Modeling of manufacturing resources towards an interactive Resource Social Network

The rapidly changing market has stimulated the emergence of self-organizing mechanisms in intelligent manufacturing systems, where resources are generally capable of making decisions through intercommunications and interoperations to maximize system adaptivity. With the increasing number of exceptional events during manufacturing, those mechanisms might eventually fail to react timely to situations of multiple resource conflicts. In this work, we discussed the social networks consisting of various manufacturing resources and provided the relevant modeling techniques including the Resource Description Framework and the Finite State Machine. The function and behavior models can support the autonomous interactions and collaborations among resources, while the communication hub connected the resources and formed a peer-to-peer network. On this basis, the dynamic features of manufacturing networks including the exception propagation phenomenon can be analyzed. A case was studied to identify the bottleneck resources using the complex network theory. This work has provided an analytical platform to optimize manufacturing resources using complex network and graph theory.