• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Saturday, August 2, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News

New software improves accuracy of factories’ mass-produced 3D-printed parts

Bioengineer by Bioengineer
March 17, 2021
in Science News
Reading Time: 2 mins read
0
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

IMAGE

Credit: University of Illinois Urbana-Champaign

Researchers at University of Illinois Urbana-Champaign developed software to improve the accuracy of 3D-printed parts, seeking to reduce costs and waste for companies using additive manufacturing to mass produce parts in factories.

“Additive manufacturing is incredibly exciting and offers tremendous benefits, but consistency and accuracy on mass-produced 3D-printed parts can be an issue. As with any production technology, parts built should be as close to identical as possible, whether it is 10 parts or 10 million,” said Professor Bill King, Andersen Chair in the Department of Mechanical Science and Engineering and leader of the project.

The team’s software allows for the rapid and automatic measurement of additively manufactured parts – a processes that is typically time consuming and costly. It also allows for increased accuracy.

“Factories that rely on 3D printing are being built rapidly all over the world. Our software helps ensure production is consistent, accurate, and cost-effective,” King said.

The software tracks how the accuracy of an additively manufactured part depends on which printer made the part and where the part was located in the printer. This process works by measuring parts using optical scanning technology and analysis of the scan data. This analysis allows a user to determine which parts are accurate and identifies which printers, and settings, produce the most accurate parts.

###

The University of Illinois researchers collaborated with engineers at Fast Radius Inc., a Chicago-based company with one of the world’s largest additive manufacturing factories. In 2018, the World Economic Forum identified Fast Radius as one of the world’s most advanced digital factories. King is one of the company’s co-founders and serves as its chief scientist.

The research was published this month in Additive Manufacturing, in an article titled: “Analyzing part accuracy and sources of variability for additively manufactured lattice parts made on multiple printers.” Authors on the study are Davis J. McGregor, Sameh Tawfick, and Chenhui Shao, and William King from University of Illinois, and Samuel Rylowicz, Aaron Brenzel, Daniel Baker, Charles Wood, David Pick, and Hallee Deutchman from Fast Radius.

Media Contact
Bill Bell
[email protected]

Related Journal Article

http://dx.doi.org/10.1016/j.addma.2021.101924

Tags: Business/EconomicsIndustrial Engineering/ChemistryResearch/DevelopmentTechnology TransferTechnology/Engineering/Computer Science
Share12Tweet8Share2ShareShareShare2

Related Posts

Gut γδ T17 Cells Drive Brain Inflammation via STING

Gut γδ T17 Cells Drive Brain Inflammation via STING

August 2, 2025
blank

Agent-Based Framework for Assessing Environmental Exposures

August 2, 2025

MARCO Drives Myeloid Suppressor Cell Differentiation, Immunity

August 2, 2025

CK2–PRC2 Signal Drives Plant Cold Memory Epigenetics

August 2, 2025
Please login to join discussion

POPULAR NEWS

  • Blind to the Burn

    Overlooked Dangers: Debunking Common Myths About Skin Cancer Risk in the U.S.

    60 shares
    Share 24 Tweet 15
  • Dr. Miriam Merad Honored with French Knighthood for Groundbreaking Contributions to Science and Medicine

    46 shares
    Share 18 Tweet 12
  • Study Reveals Beta-HPV Directly Causes Skin Cancer in Immunocompromised Individuals

    38 shares
    Share 15 Tweet 10
  • Neuropsychiatric Risks Linked to COVID-19 Revealed

    36 shares
    Share 14 Tweet 9

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

Gut γδ T17 Cells Drive Brain Inflammation via STING

Agent-Based Framework for Assessing Environmental Exposures

MARCO Drives Myeloid Suppressor Cell Differentiation, Immunity

  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.