Prateek Kathpal, President and CEO of SymphonyAI Industrial.

How is AI transforming additive manufacturing, and what key areas are seeing the most innovation?

Artificial intelligence is revolutionising additive manufacturing at every phase from design optimisation to production efficiency. This layer-by-layer manufacturing approach utilises AI to assist with activities from initial design processes—where it can evaluate different model perspectives before printing—to quality control and error detection downstream.

What role does AI play in real-time process monitoring and defect detection during 3D printing?

During process monitoring and defect detection during 3D printing, AI improves quality, reduces waste and optimises printing parameters. The technology detects and corrects mistakes early in the printing process, thus significantly reducing downtime and costs to reprint the products or purchase additional materials. Industry reports suggest that as many as one third (33%) of all 3D prints will result in waste, so this technology presents an opportunity to decrease the waste, cut costs, and deliver efficiencies.

How does machine learning help in optimising printing parameters to reduce waste and improve quality?

Machine learning helps optimise printing parameters to reduce waste and improve quality by analysing vast industry-specific datasets to determine the most efficient configurations. Using this data, the LLMs can learn and provide insights that will lead to faster design and print times, reduced material waste, and improved product quality.

What are some of the biggest challenges in traditional 3D printing that AI is helping to overcome?

AI has the power to help in many different areas of manufacturing, including 3D printing. This technology is particularly valuable for low-volume manufacturing scenarios where traditional methods requiring expensive dies or casts would be cost-prohibitive.

AI algorithms can analyse numerous design alternatives quickly, helping engineers select optimal configurations before printing. This capability is especially useful in generative design, where multiple iterations are generated based on performance criteria.

What about addressing the skills gap?

As manufacturing faces growing skills gaps, AI and generative AI tools are helping to bridge these gaps through automated error checking and design refinement, effectively creating a "what-if" modeling capability for 3D printing applications. The true value proposition emerges when AI connects the entire manufacturing ecosystem—from maintenance and production to supply chain and retail—creating a comprehensive solution that optimises efficiency and reduces costly production downtime. With generative AI applications on a connected manufacturing ecosystem, even inexperienced team members have instant, natural-language access to help them do preventive maintenance, troubleshoot issues at any point in the manufacturing process, access relevant documents, or pull in colleagues with special expertise.

In what ways can AI optimise AM supply chains, from raw material sourcing to part delivery?

The impact of AI in additive manufacturing extends far beyond the printing process itself, creating value through integration with broader manufacturing operations. AI technologies are not limited to improving additive manufacturing itself; they also integrate with broader manufacturing systems by enabling predictive maintenance, managing raw material inventories, and forecasting demand, which in turn optimise production schedules and ultimately drive the most efficient overall manufacturing throughput.

What are the most exciting AI advancements shaping the future of additive manufacturing?

AI-driven predictive maintenance helps anticipate critical asset failures before they occur, reducing downtime and maintenance costs. For example, companies like NVIDIA are developing sophisticated solutions such as lattice graph neural networks, which create comprehensive knowledge graphs of manufacturing assets and processes. These integrated systems provide a complete model of production, identifying areas for improvement and optimisation.

Additive manufacturing AI tools are also gaining traction in the automotive and electronics industries. These AI-powered tools support the design of circuit boards and components while considering supply chain constraints and customer demand. And as I mentioned earlier, domain-specific industrial copilots can provide instant, contextual content and guidance, reaching into the full range of dataops sources and specialised LLMs to most effectively assist connected workers.

What advice would you give to companies looking to integrate AI into their additive manufacturing workflows?

When integrating any new technology into an organisation, it's important first to define your goals and see where the technology can make the most real-world impacts. As good data is the base of any impactful LLM, it is vital that manufacturers first have valuable data before integrating AI into their additive manufacturing processes. This comprehensive, accurate, specialised data will make for better AI and, in turn, make the AI more impactful.

Dassault Systèmes and Airbus extend strategic partnership to use virtual twins

Dassault Systèmes and Airbus have extended their long-term strategic partnership, putting the 3DEXPERIENCE platform at the heart of lifecycle management of all new Airbus programs for civil and military aircraft and helicopters.

This deployment will support the entire development chain for all Airbus civil and military aircraft and helicopters. More than 20,000 users from every business area, as well as Airbus suppliers, will be able to collaborate more effectively and use virtual twins – on premise or on a sovereign cloud – to shorten development cycles, anticipate and improve production efficiency, and enhance aftersales support – all while reducing costs.

"Digitalisation is a key enabler that we are leveraging to support our core priorities, whether it is ramping up the production of our commercial aircraft, preparing the next generation of platforms that will further contribute to the decarbonisation of our sector, or pioneering the defense and security solutions of tomorrow," said Guillaume Faury, CEO, Airbus. "This renewed partnership with Dassault Systèmes will play an important role in accelerating our progress towards these goals, while ensuring the highest levels of quality, safety and security throughout the lifecycle of our products and solutions, from design to in-service operations."

"Our long history of collaboration with Airbus embarks on its next chapter, enabling the entire enterprise and its value chain to innovate globally, efficiently and virtually for decades to come. Airbus can take full advantage of AI-powered generative experiences, and scientific advances in material science, modeling, simulation, production and operation systems efficiency with our 3DEXPERIENCE platform. This will open new possibilities to imagine, create and produce the experiences that will define the future of the aerospace industry," said Bernard Charlès, Executive Chairman, Dassault Systèmes.

Dassault Systèmes will provide Airbus with seven industry solution experiences based on the 3DEXPERIENCE platform:  "Program Excellence," "Winning Concept," "Co-Design to Target," "Cleared to Operate," "Ready for Rate," "Build to Operate," and "Keep Them Operating."