I attended this year’s ICAM, the International Conference on Advanced Manufacturing, and filmed a variety of short video reports from the week-long event.
ICAM is hosted by ASTM international. The event this year drew 1,050 people from over 450 organizations, according to ASTM. The focus of the conference, now in its eleventh year, is additive manufacturing (AM), though the content has broadened in recent years to also address adjacent technologies such as robotics and industrial AI.
“Qualification” was the single-word theme of ICAM this year, or at least my experience of it. This is a departure from what I experienced as recently as ICAM in 2025. The scale of production in which AM is now applied and the extent to which AM is now accepted for production create a context in which the pressing challenge now is to find better qualification methods and acceptable qualification pathways to allow a broader range of AM parts and applications to enter scale production.
This picture of where we are with AM, and the way the state of progress intensifies attention on qualification, emerged in various video reports I logged during the ICAM week, which I am sharing here. Now that additive’s ability to deliver production is accepted, attention turns to both realizing and optimizing processes built on this potential.
Several aspects of this:
1. We Are Advancing Toward the Qualification Paradigm Suited to AM
The challenge of qualification in AM is that additive does so much at once. In contexts related to industrial part production, AM often specifically refers to laser powder bed fusion (LPBF), the primary additive process delivering high-value metal part production. In LPBF, the outer form, often complex, and the metal microstructure, often involving a novel alloy, are created simultaneously. And one affects the other. No other part-making process delivers part geometry and material properties with every digital layer in this way, so new validation methods are necessary to confirm these manifold outcomes.
In his ICAM keynote address, Michael Kenworthy of VulcanForms described the state of progress in getting to this qualification paradigm. Because inspection of the completed part measures too little to validate LPBF, qualification instead requires either rigid control of every variable of the process (including which individual machine runs a given part) or process monitoring sufficient to maintain a qualified window.
Here is my summary of the stages of advance, and where the next success needs to be found:
2. AM Process Monitoring Has to Confront the Large Volume of Potentially Meaningful Data
An LPBF build is a dynamic process in which the fluid dynamics of the melted material and the thermodynamics of the energy added to the part are process variables affecting the build in real time. Any monitoring system capturing enough data to meaningfully monitor the build will capture too much data (gigabytes per layer and terabytes per build) for processing and control in real time.
Prahalada Rao of Virginia Tech described a solution he has been involved in developing. It involves employing a real-time digital-twin simulation, combined with just enough monitoring and analysis to track departures from the twin:
3. Qualification Is Not a Singular Practice, But Different for Every Part
I logged some qualification stories at ICAM, involving the tactics used to validate AM production processes without the acceptance requirements posing too onerous a burden on the application. These two qualification successes came from Satya Ganti of Baker Hughes and Tyler Blumenthal of RPM Innovations, working on a NASA-funded component in collaboration with L3Harris.
4. Production Efficiency Is Governed by Workflow Factors (Just Like in Every Production Process)
Qualification challenges largely focus on the additive build, but efficiency challenges—the work of making AM as efficient as possible for production—will have to consider every step in the production sequence.
Matt Tusz of Magnitude Innovations gave a presentation on applying lean manufacturing principles to AM to expand production capacity. In LPBF, the metal 3D printer is generally not the pacesetter, he says. Leadtime delay is more apt to come from parts queueing for finishing:
5. Meanwhile, AM Itself Is Still Changing
The acceptance of additive manufacturing for production results in a strange tension, because AM itself is not a mature technology. Established processes such as casting or machining are subject generally only to incremental technology change, but systems for LPBF and other additive processes are still advancing rapidly enough that process expectations and even the parts that are practical for AM are likely to change in the coming years.
How many years? Prabhjot Singh of RTX in his ICAM keynote clocked a rate of exponential process advance paced in steps of four years. If there is a Moore’s Law for additive manufacturing, perhaps it is something like this: