Daghan Cam and Luke Rodgers from Ai Build discuss how AI simplifies large-format 3D printing.

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Artificial Intelligence (AI) has been a hot topic in the tech world lately, and it’s no surprise that the additive manufacturing industry has also jumped on the AI bandwagon. According to a recent survey, automated AI 3D model generation is seen as a crucial factor in the future of 3D printing. One company that has been ahead of the curve in this regard is Ai Build, a London-based software developer specializing in 3D printing.

Ai Build was founded in 2015 by Daghan Cam and Michael Michail Desyllas, both of whom come from an architectural background. Their mission was to simplify large-format 3D printing, which they saw as the future of manufacturing. However, they quickly realized that 3D printing technology was prone to errors, especially when it came to larger formats.

One of the main challenges they identified was the dependence on experienced machine operators to turn designs into physical parts. This limited the development and widespread adoption of 3D printing. To overcome this, Cam and Desyllas aimed to make the technology more accessible. They wanted to create a solution that would allow even designers with limited 3D printing experience to send their designs directly to the machines.

To achieve this, Ai Build turned to AI technology. By automating tasks and optimizing the printing process, they aimed to make 3D printing more efficient and cost-effective. The company has partnered with several leading 3D printer hardware manufacturers, including Meltio, KUKA, Evo3D, CEAD, and Massive Dimension, to incorporate a wide range of large-format 3D printers into their Ai Lab workshop. This collaboration allows them to test, develop, and integrate their software for various applications.

One significant achievement for Ai Build was their partnership with Meltio, a metal 3D printer manufacturer. Through this collaboration, Ai Build was able to adapt their software for Direct Energy Deposition (DED) metal 3D printing. This opened up new opportunities in the metal printing market and further solidified Ai Build’s position as a key player in the industry.

Being based in London has also been advantageous for Ai Build. Cam emphasized the city’s strong engineering ecosystem, particularly in software development and AI. London provides access to a vibrant community of software and tech companies, which has helped Ai Build thrive. However, it’s worth noting that Ai Build’s reach extends far beyond London, with employees from various nationalities and a global presence.

Ai Build’s flagship product is AiSync, an AI-driven software platform for toolpath optimization and quality control. By leveraging AI algorithms, AiSync optimizes the toolpath generation process, resulting in faster and more efficient 3D printing. In addition, the software provides automated quality assurance, ensuring that every print meets the required standards.

In conclusion, Ai Build is at the forefront of AI integration in the additive manufacturing industry. Their mission to make large-format 3D printing more accessible and efficient has led to groundbreaking advancements in toolpath optimization and quality control. With partnerships with leading 3D printer manufacturers and a strong presence in London’s tech ecosystem, Ai Build is shaping the future of industrial 3D printing.

It was earlier announced this year that Ai Build had developed a groundbreaking process that allows users to create advanced 3D printing toolpaths using natural language prompts. This feature, called Talk to AiSync, enables users to input simple text commands, such as “slice the part with 2mm layer height,” which is then translated into machine instructions to produce the desired 3D printed part.

The key to this feature is the use of large language AI models. AiSync utilizes OpenAI on the back end, with GPT-4 running the software’s natural language processing. By implementing large language models, Ai Sync is capable of translating simple English words and plain sentences into a stack of workflow commands created within the software. The main objective of this feature is to make the process easy and accessible for inexperienced users by providing a smooth user experience.

Once the toolpath has been sent to the 3D printer, AiSync offers machine-learning-driven quality control. Traditionally, large-format 3D printing has had a success rate of only 40% when printing a part for the first time. However, by using machine learning and combining it with the initial toolpath, AiSync claims to achieve a first-time print success rate of over 90%. This improvement is expected to significantly reduce the need for additional testing and qualification, making it particularly beneficial for industries like aerospace that require certification and quality assurance.

AiSync also records the entire 3D printing process and automatically detects any anomalies that were not planned during the simulation phase. This feature is highly advantageous in sectors such as aerospace, automotive, energy, marine, and construction. Ai Build estimates that 80-90% of their customers belong to one of these five categories. While specific customer names couldn’t be disclosed, major companies such as the engineering solutions firm Weir Group and aerospace manufacturer Boeing were mentioned as key customers utilizing the AiSync software.

One distinguishing feature of Ai Build’s solution is its cloud-based platform. According to Ai Build, they are the only company that has a cloud platform driven by data, collaboration, and AI. This cloud connectivity not only allows for remote monitoring and control of 3D prints but also enables data transfer and testing between different locations. For instance, toolpaths created in Ai Build’s London-based Ai Lab can be sent to a 3D printer in Germany, allowing for parts to be printed without any additional human intervention.

By incorporating AI technology into additive manufacturing, Ai Build aims to achieve full automation, which they believe is crucial for scaling the technology. Without automation, the additive manufacturing process is susceptible to errors and heavily relies on the knowledge and expertise of additive engineers. Ai Build’s goal is to fully automate the process, with AI playing a crucial role in the final stages of automation. While AiSync currently offers a collaborative process between users and software, it is expected to evolve towards higher levels of automation, resulting in a more efficient and cost-effective process.

In summary, Ai Build’s Talk to AiSync feature revolutionizes 3D printing by allowing users to create toolpaths through natural language prompts. The use of large language AI models and machine learning-driven quality control ensures a high success rate in first-time prints. The cloud connectivity enables remote monitoring and control, as well as the transfer of data and tests between different geographies. The ultimate goal is to achieve full automation, making the additive manufacturing process more efficient and less costly.

The impact of AI in the field of additive manufacturing is undeniable. According to Cam, the time and cost savings offered by AI are highly dependent on the specific application. When it comes to tooling applications, the biggest advantage of AI lies in cutting down the prototyping phase. In the current scenario, engineers often have to rely on guesswork when it comes to slicing software and toolpath generation. They need to physically 3D print the part to view the results, which in turn takes a few attempts before getting it right. This process can take weeks before actual production begins, and in some cases, engineers might need to go back to the design phase and iterate on the design as well.

This is where AI modeling and simulation come into play, making a significant impact on the development stage. It eliminates the need for prototyping before production starts, saving both time and cost. In the case of high-volume production, AI primarily benefits quality assurance. Building trust in the technology is crucial for customers, and this is where AiSync, an AI-powered system, plays a vital role. It integrates quality assurance into the additive manufacturing process, providing live and post-print reports that instill full confidence in the customer.

Looking to the future, Cam envisions a promising relationship between AI and 3D printing, considering AI as a strong companion to engineers and designers. Effective communication between computers, systems, and humans will be the key component of this relationship. The goal is to make the communication so seamless that it feels like conversing with a colleague rather than a machine. Rodgers agrees with this vision, stating that technical competence will no longer be a requirement to operate machines in the future.

The long-term goal of AiSync is to simplify the additive manufacturing process even further, making it accessible to a wider audience and enabling the production of parts at a higher quality, faster, and with more accuracy than any human mind can achieve.

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If you’re interested in a career in additive manufacturing, visit 3D Printing Jobs for available roles to kickstart your journey in this exciting industry.

Image Source: Ai Build CEO Daghan Cam at Ai Build’s Ai Lab. Photo by 3D Printing Industry.

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