Automated Part Candidacy Analysis Pipeline

Customer Challenge

The Army seeks an AI-enabled decision support tool for additive manufacturing (AM) engineers to speed parts identification. Currently, Army AM engineers spend innumerable hours manually searching the Army’s Product Lifecycle Management (PLM) systems to review and analyze technical and logistics data to determine part printability.

Innovative Solution

For this effort, Illumination Works proposed our Linnea Part Printability Recommendation System. In its end state, Linnea will integrate seamlessly into Army PLM systems. Illumination Works’ Linnea is an enabling technology for the Army that will greatly improve the productivity of AM engineers by automating much of their AM part candidacy analysis pipeline.

Benefits/Outcomes

  • Apply machine learning techniques to help automate the current manual process of identifying parts for AM
  • Automatically process technical and logistics data
  • Engineer relevant data features
  • Apply artificial intelligence/machine learning classifiers
  • Predict the suitability of parts for AM

Toolbox

  • Artificial Intelligence/Machine Learning
  • Computer vision
  • Optical character recognition (OCR)

Business Value

  • Tremendous cost savings across the Department of Defense (DoD) by automating the current manual process of identifying parts for 3D printing
  • Improved operational readiness via automation that enables identification of a greater pool of parts for AM
  • Industry agnostic automation for manufacturing parts, including utility, construction, medical, and transportation

Domain Expertise

  • Engineering data and CAD models

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