3D modelling and 3D printing workflows are to become much simpler thanks to Artificial Intelligence (AI) according to Dan Barousse.
The Slice Engineering CEO discussed AI’s impending impact on the additive manufacturing (AM) space on this week’s Additive Insight podcast.
Barousse was speaking on the topic as the leader of a company that is implementing AI across its business. So far, Slice Engineering, an extrusion 3D printing equipment manufacturer, has leant on the capabilities of AI for marketing, web design, programming, and firmware modifications, and anticipates the technology will eventually aid its design engineering output.
But the immediate success of AI in AM will depend, of course, on the application and the environment.
“I would expect that the average non-technical users’ experience with 3D modelling and the whole 3D printing workflow is going to become much more AI-enabled and simpler much faster than in medical, defence or aerospace,” Barousse said, “because it’s not a life-saving application or a mission critical application. In those applications, I think you are going to see a cross check for, for example, generating drawings for parts. Generating the drawings on the back end and doing the tolerancing, for me, is the tedious work. But you still need someone to check your drawings and that person typically needs to be a professionally licensed engineer in a mission critical or life-saving application.”
For many years, Barousse said of AI, there will need to be a certain level of ‘guess and check.’ But the ‘check’ element of that process will likely always be necessary, which is important to note given the hype around AI technology.
In a hypothetical scenario where AI is implemented in, say, the design of a component, then quality checks and defect detection will still be required further along the workflow. Despite concerns around the technology removing jobs, the design authority and responsibility for a part has to lie somewhere, and therefore, the need for design engineering skills remains.
“You will still need a user with a lot of background knowledge and understanding,” Barousse said. “I think about when I got my engineering degree, I learned a lot of math that I have never used in my career, but the math taught me principles that are then applied in the CAD software or in the finite element analysis software or in the thermal transfer software. And if I didn’t have the background knowledge of how the model is supposed to work based on the mathematics, then I would not be able to detect an error in those platforms.”
