Case Studies
Proven results from PANDAS across planning, compliance, engineering, and predictive maintenance.
An emergent plant condition processed through the complete PANDAS workflow. The system autonomously retrieved the applicable Technical Specification and plant procedures, then generated through deterministic pipelines: condition report, operability determination, NRC reporting evaluation, corrective work orders, compliance forms, P6 schedule, enterprise notifications, and stakeholder meeting coordination. Every output sourced from retrieved plant documentation.
PANDAS received a field condition, autonomously identified and retrieved the applicable Technical Specification LCO, generated a Condition Report from plant-specific source data, performed a complete Operability Determination with completion time tracking against the actual LCO requirements, evaluated NRC reporting thresholds against 10 CFR 50.72 and 50.73 criteria, and generated corrective scope. All determinations built from retrieved documentation.
Complete Design Change Package from a natural language modification description. PANDAS autonomously retrieved the applicable design basis documents, FSAR sections, and regulatory guides, then produced safety classification, quality group, ASME class, seismic and EQ evaluation, 50.59 screening, codes and standards, interface review, affected documents, and Bill of Materials. Every classification determined against retrieved source material.
Complete reliability assessment built from retrieved source data: industry failure rate databases, fleet operating experience reports, NRC inspection history, and plant-specific maintenance and condition records. Economic comparison of reactive failure cost against proactive replacement. Differentiated between identical components at the same plant based on actual operating history, not industry averages.
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