3D Printing ProcessesAdditive ManufacturingAutomation

EIT Digital launches Automation Support for Additive Manufacturing program

"Ontology of AM" project to make data on AM parts available through software add-on

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Automation Support for Additive Manufacturing, an activity supported by EIT Digital as part of the OEDIPUS High Impact Initiative intends to make it easier and faster for businesses to switch from traditional to additive manufacturing. The activity’s partners are Aalto University, Siemens, and DeskArtes.

A major barrier to more widespread adoption of additive manufacturing is that engineers and designers are not always familiar with 3D printing, therefore it’s not easy for them to understand which combination of process, machine and material to use to print a specific component. This is where EIT Digital’s project comes in.

“At Aalto University we created a database with up-to-date relevant data for 3D printing of end-use components. The database contains comprehensive data including machines, materials, mechanical properties and accuracy levels required to print a certain component; also listing post-processing steps and other factors,” Aalto’s activity leader Niklas Kretzschmar says, “Consequently,  this information and their theoretical connections  were forwarded to Siemens to create knowledge graphs, linking this data logically with each other.”

An ontology of AM

The result is that Automation Support for Additive Manufacturing will generate an “ontology of additive manufacturing”, taking the form of a software add-on, a plugin that will be integrated and commercialized by DeskArtes as an extension to its 3D Data Expert software.

Automation Support for Additive Manufacturing
A screenshot from Deskartes 3D Data Expert

The usability of the solution is pretty straightforward. All the user has to do, in fact, is to specify size, material and surface characteristics or upload the CAD file (including additional information) of a certain component to receive all 3D printing alternatives automatically.

“For instance, you want to investigate in printing a complex industrial component out of a specific metal alloy and the system would tell you which metal additive manufacturing process, machine and material type could ideally be used to address user’s demands. In this context, the system additionally provides feedback on certain mandatory post-processing steps as well as optional measures that could be beneficial for you,” Kretzschmar says.

In the past, to get to the same results, in-depth manual research from the user was needed, to access all the related data and get relevant answers; because of the complexity of the process the consequence was all too often sub-optimal printings (too expensive or not conform to the product requirements). With this solution the process has been largely automated and there’s no longer much room for mistakes from non-additive manufacturing experts.

The system, which will be sold to manufacturing, system development and service companies, is now undergoing a pilot testing phase with three trial customers and is going to be marketed by the end of this year.

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Davide Sher

Since 2002, Davide has built up extensive experience as a technology journalist, market analyst and consultant for the additive manufacturing industry. Born in Milan, Italy, he spent 12 years in the United States, where he completed his studies at SUNY USB. As a journalist covering the tech and videogame industry for over 10 years, he began covering the AM industry in 2013, first as an international journalist and subsequently as a market analyst, focusing on the additive manufacturing industry and relative vertical markets. In 2016 he co-founded London-based VoxelMatters. Today the company publishes the leading news and insights websites VoxelMatters.com and Replicatore.it, as well as VoxelMatters Directory, the largest global directory of companies in the additive manufacturing industry.

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