Additive manufacturing (AM) processes fabricate parts in a layer-by-layer manner by which materials are added and processed repeatedly. This article introduces the general concepts and approaches to design for AM (DFAM) and outlines important implications for part characteristics, design opportunities, manufacturing practices, supply chains, and even business models. It presents contrasting perspectives on DFAM, followed by a discussion on more general and overarching opportunistic design methods and on design for constraints, similar to conventional DFM. It concludes with a presentation of a design approach to the AM process chain, acknowledging that AM-fabricated parts typically undergo several postprocessing steps and that it is important to design taking into account these steps.

Additive manufacturing (AM) provides exceptional design flexibility, enabling the manufacture of parts with shapes and functions not viable with traditional manufacturing processes. The two paradigms aiming to leverage computational methods to design AM parts imbuing the design-for-additive-manufacturing (DFAM) principles are design optimization (DO) and simulation-driven design (SDD). In line with the adoption of AM processes by industry and extensive research efforts in the research community, this article focuses on powder-bed fusion for metal AM and material extrusion for polymer AM. It includes detailed sections on SDD and DO as well as three case studies on the adoption of SDD, DO, and artificial-intelligence-based DFAM in real-life engineering applications, highlighting the benefits of these methods for the wider adoption of AM in the manufacturing industry.

This article introduces the design and manufacturing implications of additive manufacturing (AM) on part characteristics as well as on design opportunities and on manufacturing practices, supply chains, and even business models. In addition, it describes how they relate to the fundamental nature of AM processes and discusses the characteristics and purposes of AM processes and the parts they fabricate.

This article reviews business cases for additive manufacturing (AM) and offers suggestions on monetizing the flexibility created by AM through a deep understanding of the most applicable cost drivers. It also reviews the common adoption drivers for AM and provides suggestions on how to take advantage of them. The AM maturity model breaks down potential additively manufactured products into five levels: preproduction, production influence, substitution, functional designs, and multifunctional. The business value of these levels is further described and evaluated with respect to the triple constraint of project management. The article then focuses on success factors for implementing AM.

Additive manufacturing (AM) offers expansive design freedoms for realizing parts that are more complex and customized than their conventionally fabricated counterparts, but all AM technologies impose restrictions on buildable geometries and features. Design rules capture those restrictions in the form of best practices to successfully design for AM. This article discusses how design rules can potentially support and accelerate the process of developing part geometry for AM. The discussion provides examples of design rules that are independent of any specific AM process and then discusses design rules specific to particular AM processes.

This article presents the analytics challenges in additive manufacturing. It discusses the types and applications of data analytics. Data analytics can be classified into four types: descriptive, diagnostic, predictive, and prescriptive. The diverse applications of data analytics and machine learning include design, process-structure-properties (PSP) relationships, and process monitoring and quality control. The article also presents tools used for data analytics.

The aviation industry has been driving the use of additive manufacturing (AM), moving from one-off demonstrator or pathfinder components toward higher-volume serial production applications. This article presents an introduction to AM in aviation, explaining how aviation requirements apply to AM. It also presents advancements, standards, and future expectations of aviation.

This article focuses on two streams of the research on part consolidation (PC): PC in the conventional manufacturing context, and PC in the additive manufacturing (AM) context. It reviews the challenges of applying AM-PC potentials. The article includes research literature on the selection of part candidates for consolidation and summarizes the conversion of assembly design to consolidated design. Then, a holistic approach for supporting PC design is introduced with integrated modules of part filtering and fusion of parts. Details of the key techniques of the two modules are later introduced with a gas pedal example. Finally, emerging trends in PC research are discussed.

This article presents the use of additive manufacturing (AM) in the space industry. It discusses metal AM processes and summarizes metal AM materials, including their relevant process categories and references. It also presents the design for AM for spacecraft. The article also provides an overview of in-space manufacturing and on-orbit servicing, assembly, and manufacturing. It presents some of the specific areas that must be understood for the qualification of AM. The article also discusses future trends, challenges, and opportunities for aerospace.