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Nesting and Scheduling Problems for Additive Manufacturing: A Taxonomy and Review.

Yosep Oh1,2, Paul Witherell1, Yan Lu1

  • 1Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899.

Additive Manufacturing
|June 8, 2026
PubMed
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This study surveys nesting and scheduling in Additive Manufacturing (AM), crucial for mass customization. It proposes a new taxonomy to better integrate these production management aspects for future research.

Area of Science:

  • Manufacturing Engineering
  • Operations Research
  • Computer Science

Background:

  • Industry 4.0 trends drive complex geometries via Additive Manufacturing (AM).
  • AM research is shifting from design realization to production management for mass customization.
  • Nesting and scheduling are critical for efficient batch processing of heterogeneous parts in AM.

Purpose of the Study:

  • To present the current status of nesting and scheduling studies applied to Additive Manufacturing.
  • To identify critical issues and future research directions in AM production management.
  • To propose a novel, holistic taxonomy for classifying AM nesting and scheduling research.

Main Methods:

  • A comprehensive literature survey of 53 technical papers on AM nesting and scheduling.
Keywords:
3D PrintingAdditive ManufacturingNestingProduction PlanningScheduling

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  • Development of a new three-dimensional taxonomy (Part, Build, AM Machine) to classify research.
  • Definition of six classes and eight supplementary criteria for organizing research papers.

    • Main Results:

    • Existing taxonomies are limited as they treat nesting and scheduling separately.
    • The proposed taxonomy provides a holistic view, integrating both aspects.
    • 53 papers were classified, revealing key research gaps and challenges.

    Conclusions:

    • A unified approach to nesting and scheduling is essential for advancing AM production.
    • The proposed taxonomy offers a framework for future research and development in AM.
    • Further investigation is needed to address the identified critical issues in AM production management.