activity
20232026
most citedLarge Language Model-Enabled Multi-Agent Manufacturing Systems

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

eess.SY2026

NeuroSymbolic Robustness Analysis for Discrete Systems with Respect to Transition Deviations

Shih-Jie Shih, Jonghan Lim, Ilya Kovalenko +1

Supervisory control of discrete-event systems provides formal guarantees of correctness with respect to a plant model and specification. However, these guarantees heavily rely on t…

cs.MA2026

Logic-Based Verification of Task Allocation for LLM-Enabled Multi-Agent Manufacturing Systems

Jonghan Lim, Mostafa Tavakkoli Anbarani, Rômulo Meira-Góes +1

Manufacturing industries are facing increasing product variability due to the growing demand for personalized products. Under these conditions, ensuring safety becomes challenging…

cs.RO2026

CoViLLM: An Adaptive Human-Robot Collaborative Assembly Framework Using Large Language Models

Jiabao Zhao, Jonghan Lim, Hongliang Li +1

With increasing demand for mass customization, traditional manufacturing robots that rely on rule-based operations lack the flexibility to accommodate customized or new product var…

cs.MA2025

A Large Language Model-Enabled Control Architecture for Dynamic Resource Capability Exploration in Multi-Agent Manufacturing Systems

Jonghan Lim, Ilya Kovalenko

Manufacturing environments are becoming more complex and unpredictable due to factors such as demand variations and shorter product lifespans. This complexity requires real-time de…

cs.RO2025

Dynamic Task Adaptation for Multi-Robot Manufacturing Systems with Large Language Models

Jonghan Lim, Ilya Kovalenko

Recent manufacturing systems are increasingly adopting multi-robot collaboration to handle complex and dynamic environments. While multi-agent architectures support decentralized c…

cs.RO2024★ 1 cited

Enhancing Human-Robot Collaborative Assembly in Manufacturing Systems Using Large Language Models

Jonghan Lim, Sujani Patel, Alex Evans +3

The development of human-robot collaboration has the ability to improve manufacturing system performance by leveraging the unique strengths of both humans and robots. On the shop f…

cs.MA2024★ 1 cited

Large Language Model-Enabled Multi-Agent Manufacturing Systems

Jonghan Lim, Birgit Vogel-Heuser, Ilya Kovalenko

Traditional manufacturing faces challenges adapting to dynamic environments and quickly responding to manufacturing changes. The use of multi-agent systems has improved adaptabilit…

cs.MA2023

Ontology-Based Feedback to Improve Runtime Control for Multi-Agent Manufacturing Systems

Jonghan Lim, Leander Pfeiffer, Felix Ocker +2

Improving the overall equipment effectiveness (OEE) of machines on the shop floor is crucial to ensure the productivity and efficiency of manufacturing systems. To achieve the goal…