A Compliance-Preserving Retrieval System for Aircraft MRO Task Search
Byungho Jo

TL;DR
This paper introduces a compliance-preserving retrieval system for aircraft MRO that enhances efficiency by integrating semantic search with certified legacy viewers, achieving high accuracy and significant time savings.
Contribution
It presents a novel retrieval system that maintains regulatory compliance while significantly reducing search time in aircraft maintenance operations.
Findings
Over 90% retrieval accuracy on synthetic queries
90.9% top-10 success rate in user studies
95% reduction in lookup time from minutes to seconds
Abstract
Aircraft Maintenance Technicians (AMTs) spend up to 30% of work time searching manuals, a documented efficiency bottleneck in MRO operations where every procedure must be traceable to certified sources. We present a compliance-preserving retrieval system that adapts LLM reranking and semantic search to aviation MRO environments by operating alongside, rather than replacing, certified legacy viewers. The system constructs revision-robust embeddings from ATA chapter hierarchies and uses vision-language parsing to structure certified content, allowing technicians to preview ranked tasks and access verified procedures in existing viewers. Evaluation on 49k synthetic queries achieves >90% retrieval accuracy, while bilingual controlled studies with 10 licensed AMTs demonstrate 90.9% top-10 success rate and 95% reduction in lookup time, from 6-15 minutes to 18 seconds per task. These gains…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Topic Modeling · Natural Language Processing Techniques
