Remanufacturing is fundamentally more challenging than traditional manufacturing because of the extreme uncertainty, variability, and incompleteness of end-of-life (EoL) products. In manufacturing, components are usually standardized and processes are repeatable; however, remanufacturing should cope with unknown product conditions, unpredictable disassembly sequences, missing or damaged parts, various product generations, and heterogeneous product types, all while meeting economic and sustainability goals. 

At the same time, remanufacturing is urgently needed as the growing volume of discarded electronics and the scarcity of critical materials demand intelligent and automated solutions to facilitate a circular economy. Despite this urgency, few research groups are systematically investigating and advancing disassembly and remanufacturing automation, and the broader control and robotics communities are mainly unaware of the unique challenges and opportunities in this emerging domain. 

This tutorial will highlight what makes remanufacturing fundamentally different from manufacturing, covering technical challenges in decision making under uncertainty, multimodal perception and inspection, flexible task and motion planning, force-aware manipulation, and workforce-in-the-loop training. Drawing from the organizers’ extensive expertise in robotics and sustainable automation, the tutorial session will provide attendees with a unified understanding of how robotics, control, and AI can jointly support scalable, safe, and intelligent remanufacturing systems.


Schedule of Talks

0:00-0:30Introduction to Remanufacturing and Unique Challenges in
Remanufacturing Automation
Minghui Zheng,
Sara Behdad
0:30-0:45Remanufacturing Automation in Decision-Making PhasesSara Behdad
0:45-1:00Remanufacturing Automation in Robotic Execution PhasesMinghui Zheng
1:00-1:15Vision-Language-Action models for robotic disassemblySibo Tian
1:15-1:30Adaptive Motion Planning via Contact-Based Intent Inference for robotic disassemblyJiurun Song
  • Minghui Zheng

    Texas A&M University

  • Sara Behdad

    University of Florida