BKO AI

LNG Plant Operations and Surveillance

BKOAI delivered a full suite of LNG operations surveillance screens in PI Vision for a large LNG facility, supported by a complete, standardized PI AF hierarchy designed to improve remote visibility, accelerate anomaly detection, and enable scalable deployment across LNG trains

Goals

Deploy operations surveillance screens for a large LNG facility before first LNG introduction.
Create a reusable, standardized data template hierarchy to streamline future train expansions.
Provide a consistent PI AF data foundation for both PI Vision operations screens and Seeq analytics.
Improve operational visibility across distributed facility areas, including the control room, administrative offices, and berths.

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Challenges

Inherited an incomplete PI AF database with missing PI tags and inadequate documentation.
Faced a compressed 5–6 month timeline after previous contractors failed to deliver.
Needed to support multiple operational areas and stakeholders while maintaining a unified asset hierarchy.
Needed to incorporate missing PI tags incrementally as they became available on the production PI Server.

Solutions

Developed PI AF templates based on P&IDs for gas inlets, turbines, and utilities.
Implemented a three-tier PI Vision screen hierarchy, including calculations for commingled composition and tank volumes.
Configured element hierarchies to provide unified asset context for Seeq analytics.
Added startup-event templates for propane unloading, gas turbine operations, and LNG tank loading and unloading activities.

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Results

Enabled remote operational visibility across control rooms, administrative offices, and berths.
Reduced future engineering effort through reusable, scalable PI AF asset templates.
Accelerated anomaly detection using rate-of-change calculations to identify abnormal conditions.
Established a standardized PI Vision architecture that can be efficiently copied and adapted for future LNG trains.

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