Modularization Design for Smart Industrial Service Ecosystem: A Framework Based on the Smart Industrial Service Identification Blueprint and Hypergraph Clustering

Compared with the conventional industrial product–service system, smart service ecosystem (SISE) mentioned in this study contains more activity according to characteristics of context, participation various stakeholders and interconnected technologies. This proposes a detailed modularization design framework for SISE, which can be referenced contexts. Firstly, context-based identification blueprint (SISIB) is proposed describe operation model SISE identify components. The SISIB ensure that designers understand work process system improve or carry out (SIS) component identification. In case article, SIS components from different levels systematically identified. Secondly, collaboration sustainable development principles are measuring correlation degree among Considering complexity multi-level distribution nature components, hyperedge concept presented realize comparison evaluation linguistics applied handle decision uncertainties. With method, effective between formed few hyperedges. Thirdly, hypergraph clustering theory define module partition. triangular fuzzy number first used strength comply vague experts. normalized cut principle realized using K nearest neighbors (kNN) algorithm, new unified related Laplace matrix obtained. Then, relevant eigenvalue gained, visualization k-means algorithm. After performed, several modular schemes gained. order select best scheme, we modularity quality measurement criteria. Regarding these three steps, renewable electricity verify viability feasibility design. result showed visible clearance connected context. scheme based on also achieve high convenient evaluation.