Granular computing–based development of service process reference models in social manufacturing contexts

Abstract

Serving as sustainable blueprints for the development of individualized services reference models advance in both flexibility and maturity. There is an increasing use of process reference models to establish inter-organizational services in social manufacturing contexts. This article describes a granular computing–based inductive approach for the development of process reference models, based on the existing historical service cases formed by co-operating partners. It is a three-step integrated approach. First, the similarities of service processes are exploited based on both the activity properties and the process sequential relations. Second, the similar service processes are clustered in an optimal granularity. Third, the common subgraphs are identified for each cluster by analyzing their nodes’ matches, and finally merged into reference models. An example is studied to validate its effectiveness and practicability.