A DPP-enabled decision support system for end-of-life strategy recommendation

The transition towards a circular economy requires reliable lifecycle information to support end-of-life (EoL) decision-making. Using a sample luminaire, this study proposes a decision-support component designed to enhance Digital Product Passport (DPP) functionality by integrating lifecycle data, condition monitoring, predictive analytics, and stakeholder priorities for end-of-life strategy selection. Guided by Axiomatic Design principles, a prototype platform was developed and demonstrated for the representative lighting fixture. The system combines product information, sensor-derived condition indicators, remaining useful life estimation, anomaly detection, and multi-criteria user preferences to generate probabilistic recommendations for alternative EoL strategies. An interactive dashboard was implemented to provide an intuitive user interface and support transparency and usability. Industrial evaluation with domain experts confirmed the conceptual validity and practical relevance of the approach while highlighting challenges related to data governance, interoperability, cybersecurity, and business model integration. The findings demonstrate the potential of intelligent DPP-enabled systems to support circular decision-making and sustainable lifecycle management.