A Decision Intelligence Platform for FLexible, Agile, Resilient, and Energy-Aware Processes

FLARE will enhance the resilience of energy-intensive industries by fusing flexibility with AI-driven decision intelligence, and proactive energy orchestration into a single platform, providing a system that can withstand, adapt and recover from the volatility and fluctuations in energy supply, cost and operational needs. Next-generation process flexibility goes far beyond the ability to switch production lines quickly; it requires the ability to embed real-time intelligence, reconfigurability, and energy-awareness into the core of manufacturing workflows, dynamically adapting to shifting conditions with enhanced human decision making. FLARE's mission is to create an adaptive, self-optimising manufacturing ecosystem where production lines can reconfigure in real-time, in collaboration with domain experts (e.g. operators, planners, designers) that are supported by digital twins, AI, and predictive analytics. Process equipment will seamlessly switch between energy sources, aligning operations with renewable availability, market demand, cost & energy efficiency. Energy-aware scheduling, self-healing control systems, and human–machine collaboration will ensure that factories remain productive, sustainable, and resilient even in the face of volatility. FLARE addresses significant challenges related to process design, system complexity and integration, flexibility vs. efficiency, holistic sustainability and investment assessment, workforce readiness and change management, focusing on multiple energy-intensive sectors, including chemical, steel and cement. Specifically, FLARE will demonstrate a significant impact on these sectors, including energy cost reductions of 10–15%, CO2 emissions reductions of 15–20%, waste reductions of 10–15%, and improved flexible response times of 10– 15 minutes across these three high-impact European example sites that act as living laboratories and demonstrate a pathway from prototype to market adoption.