FMEA Builder: Expert Guided Text Generation for Equipment Maintenance
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Abstract (arXiv)
Foundation models show great promise for generative tasks in many domains. Here we discuss the use of foundation models to generate structured documents related to critical assets. A Failure Mode and Effects Analysis (FMEA) captures the composition of an asset or piece of equipment, the ways it may fail and the consequences thereof. Our system uses large language models to enable fast and expert supervised generation of new FMEA documents. Empirical analysis shows that foundation models can correctly generate over half of an FMEA's key content. Results from polling audiences of reliability professionals show a positive outlook on using generative AI to create these documents for critical assets.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 7 Nov 2024.
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References · 6
- 2017Attention Is All You Needcited by 60,361
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
- 2019The Curious Case of Neural Text Degenerationcited by 2,916
- 2021What Makes Good In-Context Examples for GPT-3?cited by 1,195
- 2024RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculturecited by 81
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