Augmented Reality for Circular Maintenance: A Smart Testbed for Sustainable Asset Lifecycles

Abstract

As industries adopt circular economy (CE) principles, maintenance must extend asset lifespans, enable reuse, and minimise resource waste. Current digital systems rarely provide the contextual intelligence to guide repairability and lifecycle decisions. This paper presents a modular Augmented Reality (AR) testbed that integrates predictive diagnostics, prescriptive recommendations and contextual visualisation to support CE-aligned maintenance in industrial environments. Designed for offline simulation and real-time deployment, it enables technician training, live diagnostics and scenario-based evaluation of reuse, repair or replacement. Real-Time sensor data and historical records generate spatially anchored overlays that expose sustainability metrics at the point of work. A walk-through case of electric vehicle (EV) battery degradation demonstrates how risk scores and reuse suggestions can be operationalised within the testbed. Preliminary demonstrations indicate potential to improve traceability, reduce unnecessary replacements and enhance knowledge transfer. The testbed offers a flexible platform for field studies and rapid prototyping of sustainable asset management workflows.