Process optimization through AI

Improved KPIs, reduced energy consumption.

On-premise

AI Optimization

Physics-based

Digital Twin

Optimal control powered by Digital Twins & AI

Optimal process control often involves fine-tuning multiple highly correlated variables. Combined with faulty sensor readings or lack of data for any part of the manufacturing process, makes optimizing manufacturing processes difficult, slow and expensive.

AI and Digital Twins can fix this. Through GridMetrics’ platform, energy savings and improved KPIs can be achieved in days instead of months.

Digitalize and optimize

Digitalize the manufacturing process. Optimize it in a safe environment. Deploy it to control autonomously and efficiently. It takes days, instead of years.

Simulations based on physics and chemistry

Conduct experiments. What will happen to the infrastructure if you use H2 as a fuel? What about the GHG emissions? Would installing a larger pump be more energy-efficient?

Run what if scenarios
Visualize the energy and emission impact of equipment changes
Measure the impact of changes to the production process
Identify energy losses

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Optimize and automate by using AI

Algorithms that adapt themselves to the specific process. Dynamically, in real-time, improves multiple correlated parameters.

Automate multi-variable process Improve several kpis at once
Reduce energy usage
Improve process stability

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Generate process data & software sensors

Generate data for anything at any moment during the production process, without sensors.

Reduce sensor noise
Identify broken sensors
Software sensors provide measurements of physical quantities for which physical sensors are expensive or impractical
Generate vast amounts of sensor data that can be used for optimization or predictive maintenance

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