Additive Manufacturing Industry Overview

Pre-2020 Growth

• Additive manufacturing industry growth averaged 27.4% year-over-year before 2020.

Impact of COVID-19 Pandemic

• Global supply chains stalled, affecting production quotas.
• Manufacturers leveraged 3D printing for:
  • Face shields
  • Masks
  • Nasal swabs
  • Ventilator parts

2021 Industry Recovery

• Wohler's Report 2021: Industry grew 7.5%, reaching $12.8 billion in 2020.
• 3D printed parts production increased significantly to combat pandemic challenges.
• 3D Hubs 2021 report: 34% increase in engineering firms using 3D printing for functional parts compared to 2019.

Key Growth Areas

• Largest increases in sectors:
  • Biotechnology
  • Transportation
  • Automotive

Major Investments and Innovations

• GE: Invested over $3 billion in additive manufacturing, using it in products like:
  • Jet engines
  • Medical devices
  • Home appliances
• Boeing's Dreamliner 787: First commercial aircraft using 3D printed parts, saving $2-3 million per plane.
• On-demand spare parts reduce operational downtime and costs.

Case Studies

• Etihad Airlines & Big Rep: Partnership in 2020 for on-demand part printing.
• Open Hand Project: Prosthetic hands produced for $1,000, compared to $100,000 normally.
• HP & Redington 3D: Produced 120,000 ventilator parts for Agva Healthcare in India quickly during the pandemic.

Challenges in Additive Manufacturing

• Cost of Industrial Machines: Ranges from $100,000 to $5 million for metal part production.
• Material Costs: 10-100 times higher than conventional manufacturing, affecting high-volume production.
• Software Development: The gap between hardware and software is evident; current software is inefficient, leading to production gaps.

Role of Artificial Intelligence (AI) and Machine Learning

• AI is crucial for future growth in additive manufacturing:
  • Enhances material development and part design.
  • Optimizes workflows and production processes.

Benefits of AI in Manufacturing

• AI technologies can process data faster than humans, improving efficiency:
  • Generative Design: AI can autonomously design parts free of traditional manufacturing limitations.
  • Inspection & Quality Control: AI systems can predict material behavior and spot defects during production.
• Example: Inkbit: AI-based vision system scans 3D printing layers, predicting material behavior.

Efficiency Gains

• AI can potentially cut production time from 30 minutes to seconds per job.
• Improves printer utilization, material selection, and defect detection.
• Reduces need for specialized knowledge and helps automate processes.

Conclusion

• Incorporating AI in additive manufacturing can position it as the manufacturing solution of the future.