Verification and validation of large language models with retrieval-augmented generation in industrial automation systems

WO2026102013A3 Publication Date: 2026-06-18SIEMENS AG +1
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Patent Information

Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
SIEMENS AG
Filing Date
2025-11-05
Publication Date
2026-06-18

AI Technical Summary

⚠Technical Problem

The deployment of large language models (LLMs) with retrieval-augmented generation (RAG) systems in industrial automation environments faces unique challenges such as inconsistent outputs, unreliable responses, real-time performance requirements, environmental adaptability, and lack of comprehensive verification and validation frameworks, which can lead to safety hazards and operational inefficiencies.

⚗Method used

A comprehensive verification and validation framework that integrates various testing components, including model consistency verification, data quality verification, performance verification, and robustness verification, with an API server coordinating these components to ensure reliable operation and adaptability across industrial environments.

🎯Benefits of technology

Enhances defect detection capabilities and maintains compliance with industrial safety and reliability standards by systematically addressing complex failure modes and real-time performance requirements, ensuring transparent and auditable decision-making.

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Abstract

The deployment of large language model (LLM) and retrieval-augmented generation (RAG) systems in industrial automation environments present unique technical challenges that are not adequately addressed by conventional software validation approaches. A computing system can define a comprehensive architecture with cross-validation methodologies that can perform systematic detection of complex failure modes that might be missed by conventional testing approaches, while providing the reliability, safety, and real-time performance characteristics essential for successful deployment of LLM and RAG systems in industrial automation environments.
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