Abstract
The end-of-life (EoL) management of industrial assets is a critical aspect of sustainable manufacturing and resource efficiency. As industries strive to minimize waste, reduce environmental impact, extend the useful life of assets, and support circular manufacturing objectives, there is an increasing demand for data-driven and forwardlooking strategies to guide EoL decision-making. Traditionally, such decisions have relied on static assessments and reactive interventions, which often fail to account for real-time asset condition or long-term value. Digital Twin (DT) technology has emerged as a transformative enabler across asset lifecycles. While DTs are well-established in supporting middle-of-life (MoL) activities, such as condition monitoring and predictive maintenance, their strategic potential for informing EoL decisions remains underexplored. Current applications tend to focus on operational and tactical levels, lacking structured approaches to support higher-level strategic decisions such as EoL planning and asset lifecycle extension assessment. This paper addresses this gap through a structured literature review that maps existing DT-enabled indicators and technologies across operational, tactical, and strategic decision-making levels. A conceptual framework is then proposed to illustrate how DT-generated outputs, especially operational indicators like RUL, can evolve into actionable insights for EoL strategy formulation. The findings underscore the importance of reinterpreting current indicators and developing new value-centric metrics to support circular and sustainable asset lifecycle management. This study offers a foundation for repositioning DTs as not only diagnostic tools but also as strategic tools in EoL decision support.
