Automation solutions for dismantling processes with high efficiency

  • Likely project output: xx April 20xx
  • Theme 1: Pre-treatment and second-life management
  • Main Centre Node: University of Woolongong

Project summary

Almost all recycling methods require some degree of disassembly. There are, however, major challenges in disassembling EV batteries due to the large variety of types, sizes, and design complexity. Industries that operate in EV Li-Ion battery disassembly are mostly manual, which is not only time consuming and expensive, but also exposes workers to potential hazards. Automation is a promising solution to increase efficiency and safety, but it is currently challenging due to non-standardized designs.

Benefits to industry

We will advance the use of AI and robotic manipulation, not simply to dismantle packs, but to include sensory capability and intelligence as part of the robotic system to recognise parts and fixings from packs which they may never have seen before and manipulate these in the way a human operator would. An automatic and adjustable disassembly system will be developed, which includes three significant functionalities: battery pack information detection, optimizing disassembly order, and automatic robotic dismantling processes, towards rapid and efficient automated disassembly. Niche input from informal collaborators at UoA’s AIML will also be harnessed as a part of this program, teamed with our CI and Iondrive capabilities.

Project Lead & Investigators

Co-Leads

  • David Wexler (UoW)
  • Philip van Eyk (UoA)

Chief Investigators

  • Philip van Eyk (Leader, UoA)
  • Da-Wei Wang (UNSW)
  • Huijun Li (UoW)

Partner Investigator and Industry Placement

  • Keong Chan, Iondrive