Metal 3D printers churn out knee implants riddled with tiny cracks and pores that current inspection methods often miss. These defects can cause implants to fail prematurely, but the standard quality checks are slow, expensive, and ill-suited to the complex shapes that 3D printing excels at producing. The problem is that sensors on the printers generate vast, messy datasets that require expert analysis, making rapid decisions about part quality nearly impossible. NEXUS, an AI software platform from Nexus Additive Ltd, solves this by analysing sensor data in near real-time to detect defects as they form. This project tests the platform on a real medical device: a fully 3D-printed unicondylar knee replacement being developed by UK manufacturer Osstec Ltd. If successful, NEXUS could remove costly post-production inspection as a barrier to adopting metal 3D printing for safety-critical, long-life components. That would accelerate the use of custom-printed medical implants and other engineered parts, quietly improving manufacturing reliability without patients or engineers ever noticing the change.
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When producing parts in metal by 3D printing, also known as additive manufacturing (AM), defects can occur. In common with other manufacturing processes, these defects may consist of cracks, internal pores or impurities, and these defects could lead to premature or unexpected failure of a part. To combat this, inspection and quality assurance processes are undertaken to ensure that no defects that would impact the safety of a part are present. However, the current approaches to quality assurance in AM are expensive and time-consuming, and they are often unable to detect critical defects in the complex geometries AM excels at. Data collected from sensors in the AM process help us understand the root causes of defects and can be used to identify anomalies in the manufacturing process. The challenge is that these datasets are large, complex and require significant expertise to analyse and it is therefore difficult to use the data to make rapid decisions about part quality. NEXUS is an AI-powered software platform being developed by Nexus Additive Ltd that overcomes these challenges and unlocks the value in the manufacturing sensor data. It detects defects in near real-time and enables machine operators to evaluate part quality, removing costly inspection processes as a barrier to adoption of AM. This project will take the NEXUS platform, which has demonstrated a promising proof-of-concept, and explore its efficacy in detecting defects in safety critical components which require long-service life. Nexus Additive will be partnering with Osstec Ltd, a UK medical device manufacturer aiming to bring the a fully 3D printed unicondylar knee replacement to market. This project will show whether the NEXUS platform can detect defects in an end-user's components and prove its value as a quality assurance tool to enable and accelerate the adoption of innovative metal AM components.
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