1 citations · 2 across the 11 of their papers we have counts for
11 papers
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…
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…
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…
A Model Predictive Control Framework to Enhance Safety and Quality in Mobile Additive Manufacturing Systems
Yifei Li, Joshua A. Robbins, Guha Manogharan +2
In recent years, the demand for customized, on-demand production has grown in the manufacturing sector. Additive Manufacturing (AM) has emerged as a promising technology to enhance…
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…
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…
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…
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…
A Mobile Additive Manufacturing Robot Framework for Smart Manufacturing Systems
Yifei Li, Jeongwon Park, Guha Manogharan +2
Recent technological innovations in the areas of additive manufacturing and collaborative robotics have paved the way toward realizing the concept of on-demand, personalized produc…
A System-Level Energy-Efficient Digital Twin Framework for Runtime Control of Batch Manufacturing Processes
Hongliang Li, Herschel C. Pangborn, Ilya Kovalenko
The manufacturing sector has a substantial influence on worldwide energy consumption. Therefore, improving manufacturing system energy efficiency is becoming increasingly important…
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…