The Challenge of Searching PSI
Imagine a maintenance engineer looking for the operating procedure for a specific pump in the Area 1 hydrocracker unit. A SharePoint search for “pump” might return 300+ results—spanning multiple units, systems, and years. The signal gets buried in noise.
This isn’t just frustrating; it can delay work, increase the risk of human error, or cause teams to miss important updates or hazard controls.
The Answer: Asset Structure Navigation
To move beyond keyword chaos, you need to include an asset structure in your SharePoint library that reflects the facility and enterprise:
- By site, area, unit, system, and equipment
- Using asset tag metadata pulled from your CMMS or asset registry
- Enabling filtered views based on equipment function, system context, or plant area
This lets users “think like the plant” and rapidly drill down to the specific PSI they need—whether it’s a datasheet, procedure, or PHA.
But even with asset structured navigation, there’s room to go further.
Enter the AI Agent: Assisting Intelligent Search for PSI
Once the asset structure hierarchy is in place and documents are tagged properly, the next evolution is deploying an AI Agent to assist with PSI search and retrieval.
Here’s how it works:
1. Natural Language Queries
Instead of relying solely on keywords, users can ask questions like:
- “Show the current released maintenance procedure for P-1201 in the Area 1.”
- “What MOCs are related to pump seal failures in Area 1?”
The AI Agent interprets the context—asset location, function, and document type—then filters and ranks the most relevant PSI.
2. Context-Aware Filtering
The AI Agent understands metadata relationships:
- It knows that “P-1201” is a pump in the Area 1 hydrocracker unit.
- It recognizes associated documents based on tags like equipment ID, system, or failure mode.
This eliminates false positives and delivers precise results.
3. Integration with Facility Asset Model
If your asset hierarchy is built into SharePoint or synchronized from ERP or CMMS, the AI Agent can:
- Traverse that structure
- Maintain context during exploration
- Recommend related documents (e.g., P&IDs, PHAs, MOCs, inspection reports, or spare parts lists)
4. Learning from User Behavior
Over time, the agent can learn patterns:
- Frequently accessed documents by job role or plant area
- Preferred document types (e.g., datasheets vs. procedures)
- Common follow-up questions (e.g., “Is this pump in the current SIL study?”)
This drives continuous improvement in search performance and user satisfaction.
The Bottom Line
SharePoint becomes far more powerful when paired with two strategic enablers:
- A well-defined facility asset structure
- An AI Agent capable of intelligent, context-aware search
Together, they greatly enhance SharePoint’s search capabilities to support safer, faster, and more accurate decision-making across engineering and operations. The FACILEX® PSM suite supports intelligent search using an asset-based structure. Contact Gateway to start an AI-PSM project.
