UK Food & Drink (F&D) manufacturing sector productivity levels need to be radically improved if they are not to make the sector fall behind international competition and place the UK F&D sector competitiveness & growth under threat. This low productivity is caused by high levels of product demand variability the effects of which are to reduce manufacturing effectiveness. The REACT technology aims to provide controls for managing flexible responses that counteract the effects of variability. In this respect REACT provides novel digital approaches to manufacturing productivity improvement that uses data modelling & analysis, and automated decision-making. Here, the REACT approach involves innovative use of models to measure the effects of variability and automated decision-making that uses these quantified effects to determine appropriate flexible responses. REACT also enables flexible resource responses to be made available at the right time, over the right period, in the right place, and of the right type and level. REACT provides flexible responses to variability that maintains the high productivity levels, low costs & high throughput rates, required to grow the UK F&D sector. When exploiting REACT its application to other manufacturing sectors, in & out the UK, will be pursued.

The project aim is to develop, for the food & drink sector, innovative technology that provides greatly enhanced resource usage efficiency & reduction in waste production both within individual food & drink companies but also across their supply chains. The Supply Chain Overall Resource Effectiveness (SCORE) system developed will extend existing performance improvement systems by greatly extending the range of performance metrics able to measure levels of resource usage inefficiency & waste production. SCORE will also add critical capability for identifying & permanently resolving root causes of resource usage inefficiency & waste production and enable prediction of emerging negative trends & sudden adverse changes. Innovative technology developed will develop advanced modelling capability for determining the precedence & causal relationships between individual SCORE metrics and use of these relationships to build simulation models for trend prediction & root cause analysis. Overseeing SCORE will be an autonomous decision system that selects optimum solutions for emerging & sudden resource efficiency and waste production issues.