DUCTILE: Agentic Large Language Model Orchestration of Engineering Analysis in Product Development Design Practice

Artikel i vetenskaplig tidskrift, 2026

Engineering analysis automation in product development relies on rigid interfaces between tools, data formats, and documented processes. When these interfaces change, as they routinely do as the product evolves in the engineering ecosystem, the automation support breaks. This article presents a DUCTILE (delegated, user-supervised coordination of tool- and document-integrated large language model (LLM)-enabled) agentic orchestration, an approach for developing, executing, and evaluating LLM-based agentic automation support of engineering analysis tasks. The approach separates adaptive orchestration, performed by the LLM agent, from deterministic execution, performed by verified engineering tools. The agent interprets documented design practices, inspects input data, and adapts the processing path, while the engineer supervises and exercises final judgment. DUCTILE is demonstrated on a constrained but realistic industrial structural analysis task at an aerospace manufacturer, where the agent handled input deviations in format, units, naming conventions, and methodology that would break traditional scripted pipelines. Evaluation against expert-defined acceptance criteria and deployment with practicing engineers confirm that the approach produces correct, methodologically compliant results across 10 repeated independent runs. The article discusses the paradigm shift and the practical consequences of adopting agentic automation, including unintended effects on the nature of engineering work when removing mundane tasks and creating an exhausting supervisory role.