IoT GUIDE

Due to the complex, energy-intensive, and potentially hazardous and environmentally sensitive nature of most downstream petroleum refining, petrochemical, and chemical manufacturing processes and facilities, these sectors have traditionally relied upon automation and other operational technology (OT).  In recent decades, much of this investment has shifted to operational risk management software applications that reside above the control layer and to information technology (IT); with gradually increasing convergence between the OT and IT domains.

Operational data tends to be scattered throughout multiple disparate information sources, both real-time and transactional in nature. Typical systems of record include process historians, lab systems, work order management systems, asset information system, inventory management systems, operator logs, and plant asset management systems.  Increasingly, IIoT-connected smart devices and applications represent additional disparate data sources.

A clear understanding of operational risk requires insights into many of these systems with the underlying data in context. Workers and staff are too busy to establish and create this context using conventional historian tools. Organizing this data from multiple sources and providing context is complex, but essential. Industrial IoT adds more sources of information and more complexity to the data available to analyze different operational problems.

There is a clear trend to provide plant personnel with better decision-support tools to improve plant performance and better manage operational risk.  Industry leaders understand the need to make operational information available to authorized personnel in context, anywhere, on any device, anytime, and for any valid purpose.

This article was originally posted on ARC Advisory Group.