7 Important Ideas in Additive Manufacturing Right Now

Advances, successes and needs in AM today, as described in video reports from the International Conference on Advanced Manufacturing (ICAM)

Oct 18, 2025

Last week I attended the International Conference on Advanced Manufacturing (ICAM), where I worked with the ASTM International multimedia team to produce video reports on some of the ideas that caught my attention at this event.

ICAM (held in Las Vegas this year) drew about 1,100 attendees who came to see hundreds of generally engineering-focused manufacturing technology presentations. The conference is hosted by the ASTM Additive Manufacturing Center of Excellence, and in the past, the event has been strictly about additive manufacturing. The “AM” in the name used to stand for this. The show is still predominantly about additive, and in part this is because the welcoming of other technologies related to AI and automation serves to address additive manufacturing even more thoroughly. These digital manufacturing technologies interrelate and aid one another. For example, the link between AM and AI was apparent throughout the event, with many presenters sharing use cases or research leveraging both in one way or another.

Indeed, one of the important AM-related developments I identify below involves an advance that—seemingly—has nothing to do with 3D printing. Yet I see the connection to additive, and I talk about it in the video on this development below (point 5).

Taken together, these points I was able to report from the show offer a picture of the current state of AM’s advance, and where it is delivering new promise or feeling new pressure right now.

Here is some of what struck me during the week-long event:

1. The Cost Premium Separating Additive from Other Processes Is Coming Down

Cost economy often limits where additive can find its wins, but the cost gap separating additive manufacturing from other metalworking processes is getting smaller. I saw that theme come out in various ways.

Vladimir Navrotsky of Siemens Energy, in his keynote reporting on his company’s advances with additive, commented on the price gap between AM and investment casting. New productivity enhancements such as beam shaping in laser powder bed fusion will go a long way toward closing it.

And John Calhoun of CADmore Metal described how the company is bringing Cold Metal Fusion to North America. This is the process leveraging polymer selective laser sintering to produce metal parts, sometimes at lower cost compared to other metal AM options.

2. AM Offers New Possibilities for Responsiveness Addressing Military Need

In a keynote talk, Jason Bridges of Lockheed Martin spoke of the current predicament of the military industrial supply base. It has become leaner since the end of the Cold War, but also brittle. Now, in the current world, we see we may need the supply base to scale up again quickly.

Toolingless manufacturing via additive offers a way for military suppliers to scale production with little lead time, he says, if we can get out of additive’s way and let it do so. Questioning and limiting data reporting for additive parts is one aspect of this he sees.

In another presentation, Benjamin Wolf of the German military spoke about additive for responsiveness in a more focused way. The military needs to own drone production, he says. The war in Ukraine taught this, how drone and drone component suppliers can be cut off. The German military is developing its own drone production capability using additive manufacturing.

3. Platform Change in AM Still Offers Significant Room for Capability Advance

Michael Tucker of ETH Zürich is part of a team that has worked to develop an idea in laser powder bed fusion (LPBF) additive manufacturing that is outside the box in a literal sense. The company’s Rapture system is a cylindrical LPBF machine. The recoater moves continuously in a rotary path. The laser scans in polar coordinates.

Tucker has spoken about this system at ICAM in the past, but what is new this year is the way the reconceived platform is revealing its promise for capability advance. The continuous recoater is ideal for multi-material builds, he says—an option more difficult to achieve using the back-and-forth recoater of a box-shaped LPBF machine. Cylindrical rocket engine parts could more easily be made from copper and Inconel together, the two metals combined in a solid part made from a single build using the cylindrical machine.

4. A Scaling Opportunity Waits for Increasing Systemization of AM Machines

To scale additive, centralize programming the machines.

In his keynote talk at ICAM, Thomas Pomorski of Ursa Major described the company’s success using a universal slicer to program LPBF machines from seven different OEMs. A build defined once has been successfully translated for seven different machines. They’ve proven this with various builds. (In the video, I mistakenly give a smaller number than seven.)

Programming for machining already works this way. That is, one environment creates programs for many different machine tools. Shouldn’t additive work this way as well?

Ursa Major worked with Dyndrite on the solution it has validated. Pomorski sees this kind of centralization as part of what it will take to scale up production by dramatically increasing the number of AM machines in use in one network or facility.

Bonus: The centralized programming opens the way for AI to be part of the solution as well. More in the video:

5. Systemized Subtractive Operations Offer Promise for AM Postprocessing Needs

Are robots ready for AI?

Mostly no. Many robot applications are silos. But that may change. What will happen once robot cells integrate not just hardware, but data as well?

Tyler Bouchard of Flexxbotics spoke about his company’s data centralization system for automation, in which read/write capability for every machine in the robot cell is integrated and consolidated. He described the coming AI opportunity for robot cells this will bring.

I see this directly aiding additive manufacturing. For AM to be cost-effective for more of production, the steps downstream from the additive build will have to be cost-effective. That is, postprocessing either needs to be minimized or eliminated, or else it needs to be as automated and as lights-out as the 3D printing. Material-removal cells that are robot-handled and AI-controlled offer the way to achieve this latter need.

6. AM Offers an Economically Viable Solution for Reducing Plastic Waste

Can 3D printing reduce waste plastic heading to landfills? Yes. There is a path and it’s working.

Carolyn Seepersad of the Georgia Institute of Technology spoke about her work with ReCreateIt Labs, which is making home goods out of waste plastic that are sold through a store run by Habitat for Humanity International.

The ground plastic from bottles and other sources is 3D printed on a Gigabot machine from re:3D Inc.

There are challenges. They include:

Engineering challenges. How can the plastic “flake” made from ground waste plastic be made more printable?
Product challenges. What are the items to be made from this material that different customers with different interests most want to buy?

The team is rising to these challenges, and while the solution they are finding cannot account for all waste plastic, it clearly could be scaled beyond the scope of just this project. More in the video:

7. Geometric Freedom Can Deliver Mass Customization at Minute Levels

“Patient-matched” implants: The term usually refers to individualized orthopedic implants tailored to overall dimensions of a patient’s bone. But what about also matching the porous structure of an individual section of bone?

According to Jacob Peloquin of North Carolina State University, additive manufacturing can do this, too, and AI will get us there. He gave a talk on research into patient-matched osseointegration geometry.

Our bone structure is not identical from person to person, he notes. It is not even identical throughout one person’s body.

The system the NC State research is developing relies on high-resolution CT scans. AI agents work from this data to tailor an implant’s bone-ingrowth lattice to match the distinctive bone geometry, to better encourage natural bone growth into and around the geometry of the implant. The result is an implant that is patient-matched in more ways than one.

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