Collaborative Robot based Architecture to Train Flexible Automated Disassembly Systems for Critical Materials

Abstract

The capability of disassembly operations contributes to controlling the volume and flow of materials in reverse feedback cycles. An inability to achieve certain levels of volume or flow in feedback cycles from end-of-use products can risk the efficiency and profitability of recycling, remanufacturing, and reuse. Disassembly systems face a significant challenge to achieving large-scale operations due to uncertainty in end-of-use product quality, quantity and timing. In order to manage these uncertainties efficiently, disassembly systems must be flexible, however, they must be automated to achieve large-scale operations. In this paper, a cyber-physical architecture is conceptualized utilizing human-robot interaction via collaborative robots (Cobot) to train a flexible automated disassembly system. As a first step to achieving this system, this paper proposes and demonstrates a method to extract critical disassembly information from a human-cobot disassembly training work-cell that would be used to distribute tasks to processes in a high volume disassembly line.