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Human-Robot Collaboration for Flexible Manufacturing Systems

Distinguished Research Seminar Series

20250430ISE Website Event Image 2
  • Date

    30 Apr 2025

  • Organiser

    Department of Industrial and Systems Engineering, PolyU

  • Time

    10:00 - 11:30

  • Venue

    CD302  

Speaker

Prof. Qing Chang

20250430-ISE Website_Poster (2)

Summary

Modern manufacturing systems require agile and adaptable production environments to keep pace with rapidly evolving market demands, disruptions, and uncertainties. To achieve efficient mass customization while maintaining competitiveness, innovative solutions are essential. Flexible Manufacturing Systems (FMS) have emerged as a key enabler of the human-centric manufacturing paradigm, where human-robot/machine collaboration (HRC) enhances productivity and flexibility in both current and future factories. In this presentation, I will discuss our recent research addressing two critical challenges in HRC for FMS: (1) robot programming and reprogramming, and (2) intelligent decision-making and adaptive control for production coordination. First, I will present our work on robot learning from human demonstrations, which simplifies programming and reprogramming, enabling non-experts to interact seamlessly with robots. I will also introduce our research on multi-manipulator collaboration. Next, I will examine the role of intelligent decision-making and real-time coordinated control of robots and humans in optimizing production scheduling. These capabilities are crucial for enhancing manufacturing efficiency, particularly in mass customization environments. I will conclude by outlining our future directions in this field.

Keynote Speaker

Prof. Qing Chang

Prof. Qing Chang

Professor
Mechanical and Aerospace Engineering, University of Virginia, USA

Dr. Qing (Cindy) Chang is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia (UVA). With a strong emphasis on sustainability and efficiency, her research primarily revolves around the modeling, analysis, and control of dynamic manufacturing systems. She leverages adaptive control and machine learning-based techniques to optimize the performance of smart manufacturing systems and explores the potential of human-robot collaborations in the manufacturing domain. Dr. Chang is a recipient of the National Science Foundation (NSF) CAREER Award and an elected Fellow of ASME and SME, as well as a Senior Member of IEEE. In 2020, she was recognized by SME as one of the “20 Most Influential Professors in Smart Manufacturing.” Prior to her academic career, Dr. Chang amassed a decade of experience at General Motors Global Research & Development Center, where she received the highest award in GM, Boss Kettering Awards, three times in recognition of her research on improving production efficiency. She has served in leadership roles on numerous international and domestic conference and symposium organizing committees, as well as in editorial and leadership positions within ASME, IEEE, and NAMRI/SME.

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