Redefining End-of-Life: Intelligent Automation for Electronics Remanufacturing Systems

Abstract

Remanufacturing is fundamentally more challenging than traditional manufacturing due to the significant uncertainty, variability, and incompleteness inherent in end-of-life (EoL) products. At the same time, it has become increasingly essential and urgent for facilitating a circular economy, driven by the growing volume of discarded electronic products and the escalating scarcity of critical materials. In this paper, we review the existing literature and examine the key challenges as well as emerging opportunities in intelligent automation for EoL electronics remanufacturing, providing a comprehensive overview of how robotics, control, and artificial intelligence (AI) can jointly enable scalable, safe, and intelligent remanufacturing systems. This paper starts with the definition, scope, and motivation of remanufacturing within the context of a circular economy, highlighting its societal and environmental significance. Then it delves into intelligent automation approaches for disassembly, inspection, sorting, and component reprocessing in this domain, covering advanced methods for multimodal perception, decision-making under uncertainty, flexible planning algorithms, and force-aware manipulation. The paper further reviews several emerging techniques, including large foundation models, human-in-the-loop integration, and digital twins that have the potential to support future research in this area. By integrating these topics, we aim to illustrate how next-generation remanufacturing systems can achieve robust, adaptable, and efficient operation in the face of complex real-world challenges.

Figures (9)

• Figure 1: The system-level process of intelligent remanufacturing, supported jointly by advanced robotics, control, and artificial intelligence.
• Figure 2: Comparison between manufacturing and remanufacturing. The manufacturing images are sourced from kuka.com, while the remanufacturing images are sourced from Sunnking Sustainable Solutions, Inc.
• Figure 3: Paper overview. Sections II and III present a system-level review of intelligent automation in remanufacturing. Section IV introduces several emerging techniques to support future research in this domain. Sections V and VI discuss the key challenges and conclude the paper.
• Figure 4: Taxonomy of the literature reviewed in this paper on intelligent automation for remanufacturing. The figure organizes the references by remanufacturing stage and technical theme, including disassembly, other remanufacturing stages, and emerging techniques.
• Figure 5: Demonstration of perception, task planning, motion planning, and manipulation in a disassembly example.