On Oct. 21, Schneider Electric, NVIDIA and Hewlett Packard Enterprise (HPE) announced a collaboration to develop artificial intelligence agents for industrial operations. The system combines HPE Private Cloud AI with Schneider Electric’s operational technology expertise to run AI applications closer to plant operations.

The companies said the approach is designed to address barriers to industrial AI adoption, including data security, cybersecurity risks and cloud computing costs. Processing data at the industrial edge also allows operators to maintain greater control over sensitive operational information.

According to the announcement, initial applications will focus on control-system monitoring, cybersecurity and energy optimization. The AI agents are designed to identify emerging problems, assess potential operational impacts and recommend or initiate corrective actions, with the goal of helping plant personnel troubleshoot issues and improve performance.

The development reportedly builds on Schneider Electric’s existing deployment at CMPC Chile, a pulp, paper and packaging producer that has used the company’s Operational Technology Monitoring System for three years to monitor control-system health and availability.

The companies said the AI agents could build on that monitoring capability to help operations and maintenance teams investigate problems faster while keeping personnel in control of critical decisions.

Why it Matters

Industrial technology providers are increasingly combining AI-based anomaly detection with tools that help engineers investigate equipment and process problems.

On Oct. 16, Chemical Processing reported that Seeq and Applied Computing had partnered to combine industrial analytics with an AI model for energy operations, initially supporting anomaly investigation for KBR’s industrial advisory services.

Both approaches are intended to help plant personnel investigate abnormal conditions and make operational decisions using industrial data.