Productionizing AI in Manufacturing.

Your traditional process control techniques associated with costly energy consuming assets, i.e. boilers/compressors, are complex requiring an overwhelming amount of time and resources that don’t guarantee results and prove difficult to scale across the enterprise. This webinar seeks to bring awareness on how the Smart Industry community can adopt an Industry 4.0 approach in reducing real-time energy costs by taking an operational edge AI/ML framework in democratizing the implementation of industrial AI analytics solutions that can be implemented in a matter of minutes, all without having to become a data scientist or script any code.

Join us to explore:

• How maintenance/process engineers make are adding practical augmented AI intelligence to their PID techniques even in the midst of an existing Industry 3.0 infrastructure and control systems.
• How manufacturing citizen data scientists are improving common industry KPI’s such as KwH generated and Natural Gas consumed in real-time.
• How to configure an edge AI data driven operational baseline of your energy assets, not rules based or human subjectivity, in addition to mitigating the manipulation of your single source of truth.
• The techniques of deploying an edge AI operational digital twin ML model to forecast/recommend production and planning supply chain events.
• Why edge based AI can automatically optimize your process equipment parameters, reinforce a SMART dynamic setpoint in real-time and provide high levels of root causal analysis/fidelity and industrial problem solving!