Statistical and Data-Driven Methods for Additive Manufacturing Qualification

Statistical and Data-Driven Methods for Additive Manufacturing Qualification

Proceedings of a Workshop

  • Author: Pool, Robert
  • Publisher: National Academies Press
  • ISBN: 9780309725620
  • eISBN Pdf: 9780309725637
  • eISBN Epub: 9780309725651
  • Place of publication:  United States
  • Year of digital publication: 2024
  • Month: November
  • Pages: 83
  • DDC: 510
  • Language: English

Additive manufacturing (AM), the process in which a three-dimensional (3D) object is built by adding subsequent layers of materials, enables novel material compositions and shapes, often without the need for specialized tooling. On March 11-13, 2024, the Board on Mathematical Sciences and Analytics of the National Academies held a workshop on Statistical and Data-Driven Methods for Additive Manufacturing. The workshop brought together researchers from different AM communities, statisticians, data scientists, and AI/machine learning (ML) experts to examine approaches that enhance dimensional accuracy and dimensional stability; recent advances and future directions in statistics, data analytics, AI, and ML; and the issues associated with a rapid advance of AM material qualification and part certification.

  • FrontMatter
  • Reviewers
  • Contents
  • 1 Introduction
  • 2 Data, Statistics, and Analytics for Additive Manufacturing in the National Laboratories
  • 3 Enhancing Dimensional Accuracy and Stability with Digital Integration
  • 4 Dimensional Accuracy, Part Quality, and Process Stability in Additive Manufacturing
  • 5 Dimensional Accuracy, Part Quality, and Process Stability in Post-Additive Processes
  • 6 Recap of Day 1
  • 7 A Primer on Statistics, Data Analytics, and Artificial Intelligence
  • 8 Statistics, Data Analytics, and Artificial Intelligence for Automated Machine Calibration and Toolpath Correction
  • 9 Overview of Measurement and Metrology
  • 10 Measurements and Calibration for Statistics, Data Analytics, and Artificial Intelligence
  • 11 Recap of Day 2
  • 12 Barriers to the Rapid Advance of Additive Manufacturing Material Qualification and Part Certification
  • 13 Key Themes from the Workshop
  • Appendix A: Public Meeting Agenda
  • Appendix B: Biographical Information for Workshop Planning Committee Members and Speakers

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