Self-learning universal AI to improve productivity in high-value metal additive manufacturing

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Metal-based additive manufacturing (AM) encompasses a wide range of technologies such as powder bed fusion, binder jetting and direct energy deposition. These processes are primarily used for manufacturing in demanding industries such as aerospace, automotive, medical, and energy. These industries require uniform part quality with properties like those achieved by conventional casting or forging processes.However, metal AM is highly prone to component failure - 3D printed metal parts are susceptible to manufacturing errors (e.g. high porosity, deformation, cracking) during the printing process. Up to 17% materials and valuable time is wasted via failed prints costing the metals manufacturing industry millions of pounds each year.Matta is developing a self-learning universal AI digital platform which leverages the latest AI research and the power of the cloud to bring intelligence to metal AM. Machine Learning is used to detect manufacturing errors and inefficiencies in the printing process, ultimately enabling error correction and prevention to improve resource and energy efficiency over time. Matta's aim is to autonomously detect errors as soon as they occur, stop the printing, and restart the print with automatically corrected settings. Failed prints are an avoidable waste of resources, materials, and energy for a product that is ultimately unviable, and can waste days if not weeks of time. In this project, we will apply our technology to the high-value UK metals manufacturing industry.We will collect diverse datasets of the metal AM process, develop state-of-the-art data science, build self-learning universal AI models to detect errors autonomously and apply them to a live demonstrator. The system will be built as a distributed network of metal printers connected via the cloud so each metal printer can learn from the experiences of others. In this way will create the level of intelligence required to ultimately achieve autonomous error prevention by recognising similarities between manufacturing runs, dramatically improving the productivity of the sector. This project is a natural stepping stone to the development and commercialisation of a total closed-loop AM system where crucial manufacturing parameters are automatically adjusted in real time without human intervention - an industry game changer!Matta is a spin-out from University of Cambridge. This project is critical to our extension from polymer AM to high-value metals manufacturing, where stakes are much higher. Since incorporating in 2021, Matta has also been building relationships with industry leaders such as the Manufacturing Technology Centre, GE, Cambridge, and Stanford.