Rapid Fusion, a provider of LFAM solutions, has unveiled a new AI ‘print assistant’ that will help enhance the performance of its robotic additive manufacturing systems.
The UK-based company leveraged artificial intelligence to optimise its LFAM process, enabling customers to produce parts for the automotive, aerospace, construction, medical and military sectors.
After eight months of coding, troubleshooting, and various live tests, ‘Bob (Base of Build)’ is now being rolled out to existing clients and is promising to optimize its robots by making them easier to use, providing greater operator control, and ensuring less downtime through preventative maintenance.
The pre-loaded knowledge bank, anticipated to be one of the largest collections of 3D printing expertise ever created, works in both secure online/cloud-connected and offline/air-gapped configurations for military or IP-sensitive clients.
This works with Rapid Fusion’s models like Apollo and Zeus, and for its most recent system, Medusa, a large-format hybrid 3D gantry printer.
Martin Jewell, Chief Technology Officer at Rapid Fusion explained: “Having our own AI ‘print assistant’ is a game-changer and will cut machine downtime and boost efficiency. We’re teaching our systems to understand challenges and different scenarios, which means we can make the user interface more responsive and simpler to embrace – opening it up to all the workforce. In essence, if we can make our systems as ‘plug and play’ as possible, it means we will have more adopters. It’s a simple as that.”
Rapid Fusion, which employs ten people at its demo centre in Exeter, has factored in over 1000 different printing parameters into its AI language to come up with ‘best-in-class settings for more than 100 different components.
They feature smart extrusion readiness, which analyses the live temperature across four heating zones with rolling stability windows – in essence, providing confidence-scored go/no-go decisions using realistic heating/cooling profiles per material and pre-determined safety thresholds.
Material-aware intelligence also covers extensive variants, including carbon fibre composites and high-temperature polymers. When users say, ‘I need to print a high-temp mould tool,’ the AI accesses complete profiles considering heat deflection temperatures, mould shrinkage, thermal expansion, and mechanical properties for optimal configuration.
Martin went on to add: “There’s lots more. Task completion orchestrator operates three-tier intent processing; fast pattern matching for simple commands, AI interpretation accesses comprehensive material databases for complex requests, and advanced contextual understanding ensures accurate execution across all scenarios.
“Finally, the AI temperature command handler includes ‘smart chained’ intentions that combine multiple actions. For example, natural requests trigger automated sequences selecting appropriate materials, configuring multi-zone temperatures, evaluating post-processing requirements, and optimising based on embedded engineering data for the specific application.
“It’s feature rich, has a modern user interface, is completely secure and, importantly, has been built for universal integration and agent flexibility, meaning it can be shipped with either an OpenAI-powered agent or a locally hosted AI agent for online/air-gapped use.”
He concluded: “There’s a massive pre-loaded knowledge based, covering all our products, maintenance guides, troubleshooting and practical print flows. We believe we’ve come up with a ‘true’ additive manufacturing knowledge bible.”
There will be two levels of users to start with for Bob. Firstly, a super user, like a trusted partner or University, who can continue to inform and iterate the way Rapid Fusion do things.
Secondly, there will be a standard offer released at the start of 2026 for everyone who has one of the company’s systems. With upgrades able to be sent through the air, there is always the ability to improve and support customers even more – the era of smart 3D printing is well and truly here.
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