Manufacturing service composition model based on synergy effect: A social network analysis approach

Service social network is an umbrella term used to describe several interaction and collaboration phenomena that are shaping the future of how services are provided on the cloud manufacturing platform. Social relationship plays an important role when services are orchestrated with each other to build manufacturing business process, a role which has not been adequately investigated in previous research. The existing manufacturing service composition methods consider functional qualifications and Quality of Service (QoS) as major competitiveness factors. It is difficult to adopt them to situations where synergy effect is required and social relationships have significant impact on ensuring effective resources, information and knowledge hand-off in the complex task process. Focusing on the social collaboration feature of manufacturing services, a service composition method based on synergy effect is proposed. According to the data of service interaction and cooperation on the cloud platform, we extract and describe service social network and five kinds of relationships, namely interactive transaction, co-community, physical distance, resource-related, social similarity relationship. Based on the calculation of these relationships strength, the service synergy network is derived through the weighted aggregation. A service selection model that maximizes the overall synergy effect based on collaboration requirement is presented. The validity and advantages of our model and algorithm is validated through simulation experiment of intelligent automobile cloud manufacturing. The results show that our approach is not only efficient, but also finds better service scheme in line with the actual manufacturing scenario.