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From Fertilizer to Speciality chemicals, Chemical manufacturing is often complex even for very well experienced operators to take decisions due to a variety of challenges such as
- Non Homogeneous quality of raw materials;
- Complex process & Large lead time in chemical reaction process;
- Low operational visibility leading to Sub optimal operational decisions.
Leverage our Digital Twin solution to determine real-time decisions even for processes where sensor deployment is not possible.
Digital Twin for Chemicals
Our Digital Twin solution offers predictions for processes that are complex due to the presence of multiple variables, making it very difficult to predict, let alone optimization.
Use Case 1
Soft Sensor based predictions
Use Case 2
Advisory level plant control recommendation
Use Case 3
Supervisory closed loop optimization
- Multivariate, Deep learning (AI) model to Predict every Acid Quality
- Adaptive modelling approach to suit any variations to raw material inputs & operational regime
- Soft sensor to predict the product & intermittent process quality
- Reduced lead time (by up to 90%) between Quality process checks and Operator’s Action
- Low footprint AI Edge device implementation to predict quality parameters
- Advisory recommendation to control the plants for better operational excellence
Faster Quality Predictions
Operators to act swiftly (16 times faster) based on predicted quality.
Within 1st year our Digital Twins are delivering 95% model accuracy.
Soft Sensor based Quality Predictions
Help your Operator take faster actions, instead of waiting for lab results
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