In a 3D printing context, in-situ monitoring (ISM) generally refers to the use of automated processes to facilitate real-time quality assurance (QA) of parts, while they’re being printed. Companies in the industry are increasingly been pinning their hopes on the progress of ISM technologies to accelerate the scaled output of 3D printed parts.
As such, ASTM International, one of the world’s most influential standards organizations, has released a report called Strategic Guide: Additive Manufacturing In-Situ Technology Readiness Report. The report resulted from an ASTM Additive Manufacturing Center of Excellence (AM CoE) Specialty Workshop series on the subject, held in June, 2022, which was sponsored by NASA’s Marshall Space Flight Center (MSFC) and America Makes.
Last summer, the MSFC, located in Huntsville, Alabama, announced that it had selected Phase 3D (formerly Additive Monitoring Systems) to integrate its optical QA system into the NASA facility’s on-site, laser powder bed fusion (PBF) metal platforms. Phase 3D’s flagship Project Fringe system “uses structured light and machine vision” to detect defects as they occur.
While ASTM International did not specifically mention the company as a participant in the report, it is certainly at least hinted at by the involvement of MSFC, as well as by the fact that, according to Phase 3D, Project Fringe can be attached to any powder-based AM platform. In any case, then, it is a good bet that the company’s focus sheds light on the key themes at hand in the new guide.
This release also dovetails nicely with another newly released resource that ASTM International participated in producing: Authentise’s 3DGPT AM database, powered by OpenAI’s GPT-4. The two data sources are particularly relevant to one another insofar as a major objective of 3DGPT is to facilitate reduced waste in metal 3D printing.
Moreover, as the data related to ISM in the AM industry both expands and improves, there is a parallel urgency to integrate that data back into all the elements of the AM workflow process: and, subsequently, to improve the data yet again by collating as much information as possible on what is driving any and all improvements in the total AM ecosystem. As the industry continues to scale up, the observation and regulation of this feedback loop will obviously be highly prioritized, in the next few years, especially.
Although combining multiple emergent technologies always creates its own set of new challenges, it is nonetheless impossible to imagine the management of that feedback loop happening without the involvement of next-gen AI on multiple fronts. Thus, while it is already happening in seemingly every major industry, the urgency to cultivate specialists in the crossover between AI and other underlying technologies may initially be most pronounced in advanced manufacturing fields.
Featured image courtesy of ASTM
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