Wireless Cyber-Physical System Performance Evaluation Through a Graph Database Approach

Abstract

Abstract Despite the huge efforts to deploy wireless communications technologies in smart manufacturing scenarios, some manufacturing sectors are still slow to massive adoption. This slowness of widespread adoption of wireless technologies in cyber-physical systems (CPSs) is partly due to not fully understanding the detailed impact of wireless deployment on the physical processes especially in the cases that require low latency and high reliability communications. In this article, we introduce an approach to integrate wireless network traffic data and physical processes data to evaluate the impact of wireless communications on the performance of a manufacturing factory work cell. The proposed approach is introduced through the discussion of an engineering use case. A testbed that emulates a robotic manufacturing factory work cell is constructed using two collaborative-grade robot arms, machine emulators, and wireless communication devices. All network traffic data are collected and physical process data, including the robots and machines states and various supervisory control commands, is also collected and synchronized with the network data. The data are then integrated where redundant data are removed and correlated activities are connected in a graph database. A data model is proposed, developed, and elaborated; the database is then populated with events from the testbed, and the resulting graph is presented. Query commands are then presented as a means to examine and analyze network performance and relationships within the components of the network. Moreover, we detail the way by which this approach is used to study the impact of wireless communications on the physical processes and illustrate the impact of various wireless network parameters on the performance of the emulated manufacturing work cell. This approach can be deployed as a building block for various descriptive and predictive wireless analysis tools for CPS.