During RAPID + TCT 2024, Bradley Rothenberg, CEO of Engineering software developer nTop, outlined how the company is driving the adoption of computational design for 3D printing.
North America’s largest trade show saw nTop launch nTop 5, the latest version of its flagship design for additive manufacturing (DfAM) software. Rothenberg outlined a slew of new integrations with the likes of Materialise and Autodesk’s 3D printing software.
How to use AI for 3D printing was also discussed. While the hype surrounding Artificial Intelligence (AI) continues to permeate the tech industry, the nTop CEO provided a more pragmatic view of its capabilities. He pointed to the automation of repetitive design tasks to save time and cut iteration cycles from hundreds to as few as ten.
Rothenberg highlighted the importance of software standardization and increasing the ease of 3D printing data transfer. He argued this could lower the barrier to entry and drive 3D printer adoption. However, achieving this will not be easy. The nTop CEO called data transfer “the biggest challenge for 3D printing software.”
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Introducing nTop 5: advancing computational design for 3D printing
nTop 5 is billed as a “leap forward in computational design technology.” What is computational design? According to Rothenberg, it is “the process of capturing requirements into a computer-understandable language like algorithms, and then leveraging compute to run those models and find the most optimal design.”
The software update reportedly enables users to “build, run and integrate the most powerful computational models into their products.” Rothenberg stated, “The industry today has never been under more pressure to deliver high-performance products.” He believes nTop 5 is optimized to meet these demands across the automotive, aerospace, defense, medical, consumer, and industrial sectors.
nTop’s software has previously been leveraged by Siemens Energy to convert its gas turbine engines to hydrogen power. Cobra Golf also used the platform to design the lattice structures of its 3D printed golf club irons.
Elsewhere, the company’s was used to design a 3D printed cylinder head for the marine and energy firm Wärtsilä. Developed in collaboration with Materialise and Nikon SLM Solutions, the part is 60% lighter than conventionally manufactured alternatives. The nTop-enabled design also integrated up to ten subsystems, reducing assembly complexity and improving cooling performance.
According to Rothenberg, “nTop 5 marks a really important moment for us.” This is due to new core modeling technology which offers improved precision and speed. Therefore, the software enables customers to “iterate really fast and find the best possible design.”
nTop also added five new software providers to its Core Developer Library. This includes Materialise Magics, Autodesk Fusion, cloudfluid, Hexagon scSTREAM, and Intact.Simulation, which now offer nTop 5 interoperability.
This will reportedly provide better end-to-end design, simulation and production capabilities for customers. Rothenberg believes this will help to “mature deployment of additive manufacturing and drive more adoption of computational design.”
How valuable is AI for 3D printing?
Rothenberg shared his insights on the practical value of AI and machine learning (ML) in additive manufacturing.
He described AI and ML as tools that can expedite problem-solving. The immediate value lies in AI’s capacity to “speed up similar types of problems,” providing engineers with faster, more accurate predictions. “We want to make sure our customers train up custom AI models from nTop, and they could use those models to speed up nTop,” added Rothenberg.
He pointed to applications like inverse design, where AI models streamline iterative processes. This approach allows for rapid convergence on optimal designs. One example relates to the retail and robotics company Ocado.
The firm trained its own AI model using a digital nTop representation to speed up the design of its 600 Series 3D printed grocery fulfillment robot. This approach reduced design iteration cycles from hundreds to 10 to 50.
Elsewhere, the Lawrence Livermore National Laboratory has tied an nTop model to traditional AI and ML techniques to find optimal parameter sets for structural design
However, Rothenberg explained that AI is “only as good as the model you train with it.” While it can accelerate repetitive tasks and predict outcomes based on existing models, AI is not poised to invent new solutions independently.
Instead, looking along the engineering toolchain, tasks that take hours or days to complete manually could be achieved more efficiently with AI-produced surrogate models. These tasks include full build simulations or fluid analysis, with AI enabling engineers to “get a better prediction on additive manufacturing outcomes.”
Overcoming 3D printing software challenges
Rothenberg identified “smooth data transfer” between different tools and file formats as the primary challenge for the 3D printing software space. He highlighted the importance of understanding “how to transition data.”
To overcome 3D printing design bottleneck, nTop offers Implicit Interop. This allows users to move design data between nTop, manufacturing, CAD, and CAE software using the company’s .implicit file format. It creates files up to 99% smaller than traditional meshes, allowing them to be generated 500x faster.
Rothenberg believes Implicit will become the industry-standard format for transferring design and simulation data. He added that the recent integration with Materialise’s Magics build preparation software supports this goal.
Discussing concerns over intellectual property (IP) and data security, the nTop CEO emphasized nTop’s desktop-based capabilities. This allows users to run software without being connected to the cloud, minimizing the risk of unwanted third-party data transfer.
Rothenberg also mentioned ongoing efforts to enhance file security, arguing encryption methods can safeguard shared IP. He outlined measures like Custom Blocks, which package IP into nTop files. The company aims to make these files lockable, with users requiring a key to access them after they have been shared.
Software standardization to increase 3D printer adoption
The nTop CEO believes software standardization will drive 3D printer adoption and scale additive manufacturing to production applications.
He explained, “It’s critical that customers can seamlessly integrate designs into their development processes.” Rothenberg argued that the integrations introduced in nTop 5 address this need, providing a more cohesive end-to-end solution for product development.
“We view 3D printing as a transformative manufacturing technology,” Rothenberg commented. However, 3D printing’s journey towards profitability and widespread acceptance will take time. He likened this process to the evolution of composites, “which took decades to reach mainstream adoption.”
While acknowledging the industry’s youth and ongoing financial uncertainties, Rothenberg is optimistic about its trajectory. He argued for a broader perspective on 3D printing, suggesting it should be considered a fundamental aspect of modern manufacturing rather than an isolated industry.
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Featured image shows nTop CEO Bradley Rothenberg at RAPID + TCT 2024. Photo by 3D Printing Industry.
