Machine Learning and Analytics: Process Engineers Don’t Have to Be a Data Scientist

It has never been easy for any industrial organization taking on a digital transformation jersey including machine learning and analytics.

With proven processes and software technologies namely GE Digital’s Proficy CSense, the journey to success with machine learning and analytics become achievable for every industrial organization.

Process engineers have exceptional domain expertise to put together process models – or Process Digital Twins – and be able to interpret the models. This is the foundation for improving competitive advantage and success with analytics.

To drive analytics and improve processes, process engineers can align domain expertise to five capabilities:

1. Analysis

Automatic root cause identification accelerates continuous improvement

2. Monitoring

Early warnings reduce downtime and waste

3. Prediction

Proactive actions improve quality, stability, and reliability

4. Simulation

What-if simulations accelerate accurate decisions at a lower cost

5. Optimization

Optimal process setpoints improve throughput at acceptable quality by up to 10%