Global Manufacturer Improves Polymer Yield with Industrial IoT Solution

• Analytics & Modeling - Process Analytics
• Application Infrastructure & Middleware - Data Exchange & Integration
• Application Infrastructure & Middleware - Data Visualization

• Chemicals

• Process Manufacturing

• Process Control & Optimization

A global manufacturer seeks to improve production yield at polymer mixing process.

The company’s polymer mixing process was producing output of inconsistent quality, with yields sometimes dipping as low as 50%.

The scrapping of poor batches created huge costs and was crippling production capacity.

Dynamic product specification in addition to variation in a range of production parameters causing the trouble.

Hitachi's advanced analytics platform helped in integrating a wide range of production data and sensors data to visualize, analyze and diagnose the polymer mixing process.

Discovered the critical factors and optimal process parameters through correlation, visual analysis, and optimization algorithms.

Provided a deep process insight, enabling daily decision support and continuous improvement.

• Discovered the critical factors and optimal process parameters through correlation, visual analysis, and optimization algorithms.

• A deep process insight was achieved, enabling production teams in daily decision support and continuous improvement.

   

• Machine learning helped to further optimize the mixing process. 

• The solution eliminated over 50% of the poor quality batches, increasing the average yields to above 90%, and cause a Significant reduction in operating costs (multimillions of dollars).

   

• Increased mixing capacity with raised overall production throughput.