Artificial intelligence, coupled with machine learning, promises to improve plant operations from sensor level to the enterprise, but adoption has been slow with some overzealous starts.
A recent McKinsey article suggests that while many plants could benefit from the use of AI to accelerate process optimization, few are actually ready for it—from equipment on the plant floor to sensors and instrumentation, base-level controls, supervisory/advanced process controls (APC) and finally advisory models. The McKinsey report notes that 10% of plants use AI to describe, predict and inform process decisions.
Only 34% of plants have installed APC systems for critical unit operations, while 75% of plants have instrumentation and sensors in place, but only 70% of these instruments are properly calibrated and cataloged. Only 18% of plants have dedicated IT teams supporting AI solutions, and 60% of organizations have a change management strategy in place to use AI solutions in their current operations.