Supporting repairability analysis through graph-based visualisation

Abstract Repairability is a key aspect of circular economy strategies, contributing to product longevity and resource efficiency. However, existing assessment methods often provide limited insight into product architecture and rarely combine visual and quantitative analysis. This study proposes a graph-based modelling approach for repairability assessment that integrates network metrics with structural visualisation. Building on EN 45554, an EN 45554-based Repair Matrix (RM) is used to assign repair-related attributes to product components and their connections. These attributes are represented as nodes and edges within a network, enabling both visual exploration and quantitative analysis of product architecture. A three-stage methodology is developed: (i) input data structuring, (ii) graph visualisation using Gephi software and (iii) analytical output. In addition, a novel graph-based Repair Index (RI) is introduced to quantify repairability at the system level. The approach is demonstrated through an in-depth case study of a capsule coffee machine. The results show that graph metrics such as degree, modularity, eccentricity and betweenness centrality effectively reveal structural complexity, accessibility constraints and critical components. The proposed method offers a conceptually scalable and interpretable framework that supports design-for-repair strategies by highlighting component dependencies and optimising disassembly logic. Overall, this work contributes to the development of more repairable and sustainable product architectures, supporting circular economy objectives.