Increase Production Process Efficiency with Machine Learning

BHC3 Process Optimization applies advanced analytic techniques on top of operational data to improve production yield and process efficiency. BHC3 Process Optimization identifies process anomalies across systems, provides prioritized alerts and process KPIs, enables root cause analysis, and recommends optimization actions. Process and production engineers can use BHC3 Process Optimization to maximize production levels and optimize energy efficiency.

 

BHC3 Process Optimization Demo Video

View Data Sheet

Demonstrated Benefits

40%

Reduction in off-spec product

80%

Accuracy in detecting low-yield batches

15%

Increase in energy production

1%

Increase in process throughput

Next Generation AI-based Process Optimization

Issues
BHC3 Process Optimization Solution

Product yield is variable over time

Product yields and quality forecasted through advanced AI techniques to reduce waste and maximize production

Quality issues emerge without sufficient warning

AI predictions enable operators to act before a product issue emerges

Lab testing and related data are not integrated with operational data

Unified data from process simulators, operational systems, ERP systems, and asset management systems provide a holistic view of production process

Existing solutions do not handle all process types

Support for discrete, bath, semi-batch, and continuous production processes

Unpredictable impact of reactive solutions on quality issues

Integration of process simulators and optimization frameworks to evaluate what-if scenarios

Inefficient collaboration and triage

Enable operators to focus on high-priority issues and leverage AI-based prescriptive insights to support intervention

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