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Welcome
Welcome
The overarching aim of this project is to develop a responsive approach to the manufacture of high value films, across a wide range of materials and thicknesses, centred primarily upon materials for flexible electronic devices. To achieve this aim, we will use state of the art, real-time, in situ, metrology data to feed into a combination of live process simulations and model based process optimisation and control algorithms via machine learning (ML), to allow the manufacturing process to respond to changes in materials, formulations, and processing conditions. This will speed up process optimisation, maximise process efficiencies and increase product performance.
Research Vision
We will feed state-of-the-art, real-time, in-process, film metrology data into live process simulations and model-based process optimisation algorithms derived from machine learning (ML) to enable continuously responsive and sustainable industrial manufacturing of high value film coatings (1→100 μm). We will address films formed by solid suspensions of insulators, dielectrics, conductors & semiconductors using continuous manufacturing approaches (slot-die, reel-2-reel (R2R), screen printing). Our extensive in-situ metrology and ML approach will give a deeper understanding of manufacturing to allow autonomous, real-time optimisation and control with improved processing efficiency, and optimised film functionality. Using this autonomous approach, we will develop, for the first time in this industry, more resilient manufacturing processes, agile to fast-moving developments in materials/formulations and changing end user needs. We align with the goal of driving up innovation and productivity as outlined in the RCUK development roadmap (July 2020) and the project falls squarely within the Digital Manufacturing priority area of EPSRC.
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