58e014568186b4851095 · Current State and Benchmarking Generative Artificial intelligence for Additive Manufacturing

{
  "title_en": "Current State and Benchmarking Generative Artificial intelligence for Additive Manufacturing",
  "designation": "",
  "series": "",
  "status": "",
  "date": "2024-11-13",
  "date_original": "November 13, 2024",
  "url": "https://www.nist.gov/publications/current-state-and-benchmarking-generative-artificial-intelligence-additive",
  "source": "NIST Publications",
  "display_en": "",
  "authors_en": "Nowrin Akter Surovi , Paul Witherell , Kumara Sundar, Vinay Saji Mathew",
  "abstract_excerpt_en": "Additive Manufacturing (AM) is becoming increasingly popular in academia and industry due to its cost-effectiveness and time-saving benefits. However, AM faces several challenges that must be addressed to enhance its efficiency. While Machine Learning (ML)",
  "id": "58e014568186b4851095",
  "sources": [
    "NIST Publications"
  ],
  "source_records": [
    {
      "title_en": "Current State and Benchmarking Generative Artificial intelligence for Additive Manufacturing",
      "designation": "",
      "series": "",
      "status": "",
      "date": "2024-11-13",
      "date_original": "November 13, 2024",
      "url": "https://www.nist.gov/publications/current-state-and-benchmarking-generative-artificial-intelligence-additive",
      "source": "NIST Publications",
      "display_en": "",
      "authors_en": "Nowrin Akter Surovi , Paul Witherell , Kumara Sundar, Vinay Saji Mathew",
      "abstract_excerpt_en": "Additive Manufacturing (AM) is becoming increasingly popular in academia and industry due to its cost-effectiveness and time-saving benefits. However, AM faces several challenges that must be addressed to enhance its efficiency. While Machine Learning (ML)"
    }
  ],
  "translation_state": "none"
}