Additively Manufactured Metal Parts Have No Blanket Certification Pathway — Every Part Requires Bespoke Qualification

The AMSC Roadmap identifies 141 standardization gaps in additive manufacturing, 54 of which are high priority. The most consequential: no consensus framework exists for qualifying metal AM parts without destructive testing of every build. In aerospace, the FAA has no blanket approval pathway — each AM part requires years-long, bespoke manufacturer-regulator collaboration. The NRC faces the same gap for nuclear components. This means AM technology that is mature enough for serial production cannot be deployed at scale because the qualification burden scales linearly with production volume rather than being amortized across validated processes.

AM could transform manufacturing of complex, high-value metal parts across aerospace, energy, and defense — reducing weight, lead time, and waste. But qualification costs make AM economically uncompetitive for all but the highest-value one-off applications. Small and mid-sized manufacturers are effectively locked out because they lack resources for bespoke qualification programs. The AMSC notes a "capability gap between large companies and second/third tier suppliers" filled by "costly trial-and-error learning." Meanwhile, 91 of the 141 identified gaps require pre-standardization R&D before standards can even be written — the pipeline is years from completion.

The AMSC has published three roadmap versions since 2017. ASTM and ISO have published some AM-specific standards (e.g., ASTM F3572-22 for part classification, ISO/ASTM 52904:2024 for PBF processes). NASA developed its own internal standard (MSFC-STD-3716) because consensus standards were insufficient. The ASTM AM Center of Excellence has spent $4M+ across 30+ R&D projects since 2018. However, AM technology evolves faster than standards can be written — the diversity of processes (PBF, DED, binder jetting), materials, and machine configurations makes universal standardization extremely difficult. In-process monitoring technologies that could reduce qualification cost remain at low Technology Readiness Levels. Companies hoard process knowledge, preventing the shared datasets needed for industry-wide standards. Each sector (aerospace, nuclear, maritime) is developing its own parallel qualification framework, fragmenting the effort.

In-situ process monitoring that can provide real-time quality assurance — essentially proving a part is sound during the build rather than after. This requires standardized correlation between in-process measurement signatures (melt pool temperature, powder layer characteristics) and final part properties, validated at statistical scale. An adjacent analogy is how the semiconductor industry moved from destructive testing of every wafer to statistical process control based on in-line measurements.

A team could build a low-cost melt pool monitoring system for a desktop metal AM printer and attempt to correlate thermal signatures with post-build mechanical properties (tensile strength, porosity). Even a small dataset demonstrating signal-to-defect correlation would contribute to the pre-standardization R&D that NIST identifies as necessary. Relevant disciplines: materials science, mechanical engineering, computer vision, data science.