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March 8, 2026The International Journal of Advanced Manufacturing Technology8 citationsOpen Access

A systematic review and unified framework for design for additive manufacturing (DfAM)

GRGustavo ReinkeASAndréa Cristina Dos Santos

Key Points

  • The aim is to synthesize current practices and challenges in Design for Additive Manufacturing (DfAM).
  • Conducted a systematic review following the PRISMA framework.
  • Analyzed 65 peer-reviewed studies from the past decade.
  • Critically examined DfAM principles, computational strategies, and technical barriers.
  • DfAM enables intricate geometries and mass customization.
  • Identified barriers include material anisotropy and reproducibility issues.
  • Advances in topology optimization and machine learning enhance practical applications.

Abstract

Additive Manufacturing (Additive Manufacturing (AM), has progressed from a prototyping tool to a disruptive industrial technology, profoundly impacting sectors such as aerospace, automotive, and healthcare. This systematic review rigorously examines the current state-of-the-art in Design for Additive Manufacturing (DfAM), synthesizing its foundational principles, advanced computational strategies, and the overlooked structural discontinuity between design intent and final physical realization. Utilizing a structured search and selection process adhering to the PRISMA framework across major scientific databases, a total of 65 peer-reviewed studies published within the past decade were critically analyzed. The findings elucidate how DfAM fundamentally leverages the intrinsic design freedoms of AM, enabling the realization of intricate geometries, significant component lightweighting, and unprecedented mass customization. Concurrently, this review exposes the technical barriers that continue to impede widespread industrial scalability, notably material anisotropy, reproducibility issues, fragmented digital design workflows and precision metrology systems, such as CMM, 3D scanning and XCT. A key synthesis is provided on advances in topology optimization, lattice structure design, and the burgeoning integration of artificial intelligence and machine learning, with a specific emphasis on their practical implementation and industrial impact. Special consideration is given to sector-specific applications, particularly in biomedical engineering, where DfAM facilitates patient-tailored solutions but still confronts regulatory compliance and biocompatibility hurdles. Critically, this review maps evidence-based trends to expose the fragmented nature of the design-to-part continuum, providing a necessary, unified framework to guide subsequent research toward industrial maturity. This framework is designed to equip engineers, researchers, and practitioners for advancing DfAM practices, securing its evolution as a cornerstone of sustainable and innovative manufacturing within the industry eras.

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Cite This Study

Reinke et al. (2026) studied this question.

synapsesocial.com/papers/69ada836bc08abd80d5bb508https://doi.org/10.1007/s00170-026-17632-6
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