The provision and supply of hand sanitiser has been in critically short supply during the Covid 19 crisis. This project proposes to convert underutilised food processing equipment, previously used to produce discretionary food and beverage products (condiments and sauces) to deliver 36000 litres per day of new capacity of hand sanitiser. The project will enable this change of product application by applying leading edge process control techniques to the machine control. The very different rheological properties of the food material and the hand sanitiser requires significant re-design and re-engineering of the equipment to deliver the new filling capability. The new control system will however have significant long-term benefits. The new control capability will provide a machine which has un-paralleled agility. The digitalisation of the whole system will enable the control system to re-configure the application to change autonomously from one diverse product to another, and also to monitor performance during the continuous operation of the machine to manage the performance and output quality with minimal interaction from operators. The changes will therefore deliver: Significant new capacity for hand sanitiser production; New design and digital operational capability for food and beverage filling equipment; Future system process agility for rapid changeover, remote fault monitoring and material property driven setup.

Achieving optimal efficiency in the post harvest handling and processing of rice is a ubiquitous challenge for China's agri-food sector. Rice is the staple food of 2/3 of population & it produces c. 1.3bn of quality rice p/a. This is insufficient to meet the aggressive population (13M p/a). This is due to land pressure & inefficient milling process handling resulting in an average 50% grain losses in machine batch processing. There are 6000 medium large mills across China operating at 50-60% efficiency rates. Conventional milling machines are manually operated & have no mechanism to responding to process variants (temperature, machine failures, contaminants) that can result in a whole milled batch being ruined. The project aims to develop a novel digital milling processes, supported by AI software platform that will intuitively respond & adapt to potential process failures, reduce milled waste & inject an additional 3MT of high quality rice (worth an additional £1.2bn to regional farming communities) into Chinese food chain p/a. 100% uptake would deliver 40MT (worth £12M p/a). This will be supported by a new business model, and education programme to support technology uptake and changes in work practice.