Activities

 

Development of Virtual Soft Sensors using ML

Develop and embed Machine Learning Capabilities into HYPPOS to predict critical quality parameters at an early stage of the polymer manufacturing process where physical instrumentation is not available to optimise product grade transitions and minimize off-spec finished product.

Development of Plant Simulator

Develop and embed a plant Simulator into HYPPOS that takes historic data from a real Polypropylene plant and replays it in real-time.

Validation of HYPPOS-AI in Simulated Environment

Using the Polypropylene Plant Simulator, test and validate the performance of the ML module by comparing the predictions with the actual measurements.

Validation of HYPPOS-AI in Operational Environment

Testing and validating HYPPOS-AI at the HELLENiQ ENERGY polypropylene plant in Thessaloniki (Greece).

Branding and Promotion

Promotional material and campaign for raising market awareness and branding.

GENERAL PROJECT PROFILE      RESULTS      CASE STUDY      NEWS