DIGF-DIRF-06956 - Missy Enhancement

The project aims to develop and demonstrate a data-driven intelligent control system for forming and machining processes in high-value manufacturing. It will link the forging operations at AFRC with the machining processes at AMRC, forming a pseudo supply chain to enhance insights into product quality and cost efficiency. A hybrid cloud/on-premises data infrastructure will ensure secure data sharing. Activities include designing, manufacturing, inspecting, and testing components, as well as sourcing hardware and software solutions. Advanced analytics will be used to drive process improvements, with gradual integration of machine learning for achieving artificial intelligence capabilities.

The main challenge is to establish an efficient data infrastructure that connects different Research and Technology Organizations (RTOs) to support advanced analytics, improve process insights, and enhance forming and machining operations. This includes overcoming challenges in data sharing between RTOs like AFRC and AMRC, ensuring data security, and integrating big data and machine learning for manufacturing optimization.

I am leading WP4, which focuses on developing a sustainability reporting framework for the collaborating company. My responsibilities include direct communication with the collaborating company’s sustainability team, managing data collection from the forging team at AFRC, and ensuring integration across teams. I am accountable for the final deliverable of this work package and have been managing a sustainability engineer on the project. Additionally, I am researching and aligning the sustainability framework to the company’s practices for optimal results. Given the multi-centre nature of the project, I also collaborate closely with the AMRC team to replicate this approach for their manufacturing processes.

The project aims to significantly enhance the quality and cost efficiency of forming and machining processes through data-driven insights and inter-RTO collaboration. A hybrid data strategy will ensure secure data sharing while enabling advanced analytics capabilities across different levels of the organization. By integrating big data and machine learning, the project seeks to create a smarter and more responsive manufacturing process, enhancing competitiveness in digitally-enabled high-value manufacturing. The collaboration between AFRC and AMRC will foster innovation in both process quality and production efficiency.

This project was funded by the MUSIC project and was costed at £60,143.