and practical aspects of sequence normally followed in digital image-acquisition, processing, analysis, and output for material characterization. It discusses the main methods of digital imaging, image processing, and analysis, as applied to microscopy of materials. The article describes the basic concepts of sampling and resolution and quantization of light microscopy, scanning electron microscopy, and transmission electron microscopy. It discusses the acquisition of a digital image that accurately represents the sample under observation and output of the image to a printer. The methods used to enhance the digital image and to extract quantitative information are also described. Different types of image segmentation, namely, adaptive segmentation and contour-based segmentation, are reviewed. The article also presents case studies on the application of image processing and analysis to materials characterization.

Additive manufacturing, as the first fully digital manufacturing process, is critically dependent on data, including the input materials, the process parameters guiding the three-dimensional printing process execution, any postprocessing steps, and any inspections performed on the printed coupons and/or parts, to name just a few examples. This article presents the standards to enable findable, accessible, interoperable, and reusable (FAIR) data. It then discusses three main types of data models that are used to capture different levels of detail and granularity of data: conceptual, logical, and physical. Different approaches and techniques with their own strengths and weaknesses are developed to model data. Four of the major types of data models include hierarchical, relational, object-oriented, and network/graph-based. The article also presents the evolution of data management approaches. It then describes the characteristics of effective logical data models.

Failure analysis is an investigative process in which the visual observations of features present on a failed component and the surrounding environment are essential in determining the root cause of a failure. This article reviews the basic photographic principles and techniques that are applied to failure analysis, both in the field and in the laboratory. It discusses the processes involved in visual examination, field photographic documentation, and laboratory photographic documentation of failed components. The article describes the operating principles of each part of a professional digital camera. It covers basic photographic principles and manipulation of settings that assist in producing high-quality images. The need for accurate photographic documentation in failure analysis is also presented.