activity
20222026
most citedExploring LLMs for Verifying Technical System Specifications Against Requirements

1 citations · 1 across the 10 of their papers we have counts for

collaborators

16 papers

cs.AI2026

Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges

Vincent Henkel, Felix Gehlhoff, David Kube +13

Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision support, process monitoring, and e…

cs.AI2025

Benchmark for Planning and Control with Large Language Model Agents: Blocksworld with Model Context Protocol

Niklas Jobs, Luis Miguel Vieira da Silva, Jayanth Somashekaraiah +3

Industrial automation increasingly requires flexible control strategies that can adapt to changing tasks and environments. Agents based on Large Language Models (LLMs) offer potent…

cs.AI2025

Bridging Engineering and AI Planning through Model-Based Knowledge Transformation for the Validation of Automated Production System Variants

Hamied Nabizada, Lasse Beers, Alain Chahine +3

Engineering models created in Model-Based Systems Engineering (MBSE) environments contain detailed information about system structure and behavior. However, they typically lack sym…

cs.AI2025

Consistency Verification in Ontology-Based Process Models with Parameter Interdependencies

Tom Jeleniewski, Hamied Nabizada, Jonathan Reif +2

The formalization of process knowledge using ontologies enables consistent modeling of parameter interdependencies in manufacturing. These interdependencies are typically represent…

cs.SE2025

An Expert Survey on Models and Digital Twins

Jonathan Reif, Daniel Dittler, Milapji Singh Gill +5

Digital Twins (DTs) are becoming increasingly vital for future industrial applications, enhancing monitoring, control, and optimization of physical assets. This enhancement is made…

cs.AI2025

Automated Validation of Textual Constraints Against AutomationML via LLMs and SHACL

Tom Westermann, Aljosha Köcher, Felix Gehlhoff

AutomationML (AML) enables standardized data exchange in engineering, yet existing recommendations for proper AML modeling are typically formulated as informal and textual constrai…