Preprint: Human-Cobot Energy Feedback for Closed-Loop Sustainable Design for Disassembly: A Taxonomy

Abstract

This paper presents a focused analysis and taxonomy of energy feedback from human-cobot collaboration within a closed-loop sustainable design framework. Current research areas, including energy-efficient planning, design for disassembly, closed-loop design in product lifecycle management, and human-cobot collaboration, remain fragmented. Planning methods typically optimize production around a fixed product architecture, while design for disassembly relies primarily on static metrics. Studies on collaborative disassembly and robot energy modeling show that task-level energy, intervention rates, and failure or rerouting events can be measured. However, these data are rarely integrated into early product and process design. To address this gap, the proposed taxonomy is divided into eight dimensions: energy feedback type, human-robot interaction modality, energy metrics, closed-loop control logic, system architecture, industrial application, time scale, and sustainability indicators. Two cross-classifications are then introduced: an ontological structure to integrate product lifecycle management, knowledge graphs, and digital twins, and a multi-criteria analysis to balance energy, ergonomics, safety, quality, productivity, and circularity.