In refineries and chemical plants, 42% of unscheduled downtime or slowdowns can be directly attributed to operator error. When looking at safety incidents, operational errors are also the most costly—an average $42M; more than those caused by design errors, process upsets, or mechanical failures.
Complicating this uncertainty is the rate at which operators and engineers are retiring. Someone with 20+ years of expertise has likely developed their own “best practices” and know which data to trust and when. As they retire, this knowledge becomes lost. New operators often lack trust in the data and the supervised (manual) machine learning algorithms that were built to manage it, and so they ignore alarms.
Better asset intelligence empowers the worker to make better, data-driven decisions with the confidence of accessible, trusted data (and without 20+ years of operations experience). This leads to significant OPEX savings due to higher uptime, higher production throughput, and fewer safety and regulatory incidents.