Additive Manufacturing (AM) and Artificial Intelligence (AI) are two of the most exciting fields of technology today. There surely are immense synergies in both these technologies and AI-assisted 3D printing can quickly become then next frontier.
On one hand, 3D printing has revolutionised manufacturing and design, making it possible to create complex objects with ease. Meanwhile, artificial intelligence (AI) tools such as ChatGPT, MidJourney, Stable Diffusion, and Resemble have demonstrated their potential to transform the media landscape. These tools can generate art, articles, and stories in seconds using simple natural language text input. In fact, AI was used to create all of the images in this piece.
When 3D printing and AI converge, the potential for innovation is limitless. AM designers can optimise their creations to be stronger and more efficient by leveraging Artificial Intelligence. AI can even make the medium more accessible to everyone by reducing slicer tuning’s high skill ceiling to simple checkboxes. 3D printing and AI can work together to power the next generation of manufacturing.
Hubs spoke with thought leaders, journalists, and enthusiasts in the AM industry. Here are their predictions for the future of the industry.
Predictions for AI-assisted 3D Printing
Quality control
In the aerospace industry, even minor component flaws can have disastrous consequences. The solution is AI-enabled 3D printers, which can detect and correct errors before they occur. Additive Works’ AI-based software platform, for example, simulates the 3D printing process to identify potential issues long before you press the print button.
“In-print monitoring has huge potential for AI integration. We’re already seeing things like ‘Spaghetti Detection’ [utilizing computer vision and ML to detect print failures] becoming increasingly popular among desktop FFF (Fused Filament Fabrication) systems. I think we’ll soon see AI integrations enter the market that will predict and prevent failures in print jobs on high-end industrial metal or polymer printers, where a failed print can be very costly.”
– Jacob Wilson, Regional Manager at BCN3D Technologies
AI algorithms can effectively analyse the 3D model and compare it to the ongoing print process in real time. Temperature, pressure, and speed can also be closely monitored by the technology to ensure that they remain within the optimal range. In the event of any errors or deviations, the AI system can be programmed to make quick on-the-fly adjustments to address the problem.
“We can already see some implementations focused on guaranteeing a successful printing such as the Spaghetti Detector and the first layer LIDAR scanning on the Bambu Lab printers.”
– Ricardo Alcântara from VulcanoLabs
Generative design
Manufacturing capabilities have been democratised as a result of the widespread availability of consumer 3D printers and distributed manufacturing platforms such as Hubs. However, designing such objects still necessitates familiarity with both CAD and slicer software. Because of the inherent complexity of such programmes, most enthusiasts prefer to print pre-made designs available on sites such as Thingiverse rather than designing them from scratch.
CNET’s Senior Editor, James Bricknell, believes that AI will soon eliminate this barrier to entry by allowing even those with no technical knowledge to easily design their own 3D projects.
“The big AI improvement will be 3D model generation using things like ChatGPT. In the next few years, I think we will see programs that allow you to design complex geometries just by your voice. That will allow a lot of people more freedom to express their creativity,” explains Bricknell while championing the transformative potential of NLP-based AI tools such as ChatGPT.
Print optimization
To achieve the best print efficiency and quality, a variety of parameters, including layer height, infill density, path planning, and support structures, must be meticulously fine-tuned. Great results can be achieved by skilled technicians who understand the nuances of 3D printing. However, Mark Lamkin, co-founder of FYR Medical, believes that specialised AI tools will outperform even the most experienced technicians.
“We are quite good at finding patterns, but a neural net trained to iterate general 3D printing approaches toward a specific design goal (or a series of them), could result in new innovations and altogether different printing techniques. This could be [something] simple, such as improving layer fidelity, or more complex, like exploring novel combinations of manufacturing methods. Humans are very good at recognizing patterns, but we are slow compared to the speed of a computer.”
– Predicts Mark Lamkin, Co-founder of FYR Medical, while underscoring the superiority of AI’s iterative approach to problem-solving
However, it is not simply a matter of replacing human technicians. Mark, on the other hand, sees it as a positive development. AI can free up designers and engineers to focus on more important things like creativity and innovation by automating repetitive and time-consuming tasks.
Thailand’s Advancements in AI and Robotics: A Catalyst for Digital Transformation
Thailand has a strong connection to AI technologies. The country has been actively developing its AI capabilities since the 1970s through collaboration between the government, academia, and research institutes. The recent approval of the National AI Master Plan 2021-2027 and the National AI Strategy (NAIS) reflects Thailand’s commitment to bolstering its AI competitiveness, aligning with the country’s digital economic development and the National Strategy. This strategic focus on AI is aimed at advancing the country’s economy and improving the lives of its citizens, positioning Thailand ahead of its ASEAN peers in AI and robotics integration. Discussions on AI ethics have also led to the drafting of AI ethics guidelines in 2019, demonstrating Thailand’s proactive approach to the responsible development and use of AI technologies.
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Medical industry
Customized prosthetics, medical implants, and other products are already being produced across various medical disciplines, demonstrating the potential of 3D printing in industries such as healthcare. However, incorporating AI into the 3D printing process has the potential to take things to the next level.
Currently, creating personalised 3D models for patients requires the use of high-quality imaging to determine the specific needs of each case. This data is then passed on to a design engineer, who employs specialised software. Finally, the digital model is sliced into thin cross-sections for layer-by-layer printing. Some of these tasks can be automated with the help of AI. AI 3D printing tools, for example, can use medical data such as CT scans and MRI scans to generate personalised designs with minimal human intervention. This can significantly reduce costs and save valuable time for people who require urgent implants or prosthetics.
Resident 3D printing expert at Hubs, Robin Brockötter, believes AI will help doctors to play a more active role in the development of prosthetics and implants. “Specialized AI tools are set to reduce the complexity of the design process, making it easier for doctors and other healthcare professionals to be more involved in the undertaking,” Brockötter explains while underscoring the power of AI to give medical professionals tighter control over the otherwise prohibitively complicated and resource intensive process.
Given the significant changes that AI has brought about in fields such as art, literature, and software development, it’s reasonable to believe that it can also accelerate the development of 3D printing technology. In addition to making AM faster and more efficient, AI should make it more accessible and user-friendly, making it as simple to use as your average office inkjet printer.
