Featured Research

from universities, journals, and other organizations

Savvy injection molding

Date:
April 7, 2010
Source:
Fraunhofer-Gesellschaft
Summary:
With the help of neural networks, in which complex algorithms are used to monitor critical process steps, engineers are paving the way for zero-defect production in the area of metal powder injection molding. The gain for manufacturers is less waste combined with time savings.

IFAM researchers inspecting components produced using metal injection molding.
Credit: Copyright Fraunhofer IFAM

With the help of neural networks, in which complex algorithms are used to monitor critical process steps, engineers are paving the way for zero-defect production in the area of metal powder injection molding. The gain for manufacturers is less waste combined with time savings.

The metal components used in the hinges of spectacle frames, surgical instruments or artificial heart valves are often very small. For some years now, manufacturers of components with complex geometries of this type have relied on a special production process: metal injection molding. Things can occasionally go awry during production, and then it is often impossible to detect defects until after sintering, the final step in the process chain, by which time it is too late to correct the defect.

Now, researchers at the Fraunhofer Institute for Manufacturing and Advanced Materials IFAM are working towards achieving zero-defect production. Their idea is that, at any time during the molding process, the system should be able to monitor all parameters -- such as weight, pressure and temperature -- and to deliver a verdict on the quality of the component.

"In this way, errors, dimensional inaccuracies and defects such as cracks, warps or cavities can be detected on line," explains IFAM project manager Dr. Thomas Hartwig. "This will allow the manufacturer to respond immediately by changing the relevant settings."

In the long run the system can, if required, even be programmed to alter the parameters fully automatically. The necessary technical support is provided by a neural network developed for metal injection molding (MIM) in a joint effort by the IFAM engineers and algorithmica technologies, a private company. "The neural network is based on highly complex algorithms," says Hartwig. "Its advantage over existing solutions is that it is self-learning."

After a mandatory initial training phase it can interpret all the measured data in the system, detecting correlations between them that would be impossible to find without the network. All information of relevance to the manufacturer can be given by the process control system, for instance the final weight of the component if the pressure or temperature is changed at a given step in the process.

"Our goal with neural networks is to reduce reject rates by at least 50 percent," says Hartwig. "This represents a huge cost saving for manufacturers because the raw materials are so expensive. Until now, companies often had to reject large numbers of components in the first few days before quality requirements could be met again."

Another advantage of neural networks is that they could eventually make quality checks superfluous and could also be deployed in other types of series production such as die-casting in the light-metal industry. Having successfully produced a test component with the aid of neural networks, the researchers are now looking for industrial partners.


Story Source:

The above story is based on materials provided by Fraunhofer-Gesellschaft. Note: Materials may be edited for content and length.


Cite This Page:

Fraunhofer-Gesellschaft. "Savvy injection molding." ScienceDaily. ScienceDaily, 7 April 2010. <www.sciencedaily.com/releases/2010/04/100406093522.htm>.
Fraunhofer-Gesellschaft. (2010, April 7). Savvy injection molding. ScienceDaily. Retrieved April 24, 2014 from www.sciencedaily.com/releases/2010/04/100406093522.htm
Fraunhofer-Gesellschaft. "Savvy injection molding." ScienceDaily. www.sciencedaily.com/releases/2010/04/100406093522.htm (accessed April 24, 2014).

Share This



More Computers & Math News

Thursday, April 24, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Monkeys Are Better At Math Than We Thought, Study Shows

Monkeys Are Better At Math Than We Thought, Study Shows

Newsy (Apr. 23, 2014) A Harvard University study suggests monkeys can use symbols to perform basic math calculations. Video provided by Newsy
Powered by NewsLook.com
High Court to Hear Dispute of TV Over Internet

High Court to Hear Dispute of TV Over Internet

AP (Apr. 22, 2014) The future of Aereo, an online service that provides over-the-air TV channels, hinges on a battle with broadcasters that goes before the U.S. Supreme Court on Tuesday. (April 22) Video provided by AP
Powered by NewsLook.com
Aereo Takes on Broadcast TV Titans in Supreme Court Today

Aereo Takes on Broadcast TV Titans in Supreme Court Today

TheStreet (Apr. 22, 2014) Aereo heads to the Supreme Court today to fight for its right to stream broadcast TV over the Internet -- against broadcasters who say the start-up infringes upon copyright law. TheStreet Deputy Managing Editor Leon Lazaroff explains the importance of the case in the TV industry and details what the outcome of it could mean for broadcasters and for cloud storage services -- as Aereo allows its subscribers to not just watch live TV shows but also store content to a DVR in the cloud. Video provided by TheStreet
Powered by NewsLook.com
Lytro Introduces 'Illum,' A Professional Light-Field Camera

Lytro Introduces 'Illum,' A Professional Light-Field Camera

Newsy (Apr. 22, 2014) The light-field photography engineers at Lytro unveiled their next innovation: a professional DSLR-like camera called "Illum." Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins