用大模型辅助生成设备故障分析文档，提升效率与专业性
FMEA Builder: Expert Guided Text Generation for Equipment Maintenance
- 基于大语言模型构建专家引导的文本生成系统
- 可正确生成超过一半FMEA核心内容，准确率显著
- 适合可靠性工程师快速创建关键设备维护文档
基础模型在多个领域生成任务中展现出巨大潜力。本文探讨了利用基础模型生成与关键资产相关的结构化文档。故障模式与影响分析（FMEA）记录设备组成、可能的失效方式及其后果。我们的系统通过大语言模型实现快速且经专家监督的FMEA文档生成。实证分析表明，基础模型可正确生成超过一半FMEA的关键内容。对可靠性专业人士的问卷调查结果显示，他们对使用生成式AI创建关键资产文档持积极态度。
原文摘要 · Abstract (English)
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.
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