a potential route to transform manufacturing processes, whereby engineers no longer specify process parameters such as temperatures or pressures but instead specify quality or output requirements. In the context of composites this could be specifying the need for a fully infused part, or a defined degree of cure. The manufacturing system comprises Artificial Intelligence models, which utilises sensor information to control actuation systems, and then steers the manufacturing process in real time to deliver the desired output. Adaptive Manufacturing is a subset of Digital Twinning, and much of the deployed technology used can also serve additional functions such as developing digital part passports or performing automated part quality assurance. The EngD project will:

• Explore the concept of adaptive manufacturing technology readiness and accelerate its adoption into industry.
• Train machine learning (ML) models to monitor processes is real time to identify defect evolution and take corrective action.
• Investigate the possibility of using the data collected during the manufacturing process as a means to automatic quality assurance.
• Build and deploy system components such as ML models, sensor arrays and actuators into physical demonstrators that showcase the benefits of adaptive manufacturing in operation.
• Excite your interest in developing right every time composite manufacturing procedures that can be used in a wide range of processes.

Eligibility: Home/permanent UK residents subject to security clearance

To apply please submit a personal statement, outlining your experience and why you are interested in the EngD project, your CV and transcript of results to the application portal. Please include the project title in the project description field and select EngD in Composites Manufacture. Please enter Professor Janice Barton the Director of the CDT as the 2nd supervisor and indicate that the funding is provided by the CDT in Innovation for Sustainable Composites Engineering.

a potential route to transform manufacturing processes, whereby engineers no longer specify process parameters such as temperatures or pressures but instead specify quality or output requirements. In the context of composites this could be specifying the need for a fully infused part, or a defined degree of cure. The manufacturing system comprises Artificial Intelligence models, which utilises sensor information to control actuation systems, and then steers the manufacturing process in real time to deliver the desired output. Adaptive Manufacturing is a subset of Digital Twinning, and much of the deployed technology used can also serve additional functions such as developing digital part passports or performing automated part quality assurance. The EngD project will:

• Explore the concept of adaptive manufacturing technology readiness and accelerate its adoption into industry.
• Train machine learning (ML) models to monitor processes is real time to identify defect evolution and take corrective action.
• Investigate the possibility of using the data collected during the manufacturing process as a means to automatic quality assurance.
• Build and deploy system components such as ML models, sensor arrays and actuators into physical demonstrators that showcase the benefits of adaptive manufacturing in operation.
• Excite your interest in developing right every time composite manufacturing procedures that can be used in a wide range of processes.

Eligibility: Home/permanent UK residents subject to security clearance

To apply please submit a personal statement, outlining your experience and why you are interested in the EngD project, your CV and transcript of results to the application portal. Please include the project title in the project description field and select EngD in Composites Manufacture. Please enter Professor Janice Barton the Director of the CDT as the 2nd supervisor and indicate that the funding is provided by the CDT in Innovation for Sustainable Composites Engineering.