An information-integrated circularity passport for tribological systems: a trajectory-aware framework and IIoT-compatible scoring algorithm

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a novel framework for dynamic circularity assessment in degradation-governed systems, advancing lifecycle theory.

🏢実務担当者:Offers a concrete scoring algorithm and ecolabeling scheme that can be integrated with IIoT and digital twin systems for product passports.

🏛政策担当者:Highlights the need for trajectory-aware circularity standards in product passport regulations, potentially informing future policy design.

Tribological systems, governing friction, wear, lubrication, and sealing, account for approximately 20–23% of global energy consumption and represent a structurally underserved domain for circular economy (CE) governance. Existing Digital Product Passports (DPPs), mandated under the EU Ecodesign for Sustainable Products Regulation, treat sustainability attributes as static product properties, yet tribological performance evolves continuously as a function of interface degradation, regime transitions, and operational duty cycles. This trajectory-based character makes conventional, snapshot-based circularity frameworks systematically inadequate for this class of industrial devices. Adopting a Design Science Research (DSR) methodology, this study develops and demonstrates a data-driven Circularity Passport framework specifically designed for tribological devices. The artefact comprises two coupled components: (i) a matrix-based conceptual framework that structures sustainability assessment across three lifecycle phases, production, use, and end-of-life, using four tribology-specific sustainability dimensions, with explicit operating-envelope constraints and provenance-tagged data entries; and (ii) a multi-criteria scoring algorithm that normalizes heterogeneous lifecycle indicators onto a common 0–100+ scale, aggregates them through a transparent two-level weighting scheme, and maps the composite index to a five-class chromatic ecolabeling output (A–E). The algorithm is designed for state-dependent recalculation when operational monitoring detects regime transitions, making it compatible with Industrial Internet of Things (IIoT) data streams and digital twin architectures. The framework is demonstrated through the exemplar case of passenger car tyres, integrating production-phase carbon emissions, rolling-resistance energy losses, durability relative to vehicle service life, recycled content, and end-of-life material recovery into a reproducible composite score. The study advances lifecycle theory by demonstrating that in degradation-governed systems, circularity governance requires trajectory-aware information integration.

• openalex https://doi.org/10.1016/j.jii.2026.101151first seen 2026-08-02 19:26:19