Linneaâ„¢ Decision Support Tool

AI-Driven Part Printability Recommendation System
for Additive Manufacturing

Linnea applies AI and machine learning innovation to additive manufacturing engineering workflows to speed the identification of parts suitable for 3D printing

Key Benefits of Linnea

  • Improve efficiency and accuracy of AM part selection process
  • Save time and costs by automating analysis for suitable parts identification
  • Easily process and classify part features from 2D engineering drawings and 3D engineering models
  • Empower confident decisions with AI-enabled AM part candidacy scoring and recommendations

AM engineers spend innumerable hours manually reviewing and analyzing various forms of engineering data from disparate sources to identify good part candidates for 3D printing

Linnea enhances AM workflows with AI automation by taking on the heavy analysis burden and calculating part candidacy scores with recommendations for engineer decision making

Key sustainment and logistics organizations are rapidly adopting additive manufacturing as a strategic lever to:

  • Gain decision advantage
  • Remediate supply chain challenges
  • Manage increased product complexity
  • Eliminate lag times and costs in delivering parts for repair

Linnea Part Printability Recommendation System

Feature Extraction

  • Customized algorithms extract and process multi-format engineering inputs with machine learning, NLP, and computer vision
  • 2D drawing processing parses text, segments geometric objects, extracts geometric contours, and computes features
  • 3D model processing extracts text and derives geometric and complexity features

Classification Engine

  • Expert decision rules are applied to rapidly identify parts not suitable for printing due to incompatibilities with size, tolerance, or material
  • AI/ML-classifiers accurately predict AM part suitability based on complexity and geometry features
  • 3D print recommendations and scoring for parts are served to the interactive user interface

Interactive User Interface

  • Human-in-the loop workflow enables AM engineer to interact with part printability recommendations for further analyses and reporting
  • Final 3D print decisions are made by the AM engineer and captured via the user interface
  • Parts identified for 3D printing are cataloged and made available for future analyses and decision making

Ready to elevate you AM processes?

Schedule your personalized demo to experience Linnea in action!

Contact: Jan Turkelson, Senior Vice President or Scott Rutledge, Government Director

Customer Journey Case Studies

Our experts leverage relevant accelerators for specific business goals providing quick wins and efficient return on investment