SystemsML is deploying advanced control systems including model-predictive and AI-assisted control techniques for the safe and efficient operation management and control of industrial complexes. The cutting-edge control platform of SystemsML is implemented across all scales (lab, pilot, industry) in capital-intensive application sectors such as manufacturing, chemical process and energy systems for the operation excellence and economic value creation.
The key feature of SystemsML approach is the rigorous integration of uncertainty (from feedstocks to industrial-scale processes to supply chain disruption) in the digital twin platform that evaluates real-world uncertainty sources for the robust operation control and to achieve targeted value gains in economic, energy and environmental domains.
SystemsML is on the mission of unlocking actual potential of AI at safety-critical and capital-intensive industrial sectors (manufacturing, chemical processes, energy systems) where AI adoption remains marginally low despite $13 trillions economic value by 2030. SystemsML is revolutionising the conventional and low-performing control schemes of capital-heavy industrial assets with the robust data-driven and uncertainty aware digital twins capabilities for real-time, dynamic process control, process scheduling (short-long term) to maximally exploit renewable energy as well as prescriptive maintenance to ensure reliability and availability of the systems in the industrial environment of manufacturing, chemical processes and energy sectors.