Feb 17, 2017
By Elizabeth Montalbano, DesignNews
A new toolkit that uses artificial intelligence (AI) to help advance the 3D printing of metals by managing and simplifying steps of what is currently a complex process.
Sculpteo Software , a French software provider, recently unveiled Agile Metal Technology (AMT) at the CES show in Las Vegas. The suite of six tools aim to help take the complexity out of 3D metal printing by adding automation, management, and optimization to the 3D metal printing process.
Using metals in an additive manufacturing process allows for the creation of fully functioning parts with high mechanical properties that may otherwise be impossible to develop with traditional manufacturing techniques, said Sculpteo Marketing Content Manager Hannah Bensoussan in a blog post .
To be sure, while 3D printing of metals is currently possible, it’s not easy, and it’s still fairly expensive due to the necessary use of complex procedures, she said. One of those procedures often includes the need to make multiple versions of single parts before coming up with a final product, which is time consuming and expensive.
Making it easier to use 3D printing to fabricate in materials beyond plastic is the next milestone for this type of manufacturing to make it more widely accessible. That’s in part the reasoning behind the development of the AMT suite, said Sculpteo CEO Clement Moreau.
“Metal 3D printing offers the possibility of building new parts with complex geometries that are not possible with traditional methods; however getting metal additive manufacturing right is a serious challenge,” he said. “As the complexity of additive manufacturing grows, it is difficult to get the necessary information to make the project go smoothly. Experts and specific software exist, but they are extremely expensive, and add to production time.”
Sculpteo already has made the first tool in the online suite—Business Case—available, with the others currently in development and will follow later.
Business Case is a “self-learning artificial intelligence” that can analyze the feasibility of a metal additive manufacturing project, calculate risks and opportunities, and provide advice in the case that there is a better material or technique to fit the project’s needs, according to Bensoussan’s post. The tool is available online.
Forthcoming tools in the suite are Smart Design Optimizer; Automatic Lattice Generator; Support Generator; Post-Processor; and Batch Control for 3D Metal Printing.
The optimizer takes a deeper dive into a 3D metal device to provide insight for shaping the object so it’s optimized for the process in terms of compatibility, thermal behavior simulation, and 3D printing orientation, Bensoussan said. It also will identify any problematic features that should be changed to get the best result.
The lattice generator also analyzes a design, but in a different way, taking a look at the force that will be applied to each part of the finished object. In this way, it can provide specific structural recommendations, such as where an object might have a lattice structure instead of a full structure. It also suggests lattice-cell designs and helps manufacturers to choose the best one, Bensoussan said.
The support generator is a key tool in the suite because proper supports are integral to product success or failure, according to Bensoussan. This tool analyzes a design and recommend the best way to arrange the supports to meet the part’s requirements, she said.
The post-process tool will help manufacturers prepare for the post-processing part of the additive manufacturing strategy, Bensoussan said. The tool allows them to evaluate how polishing, grinding, drilling, milling, and threading can be applied to a part for optimum results, as well as to calculate a timeline and budget for post-processing work.
Finally, the batch control tool—which Sculpteo already has released for white plastic parts—will soon be available for metal parts, as well. The tool provides an adapted price of production for small and medium series parts, as well as virtual control over the machine so that manufacturers can create production batches as they see fit, Bensoussan said.